One of the most time consuming aspects of the dissertation is the statistics part of the dissertation. Because statistics are needed for the dissertation, and because a dissertation is needed for a student to receive his/her doctoral degree, the statistics part of the dissertation is essentially the most important part of the dissertation.
There is help, however, and this help comes in the form of dissertation statistics help. Dissertation statistics help can help with every single statistical issue in a dissertation. Dissertation statistics help can guide the student step-by-step through the statistics, and dissertation statistics help can be an invaluable resource for all students pursuing their doctoral degree.
Dissertation statistics help is invaluable because dissertation statistics help can answer all questions a student might have. While students can certainly ask their advisor these questions, oftentimes a student’s advisor is unavailable. Dissertation statistics help, however, is always available and dissertation statistics help is there only to help the student. Thus, dissertation statistics help is like a permanent advisor for the student.
And just like an advisor, dissertation statistics help guides and assists the students who are seeking their doctoral degree. Dissertation statistics help provides all of the information necessary for the student to do the work. Because dissertation statistics help offers this information and guidance, students are able to learn the material for themselves, with the help of dissertation statistics help. In other words, dissertation statistics help ensures that the student is actually learning—not just hiring someone to do the work. Therefore, dissertation statistics help can be an invaluable learning tool for students.
Additionally, dissertation statistics help can save the student much time and energy. There are many, many, many rules and regulations guiding statistics (it is, after all a science—and just like all science, it has rules, regulations, procedures, etc. that need to be followed). Dissertation statistics help can explain these rules and procedures and dissertation statistics help can make sure that students are traveling in the right direction. Improper statistics lead to inaccurate results and therefore dissertation statistics help will ensure that students who seek dissertation statistics help do not get improper results.
Dissertation statistics help will also create a timeline for students to follow. This timeline provided by dissertation statistics helps allows students to know exactly what needs to be done, when it needs to be done and how it needs to be done. Without this timeline provided by dissertation statistics help, students are often at a loss at how to proceed and where to even begin. The timeline provided by dissertation statistics help organizes students and helps them stay on-target and on-task.
Dissertation statistics help should be sought by the student and it should come from experts in the field. These experts, above all, must be trained in statistics. They must also have comprehensive knowledge of computers and the statistical programs that work on computers (SPSS, for example). Additionally, dissertation statistics help should be sought from people who are easily and readily available. Finally, dissertation statistics help should be acquired from people who know how to effectively communicate with students and their clients. Because proper communication is essential for any project to get done, people who offer dissertation statistics help should be good communicators. There is no question that dissertation statistics help is the most invaluable, essential and helpful tool available for all students needing to successfully complete their dissertations. Dissertation statistics help can make the difficult chore of completing the dissertation possible, and dissertation statistics consultants can allow students to complete this chore on-time. Finally, dissertation statistics consultants will not stop until their student earns his/her degree in the most successful way possible.
Monday, May 11, 2009
Friday, May 8, 2009
Statistics Consulting
Statistics consulting is a valuable tool for anyone in need of help with statistics. Statistics involves the very precise accumulation of data and the very precise interpretation of this data. Because statistics is a science, it can be very difficult to obtain accurate statistics without the help of statistics consulting. Statistics consulting, then, provides all of the information, guidance and assistance one would need to acquire accurate statistics.
Statistics consulting came about because not everyone who needs to use statistics is trained in the various methodologies of statistics. Statistics consulting helps individuals who are in this predicament.
Students looking to acquire their doctorate degree are often in need of statistics consulting. This is because, again, students are not always trained in statistics. And yet, these students need to use statistics in order to get accurate information from which to write a dissertation. Statistics consulting, however, can guide a student step-by-step through the process and procedures of statistics, as statistics consulting will provide valuable assistance to any student. Statistics consulting helps students break-down what needs to be done to get accurate statistics. The first thing that needs to be done, of course, is gathering data or information. This, however, is not easy as there are many rules and regulations surrounding the gathering of information. Statistics consulting explains these rules and statistics consulting can take the student through each and every step of the gathering of data and information. Once this data is gathered and acquired, statistics consulting helps students analyze and interpret the results. Here again, this is not easy. Students not trained in statistics often do not know how to accurately interpret the results, but statistics consulting provides all of the information necessary to accurately interpret the results. Finally, statistics consulting helps students to “put it all together.” In other words, statistics consulting helps students finalize their dissertations as statistics consulting ensures that all of the statistics acquired are not only accurate, but pertain to the actual topic of the dissertation.
Statistics consulting can also provide invaluable help to businesses. This is particularly true for very small businesses as statistics consulting can provide these small businesses with everything they need to be successful. This is true because oftentimes small businesses do not have the expertise, know-how or experience to get useful statistics. And useful statistics are invaluable in market research—which, of course is invaluable in knowing which products will work where, and at what price, etc. Statistics consulting, then, does all of this research for the business and statistics consulting provides all of the results necessary to help a small business. Small businesses can take the information received from statistics consulting and apply it to their business model. Without the help of statistics consulting, small businesses are often left struggling as they try their product on the market without proper market research, and only learn from experience (and much money lost) that their product will not work in that particular market. Statistics consulting can clearly save a business both time and money.
Because statistics consulting can be so helpful both to organizations and businesses, it is important to seek statistics consulting from experts in the field. Statistics consulting is widely available and a simple on-line search will yield many search results for statistics consulting. Not all statistics consulting firms are as good as others, however. Thus, before deciding upon a particular statistics consulting firm, it is important to do adequate research on that statistics consulting firm. Once that research is completed, and once a statistics consulting firm is hired to help, there is no-doubt that the people seeking that help will benefit greatly from statistics consulting.
Statistics consulting came about because not everyone who needs to use statistics is trained in the various methodologies of statistics. Statistics consulting helps individuals who are in this predicament.
Students looking to acquire their doctorate degree are often in need of statistics consulting. This is because, again, students are not always trained in statistics. And yet, these students need to use statistics in order to get accurate information from which to write a dissertation. Statistics consulting, however, can guide a student step-by-step through the process and procedures of statistics, as statistics consulting will provide valuable assistance to any student. Statistics consulting helps students break-down what needs to be done to get accurate statistics. The first thing that needs to be done, of course, is gathering data or information. This, however, is not easy as there are many rules and regulations surrounding the gathering of information. Statistics consulting explains these rules and statistics consulting can take the student through each and every step of the gathering of data and information. Once this data is gathered and acquired, statistics consulting helps students analyze and interpret the results. Here again, this is not easy. Students not trained in statistics often do not know how to accurately interpret the results, but statistics consulting provides all of the information necessary to accurately interpret the results. Finally, statistics consulting helps students to “put it all together.” In other words, statistics consulting helps students finalize their dissertations as statistics consulting ensures that all of the statistics acquired are not only accurate, but pertain to the actual topic of the dissertation.
Statistics consulting can also provide invaluable help to businesses. This is particularly true for very small businesses as statistics consulting can provide these small businesses with everything they need to be successful. This is true because oftentimes small businesses do not have the expertise, know-how or experience to get useful statistics. And useful statistics are invaluable in market research—which, of course is invaluable in knowing which products will work where, and at what price, etc. Statistics consulting, then, does all of this research for the business and statistics consulting provides all of the results necessary to help a small business. Small businesses can take the information received from statistics consulting and apply it to their business model. Without the help of statistics consulting, small businesses are often left struggling as they try their product on the market without proper market research, and only learn from experience (and much money lost) that their product will not work in that particular market. Statistics consulting can clearly save a business both time and money.
Because statistics consulting can be so helpful both to organizations and businesses, it is important to seek statistics consulting from experts in the field. Statistics consulting is widely available and a simple on-line search will yield many search results for statistics consulting. Not all statistics consulting firms are as good as others, however. Thus, before deciding upon a particular statistics consulting firm, it is important to do adequate research on that statistics consulting firm. Once that research is completed, and once a statistics consulting firm is hired to help, there is no-doubt that the people seeking that help will benefit greatly from statistics consulting.
Thursday, May 7, 2009
Autocorrelation
In cross sectional studies, data often involves households (in a consumption function analysis) or firms (in an investment study analysis), so if by chance an error term of a particular household or firm gets correlated with some other household or firm, then such correlations are termed as autocorrelation. Autocorrelation also occurs in the case of time series data. In the case of time series data, if the observations exhibit intercorrelations, especially when the time interval between the successive observations are short, then those intercorrelations are nothing but autocorrelation.
So, the term autocorrelation is defined as the correlation between the members of the series of the observations that are ordered with respect to time. Let us discuss two cases based on cross sectional and time series data to explain autocorrelation in a much better manner. In the case of cross sectional data, if a change in the income of a particular person affects the consumption expenditure of another household (other than his), then autocorrelation is present in the data. In the case of time series data, if an output is low in one quarter due to a labor strike, and if the data shows low output continues in the next quarter as well, then autocorrelation is present in the data.
Autocorrelation can be defined as the lag correlation of a given series with itself, lagged by a number of time units. On the other hand, serial autocorrelation defines the lag correlation between the two series in time series data.
There are certain patterns of autocorrelation, thus autocorrelation comes with various patterns. One example would be showing a discernible pattern among the residual errors. Autocorrelation exists when the residual error shows a cyclical pattern or an upward or downward trend in the disturbances, etc.
One of the major reasons for autocorrelation is the inertia or sluggishness caused in the time series data. The usage of an incorrect functional form also becomes a reason for an autocorrelation to occur.
The manipulation involving the extrapolation and the interpolation in the data also becomes a reason for autocorrelation. In this, the time series data is averaged so that smoothness occurs in the data, and this smoothness in the data exhibits a systematic pattern which in turn, introduces autocorrelation in the data.
A non stationarity property in the time series data also gives rise to the phenomenon of autocorrelation. Therefore, in order to make the time series free of autocorrelation, the researcher should make the data stationary.
Researchers should know that autocorrelation can be positive as well as negative. Economic time series generally exhibits positive autocorrelation as the series move in an upward or downward pattern. If the series move in a constant upward and downward movement, then autocorrelation is negative.
The major consequence of using ordinary least square (OLS) in the presence of autocorrelation is that it simply makes the estimator inefficient. As a result, the hypothesis testing procedures will give inaccurate results due to the presence of autocorrelation.
There is a popular test called the Durbin Watson test that detects the presence of autocorrelation. This test is conducted under the null hypothesis that there is no autocorrelation in the data. A test statistic called‘d’ is computed. “d” is defined as the ratio between the sum of the square of the difference in the residuals with ith and (i-1) time and the square of the residual in ith time. If the upper critical value of the test comes out to be less than the value of ‘d,’ then there is no autocorrelation. If the lower critical value of the test is more than the value of ‘d’ then there is autocorrelation.If one detects autocorrelation in the data, then the first thing a researcher should do is to try to find whether or not the autocorrelation is pure. If it is pure autocorrelation, then one can transform it into the original model, which is free from pure autocorrelation.
So, the term autocorrelation is defined as the correlation between the members of the series of the observations that are ordered with respect to time. Let us discuss two cases based on cross sectional and time series data to explain autocorrelation in a much better manner. In the case of cross sectional data, if a change in the income of a particular person affects the consumption expenditure of another household (other than his), then autocorrelation is present in the data. In the case of time series data, if an output is low in one quarter due to a labor strike, and if the data shows low output continues in the next quarter as well, then autocorrelation is present in the data.
Autocorrelation can be defined as the lag correlation of a given series with itself, lagged by a number of time units. On the other hand, serial autocorrelation defines the lag correlation between the two series in time series data.
There are certain patterns of autocorrelation, thus autocorrelation comes with various patterns. One example would be showing a discernible pattern among the residual errors. Autocorrelation exists when the residual error shows a cyclical pattern or an upward or downward trend in the disturbances, etc.
One of the major reasons for autocorrelation is the inertia or sluggishness caused in the time series data. The usage of an incorrect functional form also becomes a reason for an autocorrelation to occur.
The manipulation involving the extrapolation and the interpolation in the data also becomes a reason for autocorrelation. In this, the time series data is averaged so that smoothness occurs in the data, and this smoothness in the data exhibits a systematic pattern which in turn, introduces autocorrelation in the data.
A non stationarity property in the time series data also gives rise to the phenomenon of autocorrelation. Therefore, in order to make the time series free of autocorrelation, the researcher should make the data stationary.
Researchers should know that autocorrelation can be positive as well as negative. Economic time series generally exhibits positive autocorrelation as the series move in an upward or downward pattern. If the series move in a constant upward and downward movement, then autocorrelation is negative.
The major consequence of using ordinary least square (OLS) in the presence of autocorrelation is that it simply makes the estimator inefficient. As a result, the hypothesis testing procedures will give inaccurate results due to the presence of autocorrelation.
There is a popular test called the Durbin Watson test that detects the presence of autocorrelation. This test is conducted under the null hypothesis that there is no autocorrelation in the data. A test statistic called‘d’ is computed. “d” is defined as the ratio between the sum of the square of the difference in the residuals with ith and (i-1) time and the square of the residual in ith time. If the upper critical value of the test comes out to be less than the value of ‘d,’ then there is no autocorrelation. If the lower critical value of the test is more than the value of ‘d’ then there is autocorrelation.If one detects autocorrelation in the data, then the first thing a researcher should do is to try to find whether or not the autocorrelation is pure. If it is pure autocorrelation, then one can transform it into the original model, which is free from pure autocorrelation.
Wednesday, May 6, 2009
Time Series Analysis
Time series analysis is that type of analysis that deals with time series data. The time series data in time series analysis usually involves price data of certain commodities, or stock exchanges, like the Bombay Stock Exchange (BSE) and the New York Stock Exchange (NYSE).
There are many concepts used in time series analysis. One such process is a random process or a stochastic process in time series analysis. This is a collection of random variables that are ordered with respect to the time. For example, if Y is a random variable, in the case of continuous nature, it will be denoted as Y(t), and in the case of its discreet nature, it will be denoted as Yt in time series analysis.
In time series analysis, it is very important for the analyst to know that before conducting time series analysis, the stochastic process should be made stationary. A stationary process in time series analysis is said to be stationary only if the mean and variance is constant over the time, and if the value of the covariance between the two time periods mainly depends upon the distance between the two time periods. It is important for the analyst to know the reason behind stationary stochastic process in time series analysis. The reason is that it is not practically possible to compute mean and variance for every time period in time series analysis. If the time series is not stationary, then it will give the value of mean and variance for that particular time series.
A stochastic process in time series analysis is said to be purely random only if it has the mean as zero and the variance as constant. Additionally, it must be serially uncorrelated.
Differencing is one of the methods in time series analysis that helps in making the volatile time series into a stationary one. There are different orders of differencing in time series analysis. Suppose, for example, that the volatility is not reduced from the data after first order differencing. In this case, the analyst can make a second order differencing, in order to achieve stationarity in data in time series analysis.
In time series analysis, the exponential smoothing method predicts the next period value on the basis of the past value and the current value. In time series analysis, this method is used to make short term predictions about the commodities or the stock exchanges. Alpha, Gamma, Phi, and Delta are the parameters that are used to estimate the effect of the time series data in time series analysis. In time series analysis, alpha is used when seasonality is not present in the data. In time series analysis, Gamma is used when the series exhibits certain trends in the data. Delta is used in time series analysis when seasonality cycles are present in data. In time series analysis, the various models are applied according to the exhibition of the pattern in the data.
The major goal of time series analysis is to fit the data to the appropriate model under consideration.
There are certain assumptions made in time series analysis. These assumptions are as follows:
In time series analysis, the first assumption is that the series should be stationary. In other words, it means that in time series analysis, the series are normally distributed and the mean and variance is constant over that period of time.
In time series analysis, it is assumed that the error term is randomly distributed and the mean and the variance are constant over a time period. The errors in time series analysis are assumed to be uncorrelated to each other.
In time series analysis, it is assumed that no outlier is present in the series. The presence of outliers affects the inference of the data in time series analysis and thus leads to inaccurate results. If shocks are present in the time series analysis, they are assumed to be randomly distributed with a mean zero and a constant variance.
There are many concepts used in time series analysis. One such process is a random process or a stochastic process in time series analysis. This is a collection of random variables that are ordered with respect to the time. For example, if Y is a random variable, in the case of continuous nature, it will be denoted as Y(t), and in the case of its discreet nature, it will be denoted as Yt in time series analysis.
In time series analysis, it is very important for the analyst to know that before conducting time series analysis, the stochastic process should be made stationary. A stationary process in time series analysis is said to be stationary only if the mean and variance is constant over the time, and if the value of the covariance between the two time periods mainly depends upon the distance between the two time periods. It is important for the analyst to know the reason behind stationary stochastic process in time series analysis. The reason is that it is not practically possible to compute mean and variance for every time period in time series analysis. If the time series is not stationary, then it will give the value of mean and variance for that particular time series.
A stochastic process in time series analysis is said to be purely random only if it has the mean as zero and the variance as constant. Additionally, it must be serially uncorrelated.
Differencing is one of the methods in time series analysis that helps in making the volatile time series into a stationary one. There are different orders of differencing in time series analysis. Suppose, for example, that the volatility is not reduced from the data after first order differencing. In this case, the analyst can make a second order differencing, in order to achieve stationarity in data in time series analysis.
In time series analysis, the exponential smoothing method predicts the next period value on the basis of the past value and the current value. In time series analysis, this method is used to make short term predictions about the commodities or the stock exchanges. Alpha, Gamma, Phi, and Delta are the parameters that are used to estimate the effect of the time series data in time series analysis. In time series analysis, alpha is used when seasonality is not present in the data. In time series analysis, Gamma is used when the series exhibits certain trends in the data. Delta is used in time series analysis when seasonality cycles are present in data. In time series analysis, the various models are applied according to the exhibition of the pattern in the data.
The major goal of time series analysis is to fit the data to the appropriate model under consideration.
There are certain assumptions made in time series analysis. These assumptions are as follows:
In time series analysis, the first assumption is that the series should be stationary. In other words, it means that in time series analysis, the series are normally distributed and the mean and variance is constant over that period of time.
In time series analysis, it is assumed that the error term is randomly distributed and the mean and the variance are constant over a time period. The errors in time series analysis are assumed to be uncorrelated to each other.
In time series analysis, it is assumed that no outlier is present in the series. The presence of outliers affects the inference of the data in time series analysis and thus leads to inaccurate results. If shocks are present in the time series analysis, they are assumed to be randomly distributed with a mean zero and a constant variance.
Chi Square Test
The idea behind the parametric tests that involve parameters is to test the statistical significance of the observations under study. Chi square test is one of the parametric tests.
Chi square test involves different types of chi square tests, like chi square test for cross tabulation, chi square test for goodness of fit, likelihood ratio chi square test, etc.
The statistic in chi square test is used to test the statistical significance of the observed relationship in the cross tabulation of two variables. The statistic used in chi square test helps the researcher to determine whether or not an appropriate relationship exists between the two variables.
The null hypothesis assumed in chi square test assumes that there exists absolutely no correlation between the two variables being observed under the study. The chi square test is conducted by computing the cell frequencies which consist of the expected frequencies, if there is no correlation between the variables. The expected frequency in chi square test is then compared to the actual observed frequencies found in cross tabulation to calculate the chi square statistic in chi square test. The expected frequency in chi square test is calculated as the product of the total number of observations in the row and the column divided by the total size of the sample. The chi square statistic in chi square test is then calculated as the sum of the square of the deviation between the observed and the expected frequency, which is divided by the expected frequency.
The researcher should know that the greater the difference between the observed and expected cell frequency, the larger the value of the chi square statistic in chi square test.
In order to determine the association between the two variables, the probability of obtaining a value of chi square should be larger than the one obtained from chi square test of cross tabulation.
There is one more popular test called the chi square test for goodness of fit. This type of chi square test, called the chi square test for goodness of fit, helps the researcher to understand whether or not the sample drawn from a certain population has a specific distribution that actually belongs to that specified distribution. This type of chi square test can be applicable to only discrete types of distributions, like poisson, binomial, etc. This type of chi square test is an alternative test for the non parametric test and it is called the Kolmogorov Smrinov goodness of fit test.
The null hypothesis assumed by the researcher in this type of chi square test is that the data drawn from the population follows the specified distribution. The chi square statistic in this chi square test is defined in a similar manner as defined in the above type of test. One of the important points to be noted by the researcher is that the expected number of frequencies in this type of chi square test should be at least five. This means that the chi square test will not be valid for those whose expected cell frequency is less than five.
As discussed in the above chi square test, the probability of obtaining a value of chi square should be larger than the one obtained from chi square test for goodness of fit.
There are certain assumptions in a chi square test. The assumptions are as follows:
- In a chi square test, random sampling of the data is assumed.
- In a chi square test, a sample with a sufficiently large size is assumed. If a chi square test is conducted on a sample with a smaller size, then the chi square test will yield an inaccurate inference. The researcher, by using chi square test on small samples, might end up committing a Type II error.
- In a chi square test, the observations are always assumed to be independent of each other.
- In a chi square test, the observations must have the same fundamental distribution.
Tuesday, May 5, 2009
APA Bibliography
APA citation is a method of formatting a scientific paper or dissertation. APA stands for the American Psychological Association, and there are APA rules and guidelines that govern every single aspect of the dissertation. Oftentimes, APA citation can be divided into two separate parts: APA citation within the text and APA citation after the text. The APA citation after the text refers, essentially, to the APA bibliography. The APA bibliography must adhere to very precise rules and regulations in order to be acceptable. In other words, the APA bibliography must be formatted correctly, using proper APA bibliography standards if the dissertation is to be accepted.
The purpose of the APA bibliography is to document all of the sources that a student uses throughout his or her dissertation. Thus, the APA bibliography provides all of the information on the outside information that a student cites within his or her dissertation. (APA rules also govern how those citations are formatted within the text, as well as governing the rules of the APA bibliography.) Because dissertations must be checked in order to assess their validity, it is important to carefully document all sources used within the dissertation and within the APA bibliography. A well written and properly formatted APA bibliography will allow advisors, professors and those parties who authorize the dissertation to check all of the sources that the student has listed in the APA bibliography. Further, a standard method of formatting for the APA bibliography page saves valuable time for these people who want to double check all the sources.
The APA bibliography, therefore, lists all of the sources used in the dissertation. Examples of sources that can be found in the dissertation and in the APA bibliography include journal articles, books, web documents on university web-sites, stand alone web documents, journal articles from databases, abstracts from secondary databases, articles in edited books, etc. Because the list of possible sources is extensive, it is important to make sure that much time is spent researching what, exactly, needs to be written in the APA bibliography. In other words, because there are so many different kinds of sources that one can use and document in the APA bibliography, it is important to get accurate and precise information regarding what rules govern the APA bibliography.
While the rules of APA citation and the APA bibliography are not necessarily hard to follow, it is time consuming to look up all of these rules and regulations regarding APA citation and the APA bibliography. Additionally, many students wait until the last minute to format their paper and their APA bibliography. They wait until the last minute because students do not realize how long it can take to transform everything (including the APA bibliography) into proper APA format. Add to this the pressure and stress that a student feels at the end of his or her dissertation, and this is a certain recipe for disaster. The disaster occurs when students rush through APA citation and take shortcuts on their APA bibliography. A dissertation cannot be approved, however, unless the document itself and the APA bibliography are formatted correctly. And while a student may think that his or her APA formatting within the text and his or her APA bibliography are “close enough,” the dissertation advisors and the dissertation acceptance committees are very well informed on proper APA citation. Thus, a student will not have their dissertation accepted or approved if it is not in proper APA format.
Students struggling with APA format and the APA bibliography should look for help. Oftentimes their advisors are too busy to worry about APA format and the APA bibliography. APA formatting help is available, however, and students should turn to consultants who have extensive expertise in APA formatting and the APA bibliography.
The purpose of the APA bibliography is to document all of the sources that a student uses throughout his or her dissertation. Thus, the APA bibliography provides all of the information on the outside information that a student cites within his or her dissertation. (APA rules also govern how those citations are formatted within the text, as well as governing the rules of the APA bibliography.) Because dissertations must be checked in order to assess their validity, it is important to carefully document all sources used within the dissertation and within the APA bibliography. A well written and properly formatted APA bibliography will allow advisors, professors and those parties who authorize the dissertation to check all of the sources that the student has listed in the APA bibliography. Further, a standard method of formatting for the APA bibliography page saves valuable time for these people who want to double check all the sources.
The APA bibliography, therefore, lists all of the sources used in the dissertation. Examples of sources that can be found in the dissertation and in the APA bibliography include journal articles, books, web documents on university web-sites, stand alone web documents, journal articles from databases, abstracts from secondary databases, articles in edited books, etc. Because the list of possible sources is extensive, it is important to make sure that much time is spent researching what, exactly, needs to be written in the APA bibliography. In other words, because there are so many different kinds of sources that one can use and document in the APA bibliography, it is important to get accurate and precise information regarding what rules govern the APA bibliography.
While the rules of APA citation and the APA bibliography are not necessarily hard to follow, it is time consuming to look up all of these rules and regulations regarding APA citation and the APA bibliography. Additionally, many students wait until the last minute to format their paper and their APA bibliography. They wait until the last minute because students do not realize how long it can take to transform everything (including the APA bibliography) into proper APA format. Add to this the pressure and stress that a student feels at the end of his or her dissertation, and this is a certain recipe for disaster. The disaster occurs when students rush through APA citation and take shortcuts on their APA bibliography. A dissertation cannot be approved, however, unless the document itself and the APA bibliography are formatted correctly. And while a student may think that his or her APA formatting within the text and his or her APA bibliography are “close enough,” the dissertation advisors and the dissertation acceptance committees are very well informed on proper APA citation. Thus, a student will not have their dissertation accepted or approved if it is not in proper APA format.
Students struggling with APA format and the APA bibliography should look for help. Oftentimes their advisors are too busy to worry about APA format and the APA bibliography. APA formatting help is available, however, and students should turn to consultants who have extensive expertise in APA formatting and the APA bibliography.
Monday, May 4, 2009
Analysis of covariance (ANCOVA)
Analysis of covariance (ANCOVA) is used in examining the differences in the mean values of the dependent variables that are related to the effect of the controlled independent variables while taking into account the influence of the uncontrolled independent variables.
The Analysis of covariance (ANCOVA) is used in the field of business. This document will detail the usability of Analysis of covariance (ANCOVA) in market research.
Analysis of covariance (ANCOVA) can be used to determine the variation in the intention of the consumer to buy a particular brand with respect to different levels of price and the consumer’s attitude towards that brand.
Analysis of covariance (ANCOVA) can be used to determine how a change in the price level of a particular commodity will affect the consumption of that commodity by the consumers.
Analysis of covariance (ANCOVA) consists of at least one categorical independent variable and at least one interval natured independent variable. In Analysis of covariance (ANCOVA), the categorical independent variable is termed as a factor, whereas the interval natured independent variable is termed as a covariate. The task of the covariate in Analysis of covariance (ANCOVA) is to remove the extraneous variation from the dependent variable. This is done because the effects of the factors are of major concern in Analysis of covariance (ANCOVA).
Analysis of covariance (ANCOVA) is most useful in those cases where the covariate is linearly related to the dependent variables and is not related to the factors.
Similar to Analysis of variance (ANOVA), Analysis of covariance (ANCOVA) also assumes similar assumptions. The following are the assumptions of Analysis of Covariance (ANCOVA):
The variance in Analysis of covariance (ANCOVA) that is being analyzed must be independent.
In the case of more than one independent variable, the variance in Analysis of covariance (ANCOVA) must be homogeneous in nature within each cell that is formed by the categorical independent variables.
The data should be drawn from the population by means of random sampling in Analysis of covariance (ANCOVA). Analysis of covariance (ANCOVA) assumes that the adjusted treatment means those that are being computed or estimated are based on the fact that the variables obtained due to the interaction of covariate are negligible.
The Analysis of covariance (ANCOVA) is done by using linear regression. This means that Analysis of covariance (ANCOVA) assumes that the relationship between the independent variable and the dependent variable must be linear in nature.
In Analysis of covariance (ANCOVA), the different types of the independent variables are assumed to be drawn from the normal population having a mean of zero.
The Analysis of covariance (ANCOVA) assumes that the regression coefficients in every group of the independent variable must be homogeneous in nature.
Analysis of covariance (ANCOVA) is applied when an independent variable has a powerful correlation with the dependent variable. But, it is important to remember that the independent variables in Analysis of covariance (ANCOVA) do not interact with other independent variables while predicting the value of the dependent variable. Analysis of covariance (ANCOVA) is generally applied to balance the effect of comparatively more powerful non interacting variables. It is necessary to balance the effect of interaction in Analysis of covariance (ANCOVA) in order to avoid uncertainty among the independent variables.
Analysis of covariance (ANCOVA) is applied only in those cases where the balanced independent variable is measured on a continuous scale.
Let us assume a researcher wants to determine the effect of an in-store promotion on sales revenue. In this case, Analysis of covariance (ANCOVA) is an appropriate technique because the change in the attitude of the consumer towards the store will automatically affect the sales revenue of the store in Analysis of covariance (ANCOVA). Therefore, in Analysis of covariance (ANCOVA), the dependent variable will be the sales revenue of the store. And the independent variable will be the attitude of the consumer in Analysis of covariance (ANCOVA).
The Analysis of covariance (ANCOVA) is used in the field of business. This document will detail the usability of Analysis of covariance (ANCOVA) in market research.
Analysis of covariance (ANCOVA) can be used to determine the variation in the intention of the consumer to buy a particular brand with respect to different levels of price and the consumer’s attitude towards that brand.
Analysis of covariance (ANCOVA) can be used to determine how a change in the price level of a particular commodity will affect the consumption of that commodity by the consumers.
Analysis of covariance (ANCOVA) consists of at least one categorical independent variable and at least one interval natured independent variable. In Analysis of covariance (ANCOVA), the categorical independent variable is termed as a factor, whereas the interval natured independent variable is termed as a covariate. The task of the covariate in Analysis of covariance (ANCOVA) is to remove the extraneous variation from the dependent variable. This is done because the effects of the factors are of major concern in Analysis of covariance (ANCOVA).
Analysis of covariance (ANCOVA) is most useful in those cases where the covariate is linearly related to the dependent variables and is not related to the factors.
Similar to Analysis of variance (ANOVA), Analysis of covariance (ANCOVA) also assumes similar assumptions. The following are the assumptions of Analysis of Covariance (ANCOVA):
The variance in Analysis of covariance (ANCOVA) that is being analyzed must be independent.
In the case of more than one independent variable, the variance in Analysis of covariance (ANCOVA) must be homogeneous in nature within each cell that is formed by the categorical independent variables.
The data should be drawn from the population by means of random sampling in Analysis of covariance (ANCOVA). Analysis of covariance (ANCOVA) assumes that the adjusted treatment means those that are being computed or estimated are based on the fact that the variables obtained due to the interaction of covariate are negligible.
The Analysis of covariance (ANCOVA) is done by using linear regression. This means that Analysis of covariance (ANCOVA) assumes that the relationship between the independent variable and the dependent variable must be linear in nature.
In Analysis of covariance (ANCOVA), the different types of the independent variables are assumed to be drawn from the normal population having a mean of zero.
The Analysis of covariance (ANCOVA) assumes that the regression coefficients in every group of the independent variable must be homogeneous in nature.
Analysis of covariance (ANCOVA) is applied when an independent variable has a powerful correlation with the dependent variable. But, it is important to remember that the independent variables in Analysis of covariance (ANCOVA) do not interact with other independent variables while predicting the value of the dependent variable. Analysis of covariance (ANCOVA) is generally applied to balance the effect of comparatively more powerful non interacting variables. It is necessary to balance the effect of interaction in Analysis of covariance (ANCOVA) in order to avoid uncertainty among the independent variables.
Analysis of covariance (ANCOVA) is applied only in those cases where the balanced independent variable is measured on a continuous scale.
Let us assume a researcher wants to determine the effect of an in-store promotion on sales revenue. In this case, Analysis of covariance (ANCOVA) is an appropriate technique because the change in the attitude of the consumer towards the store will automatically affect the sales revenue of the store in Analysis of covariance (ANCOVA). Therefore, in Analysis of covariance (ANCOVA), the dependent variable will be the sales revenue of the store. And the independent variable will be the attitude of the consumer in Analysis of covariance (ANCOVA).
Wednesday, April 29, 2009
APA Citation
The letters APA in APA citation stand for the American Psychological Association. Thus, APA citation is a method of documenting sources and formatting academic papers in concurrence with the standards of the American Psychological Association. This citing and formatting is known as APA citation. There are many different styles of citations, and these include MLA, AMA, etc.. APA citation, however, is one of the most popular as APA citation is used in most academia. APA citation is essential to an academic paper and therefore, APA citation plays an important role in a dissertation or academic paper.
APA citation has a purpose, and the purpose of APA citation is so others can look up and access all resources cited in a paper. Thus, proper APA citation will allow all information, data and research to be checked and verified. This is most definitely an important feature of dissertations as proper APA citation allows for a dissertation to be pronounced as valid.
Many students struggle with APA citation because many students are not familiar with APA citation. Further, APA citation can seem unimportant as the student and writer of the dissertation is more concerned with the larger aspect of the dissertation, like the research and analysis involved in the dissertation. Thus, APA citation can seem minor in comparison to the larger point the student is making. And yet, the dissertation will not be accepted if it does not have proper APA citation. In other words, proper APA citation can be an annoying task, but proper APA citation is absolutely necessary.
APA citation has two major parts. These two parts of APA citation are in-text citations and the reference list for APA citation. The in-text citations for APA citation occur within the document. In other words, there is a proper way to apply APA citation to text within the document. The second part of APA citation occurs at the end of the document, in the reference list or bibliography part of the paper. There is a very specific way to cite everything in the reference list if the dissertation is to follow proper APA citation.
APA citation also follows many formatting guidelines, most of which are unique to APA citation. Thus, APA citation includes formatting for every aspect of the dissertation. In other words, there is APA citation for the title page, APA citation for the page numbers, APA citation for the running head of a dissertation, APA citation for the abstract, APA citation for the visuals, APA citation for headings, and, as previously mentioned, APA citation for the reference list. Clearly then, APA citation will happen on every single page of the dissertation, be it to properly cite sources, data and research or to diagram charts and graphs.
Because many students are concerned with citation (as well they should be since APA citation plays a major part in the dissertation) APA citation help is available. APA citation help will dramatically cut-down on the time that a student needs to spend on his or her thesis. This is particularly important because often-times students do not know how APA citation works and they wait until the last minute to figure out how APA citation should fit into their dissertations. Thinking that using APA citation will be an easy concept to grasp, students do not plan enough time to fix and edit their paper so that it is has proper APA citation. In other words, many students finish their dissertations, but these “finished” dissertations are not finished at all because they are not in adequate APA citation. Thus, students are under much stress and pressure as they must quickly figure out how to put their paper into proper APA citation. APA citation, however, is not something that can be done so quickly! In fact, entire books have been written on proper APA citation—and because this is the case, many students are overwhelmed with the daunting task of changing, editing and reformatting their paper. APA citation help is available, however, and with the help of an expert in proper APA citation, the student will no-doubt truly finish their dissertation before the ever-looming deadline.
APA citation has a purpose, and the purpose of APA citation is so others can look up and access all resources cited in a paper. Thus, proper APA citation will allow all information, data and research to be checked and verified. This is most definitely an important feature of dissertations as proper APA citation allows for a dissertation to be pronounced as valid.
Many students struggle with APA citation because many students are not familiar with APA citation. Further, APA citation can seem unimportant as the student and writer of the dissertation is more concerned with the larger aspect of the dissertation, like the research and analysis involved in the dissertation. Thus, APA citation can seem minor in comparison to the larger point the student is making. And yet, the dissertation will not be accepted if it does not have proper APA citation. In other words, proper APA citation can be an annoying task, but proper APA citation is absolutely necessary.
APA citation has two major parts. These two parts of APA citation are in-text citations and the reference list for APA citation. The in-text citations for APA citation occur within the document. In other words, there is a proper way to apply APA citation to text within the document. The second part of APA citation occurs at the end of the document, in the reference list or bibliography part of the paper. There is a very specific way to cite everything in the reference list if the dissertation is to follow proper APA citation.
APA citation also follows many formatting guidelines, most of which are unique to APA citation. Thus, APA citation includes formatting for every aspect of the dissertation. In other words, there is APA citation for the title page, APA citation for the page numbers, APA citation for the running head of a dissertation, APA citation for the abstract, APA citation for the visuals, APA citation for headings, and, as previously mentioned, APA citation for the reference list. Clearly then, APA citation will happen on every single page of the dissertation, be it to properly cite sources, data and research or to diagram charts and graphs.
Because many students are concerned with citation (as well they should be since APA citation plays a major part in the dissertation) APA citation help is available. APA citation help will dramatically cut-down on the time that a student needs to spend on his or her thesis. This is particularly important because often-times students do not know how APA citation works and they wait until the last minute to figure out how APA citation should fit into their dissertations. Thinking that using APA citation will be an easy concept to grasp, students do not plan enough time to fix and edit their paper so that it is has proper APA citation. In other words, many students finish their dissertations, but these “finished” dissertations are not finished at all because they are not in adequate APA citation. Thus, students are under much stress and pressure as they must quickly figure out how to put their paper into proper APA citation. APA citation, however, is not something that can be done so quickly! In fact, entire books have been written on proper APA citation—and because this is the case, many students are overwhelmed with the daunting task of changing, editing and reformatting their paper. APA citation help is available, however, and with the help of an expert in proper APA citation, the student will no-doubt truly finish their dissertation before the ever-looming deadline.
Tuesday, April 28, 2009
Statistics Consulting
Seeking the help of statistics consulting is one of the best decisions an individual or organization can make. Statistics consulting provides help on all things concerning statistics. Statistics consulting can both attain the necessary data needed and statistics consulting can then explain the results. Statistics consulting can then give these results to the organization or individual and with the information acquired from statistics consulting and statistics consulting firms, the individual or organization can make much needed decisions.
First, let’s look at how individuals can use statistics consulting and statistics consulting firms. Most often individuals get statistics consulting help and contact statistics consulting firms when they need help with a large project that involves statistics. This is most often the case for doctoral students who need to write their dissertations. Dissertations, however, require mass amounts of time. Statistics consulting and statistics consulting firms can help these time-strapped students. In fact, if a student seeks statistics consulting from a statistics consulting firm, the student is guaranteed to save both time and energy. This is true because statistics consulting can help from the very beginning of the project and statistics consulting firms will see this project through until it is completed.
Thus, statistics consulting is essential as statistics consulting firms ‘jump in’ at the very beginning of a project. The beginning of the project is the actual choosing of the topic. Many students do not even know where to start when it comes to their dissertations, and this is where statistics consulting provided by statistics consulting firms can begin. Statistics consulting provided by statistics consulting firms will help the student narrow-down the options of their topic. Statistics consulting provided by statistics consulting firms gives valuable feedback to students because they are trained and experienced. Statistics consulting provided by statistics consulting firms is especially helpful for first-time dissertation writers as these students often struggle most. Not only have these ‘first-timers’ never written a dissertation before, they are often-times overwhelmed by the magnitude and scope of the project. Statistics consulting provided by statistics consulting firms, however, are not intimidated as statistics consultants have expertise in the subject and are prepared to help.
Once the topic for the project is decided, statistics consulting provides a timeline for the students. This timeline provided by statistics consulting gives students much-needed targets. Thus, statistics consulting helps organize students and statistics consulting provides step-by-step instruction on what needs to be done and in what order.
Statistics consulting then helps the student with every single aspect of his/her project. This includes gathering the data, analyzing the data and applying all the necessary principles, assumptions and rules to the data gathering and analyzing. This is especially hard for students as students are not always trained in statistics. Statistics consulting provided by statistics consulting firms, however, provides all of the information, guidance and assistance necessary as they carry-out and explain all of the statistics procedures. Statistics consulting, for example, explains how research needs to be gathered—be it by questionnaire, on-line survey, telephone interview, etc. Statistics consulting then explains how a student needs to interpret the results of the data they collect. Statistics consulting explains, for example, the assumptions, rules and tests of statistics (for example, ANOVA, ANCOVA, MANOVA, etc). In other words statistics consulting provided by statistics consulting firms will go through every single aspect of acquiring, organizing and processing the data that the student collects and statistics consulting firms will ensure that the dissertation is complete.
Students, however, are not the only people that can benefit greatly from statistics consulting provided by statistics consulting firms. Statistics consulting firms can also help organizations and businesses as it can deliver information about how to maximize profits. Additionally, statistics consulting provided by statistics consulting firms can help in fields such as psychology, medicine, nursing and government. This is true because all of these fields require statistics.
Acquiring statistics consulting is easy as there is much statistics consulting available through statistics consulting firms. Statistics consulting is also very affordable as statistics consulting saves time and energy, which in turn saves money. Statistics consulting provided by statistics consulting firms is well worth the cost as statistics consulting provides valid and accurate results in all fields requiring statistics. Statistics consulting will no doubt ensure success for both the individual and the organization.
First, let’s look at how individuals can use statistics consulting and statistics consulting firms. Most often individuals get statistics consulting help and contact statistics consulting firms when they need help with a large project that involves statistics. This is most often the case for doctoral students who need to write their dissertations. Dissertations, however, require mass amounts of time. Statistics consulting and statistics consulting firms can help these time-strapped students. In fact, if a student seeks statistics consulting from a statistics consulting firm, the student is guaranteed to save both time and energy. This is true because statistics consulting can help from the very beginning of the project and statistics consulting firms will see this project through until it is completed.
Thus, statistics consulting is essential as statistics consulting firms ‘jump in’ at the very beginning of a project. The beginning of the project is the actual choosing of the topic. Many students do not even know where to start when it comes to their dissertations, and this is where statistics consulting provided by statistics consulting firms can begin. Statistics consulting provided by statistics consulting firms will help the student narrow-down the options of their topic. Statistics consulting provided by statistics consulting firms gives valuable feedback to students because they are trained and experienced. Statistics consulting provided by statistics consulting firms is especially helpful for first-time dissertation writers as these students often struggle most. Not only have these ‘first-timers’ never written a dissertation before, they are often-times overwhelmed by the magnitude and scope of the project. Statistics consulting provided by statistics consulting firms, however, are not intimidated as statistics consultants have expertise in the subject and are prepared to help.
Once the topic for the project is decided, statistics consulting provides a timeline for the students. This timeline provided by statistics consulting gives students much-needed targets. Thus, statistics consulting helps organize students and statistics consulting provides step-by-step instruction on what needs to be done and in what order.
Statistics consulting then helps the student with every single aspect of his/her project. This includes gathering the data, analyzing the data and applying all the necessary principles, assumptions and rules to the data gathering and analyzing. This is especially hard for students as students are not always trained in statistics. Statistics consulting provided by statistics consulting firms, however, provides all of the information, guidance and assistance necessary as they carry-out and explain all of the statistics procedures. Statistics consulting, for example, explains how research needs to be gathered—be it by questionnaire, on-line survey, telephone interview, etc. Statistics consulting then explains how a student needs to interpret the results of the data they collect. Statistics consulting explains, for example, the assumptions, rules and tests of statistics (for example, ANOVA, ANCOVA, MANOVA, etc). In other words statistics consulting provided by statistics consulting firms will go through every single aspect of acquiring, organizing and processing the data that the student collects and statistics consulting firms will ensure that the dissertation is complete.
Students, however, are not the only people that can benefit greatly from statistics consulting provided by statistics consulting firms. Statistics consulting firms can also help organizations and businesses as it can deliver information about how to maximize profits. Additionally, statistics consulting provided by statistics consulting firms can help in fields such as psychology, medicine, nursing and government. This is true because all of these fields require statistics.
Acquiring statistics consulting is easy as there is much statistics consulting available through statistics consulting firms. Statistics consulting is also very affordable as statistics consulting saves time and energy, which in turn saves money. Statistics consulting provided by statistics consulting firms is well worth the cost as statistics consulting provides valid and accurate results in all fields requiring statistics. Statistics consulting will no doubt ensure success for both the individual and the organization.
Independent Sample T-Test
Independent sample t-test is a statistical technique that is used to analyze the mean comparison of two independent groups. In independent samples t-test, when we take two samples from the same population, then the mean of the two samples may be identical. But when samples are taken from two different populations, then the mean of the sample may differ. In this case, independent sample t-test is used to draw conclusions about the means of two populations, and used to tell whether or not they are similar.
Assumptions in independent samples t-test:
1. Independent sample t-test assumes that the dependent variable is normally distributed.
2. Independent sample t-test assumes that the variance of the two groups are the same as the dependent variable.
3. Independent sample t-test also assumes that the two samples are independent of each other.
4. Samples for independent sample t-test are drawn from the population at random.
5. In independent sample t-test, all observations must be independent of each other.
6. In independent sample t-test, dependent variables must be measured on an interval or ratio scale.
Procedures for independent sample t-test:
1. Set up the hypothesis for independent sample t-test.
a. Null Hypothesis: In independent sample t-test, null hypothesis is assumed when the means of the two groups are not significantly different.
b. Alternative Hypothesis: In independent sample t-test, Alternative hypothesis assumes that the means of the two groups are significantly different.
2. Calculate the standard deviation for the independent sample t-test by using this formula:
Independent sample t-test group statistics table: This table will show the total number in each group, the mean, the standard deviation and the standard error for the independent sample t-test.
Assumptions in independent samples t-test:
1. Independent sample t-test assumes that the dependent variable is normally distributed.
2. Independent sample t-test assumes that the variance of the two groups are the same as the dependent variable.
3. Independent sample t-test also assumes that the two samples are independent of each other.
4. Samples for independent sample t-test are drawn from the population at random.
5. In independent sample t-test, all observations must be independent of each other.
6. In independent sample t-test, dependent variables must be measured on an interval or ratio scale.
Procedures for independent sample t-test:
1. Set up the hypothesis for independent sample t-test.
a. Null Hypothesis: In independent sample t-test, null hypothesis is assumed when the means of the two groups are not significantly different.
b. Alternative Hypothesis: In independent sample t-test, Alternative hypothesis assumes that the means of the two groups are significantly different.
2. Calculate the standard deviation for the independent sample t-test by using this formula:
3. Calculate the value of the independent sample t-test by using this formula:
4. Degree of freedom for independent sample t-test:
Where
V= degree of freedom
N1+N2= number of observations in both samples of the independent sample t-test.
5. Hypothesis testing: In hypothesis testing for the independent sample t-test, statistical decisions are made about whether or not the two population means are identical. Compare the calculated value of the independent sample t-test with the table value of the sample t-test. If the calculated value of the independent sample t-test is greater than the table value of the predetermined significance level, we will reject the null hypothesis and say that the means of the two groups are different. If the calculated value of the independent sample t-test is less than the table value, then we will say that the means of the two groups are the same.
Independent sample t-test and SPSS: Most statistical software has the option to perform the independent sample t-test. In SPSS, to perform the independent sample t-test we have to perform following procedure:
V= degree of freedom
N1+N2= number of observations in both samples of the independent sample t-test.
5. Hypothesis testing: In hypothesis testing for the independent sample t-test, statistical decisions are made about whether or not the two population means are identical. Compare the calculated value of the independent sample t-test with the table value of the sample t-test. If the calculated value of the independent sample t-test is greater than the table value of the predetermined significance level, we will reject the null hypothesis and say that the means of the two groups are different. If the calculated value of the independent sample t-test is less than the table value, then we will say that the means of the two groups are the same.
Independent sample t-test and SPSS: Most statistical software has the option to perform the independent sample t-test. In SPSS, to perform the independent sample t-test we have to perform following procedure:
1. Click on the “SPSS 16” icon from the start menu.
2. Click on the “open data” icon and select the data for the independent sample t-test.
3. Click on the “analysis” option and select “compare mean” from the analysis option.
4. Select “independent sample t-test” from the compare mean option. As we click on the independent sample t-test, the following window will appear:
2. Click on the “open data” icon and select the data for the independent sample t-test.
3. Click on the “analysis” option and select “compare mean” from the analysis option.
4. Select “independent sample t-test” from the compare mean option. As we click on the independent sample t-test, the following window will appear:
Select the grouping variable and insert them into the grouping variable box. Define the group in the independent samples t-test. Select the dependent variable and insert them into the test variable list. Click on “option” and select “% confidence interval.” As we click on the “ok” button, the result window for the independent sample t-test will appear in front of us.
Independent sample t-test group statistics table: This table will show the total number in each group, the mean, the standard deviation and the standard error for the independent sample t-test.
Independent sample t-test statistics table: In this table, the first test will be Levene’s test, which is used to test the assumptions of equal variance between all the groups in the independent sample t-test. Significance value of F is used to make the statistical decision about the assumptions of equal variance. The second test statistics will show the calculated value of the independent sample t-test, the degree of freedom, and the significance value of the independent sample t-test. This significance value is used to make the statistical decision about the mean of the two groups. If the calculated value is less than the predetermined significance level, then we can say that the means are significantly different.
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