The normal curve tests of means and proportions refer to those tests that are basic methods of testing the possible differences between two samples. The normal curve tests of means and proportions can also be referred to as parametric tests under the assumption that the population follows a normal distribution. Normal curve tests of means and proportions are used when the size of the sample is more than 29.
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There are certain conceptual terms that are helpful to know to better understand the normal curve tests of means and proportions.
The deviation scores in normal curve tests of means and proportions are defined mathematically as the difference between the observed score and the mean for any particular variable. The deviation score in normal curve tests of means and proportions is generally zero, since half of the deviations are above the mean value and the other half are below the mean value.
The standard error in normal curve tests of means and proportions is used to estimate the variability of the sample means. Since there is only one sample in the normal curve tests of means and proportions, the estimated standard error can be computed by the ration between the standard deviation and the square root of the sample size.
The confidence limits in the normal curve tests of means and proportions set the upper and the lower bounds on an estimate for a given level of significance. In the normal curve tests of means and proportions, these limits are regarded by the researchers as they provide additional information about the estimates.
The normal curve tests of proportions in normal curve tests of means and proportions are used to test the difference in the proportions or the percentages rather than the means.
When two independent samples are tested by the researcher in the normal curve tests of means and proportions, then some different formulas are used, although the main aim remains the same. Thus, the comparison of the z values with the critical values in the table is done under the normal curve.
When the correlated two samples test is used by the researcher in the normal curve tests of means and proportions, then the two correlated samples are factored into the formulas for the two sample means and proportions test. The notations that are in these samples of the normal curve tests of means and proportions are similar to the previous samples with an addition of the Pearsonian correlation.
There are also certain assumptions in the normal curve tests of means and proportions.
The first assumption of the normal curve tests of means and proportions is that as the name suggests, the variable of interest should be normally distributed in the population.
The second assumption of the normal curve tests of means and proportions is that the data should be of interval scale.
The third assumption of the normal curve tests of means and proportions is that the size of the sample should not be small.
The fourth assumption of the normal curve tests of means and proportions is that there should be homogeneity within the variances. This assumption of the normal curve tests of means and proportions is used in two sample testing cases.
Monday, June 29, 2009
Friday, June 26, 2009
Reliability Analysis
In Reliability analysis, the word reliability refers to the fact that a scale should consistently reflect the construct it is measuring. There are certain times and situations where Reliability analysis can be useful.
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An aspect in which the researcher can think about Reliability analysis is when two observations under study that are equivalent to each other in terms of the construct being measured also have the equivalent outcome.
There is a popular technique of Reliability analysis called the split half reliability. This method of Reliability analysis splits the data into two parts. The score for each participant in the Reliability analysis is then computed on the basis of each half of the scale. In that type of Reliability analysis, if the scale is very reliable, then the value of the person’s score on one half of the scale would be equivalent to the score on the other half. In this type of Reliability analysis, the previous fact should remain true for all the participants.
The major problem with this type of Reliability analysis is that there are several ways in which a set of data can be divided into two parts, and therefore the outcome could be numerous.
In order to overcome this problem in this type of Reliability analysis, Cronbach (1951) introduced a measure that is a common measure in Reliability analysis. This measure of Reliability analysis is loosely equivalent to the splitting of the data in two halves in every possible manner and further computing the correlation coefficient for each split. The average of these values is similar to the value of Cronbach’s alpha in Reliability analysis.
There are basically two versions of alpha in Reliability analysis. The first version of alpha in Reliability analysis is the normal version. The second version of alpha in Reliability analysis is the standardized version.
The normal version of alpha in Reliability analysis is applicable when the items on a scale are summed to produce a single score for that scale. The standardized version of alpha in Reliability analysis is applicable when the items on a scale are standardized before they are summed up.
According to Kline (1999), the acceptable value of alpha in Reliability analysis is 0.8 in the case of intelligence tests, and the acceptable value of alpha in Reliability analysis is 0.7 in the case of ability tests.
There are certain assumptions that are assumed in Reliability analysis.
While conducting Reliability analysis in SPSS, the researcher should click on “Tukey’s test of additivity” as additivity is assumed in Reliability analysis.
In Reliability analysis, independence within the observations is assumed. However, it should be noted by the researcher that the test retest type of Reliability analysis involves the correlated data between the observations which do not pose a statistical problem in assessing the reliability in Reliability analysis.
In Reliability analysis, it is assumed that the errors are uncorrelated to each other. This means that in Reliability analysis, there exists no association among the errors and therefore all the errors in Reliability analysis are different.
In Reliability analysis, to attain reliability in the data, the coding done by the researcher should be consistent. This means that in Reliability analysis, the high values must be coded consistently, such that they have the same meaning across the items.
In the split half type of Reliability analysis, the random assignment of the subjects is assumed. Generally, in this type of Reliability analysis, the odd numbered items fall in one category and the even numbered items fall in the other.
Statistics Solutions is the country's leader in statistical data analysis and can assist with reliability analysis for your dissertation, thesis or research project. Contact Statistics Solutions today for a free 30-minute consultation.
An aspect in which the researcher can think about Reliability analysis is when two observations under study that are equivalent to each other in terms of the construct being measured also have the equivalent outcome.
There is a popular technique of Reliability analysis called the split half reliability. This method of Reliability analysis splits the data into two parts. The score for each participant in the Reliability analysis is then computed on the basis of each half of the scale. In that type of Reliability analysis, if the scale is very reliable, then the value of the person’s score on one half of the scale would be equivalent to the score on the other half. In this type of Reliability analysis, the previous fact should remain true for all the participants.
The major problem with this type of Reliability analysis is that there are several ways in which a set of data can be divided into two parts, and therefore the outcome could be numerous.
In order to overcome this problem in this type of Reliability analysis, Cronbach (1951) introduced a measure that is a common measure in Reliability analysis. This measure of Reliability analysis is loosely equivalent to the splitting of the data in two halves in every possible manner and further computing the correlation coefficient for each split. The average of these values is similar to the value of Cronbach’s alpha in Reliability analysis.
There are basically two versions of alpha in Reliability analysis. The first version of alpha in Reliability analysis is the normal version. The second version of alpha in Reliability analysis is the standardized version.
The normal version of alpha in Reliability analysis is applicable when the items on a scale are summed to produce a single score for that scale. The standardized version of alpha in Reliability analysis is applicable when the items on a scale are standardized before they are summed up.
According to Kline (1999), the acceptable value of alpha in Reliability analysis is 0.8 in the case of intelligence tests, and the acceptable value of alpha in Reliability analysis is 0.7 in the case of ability tests.
There are certain assumptions that are assumed in Reliability analysis.
While conducting Reliability analysis in SPSS, the researcher should click on “Tukey’s test of additivity” as additivity is assumed in Reliability analysis.
In Reliability analysis, independence within the observations is assumed. However, it should be noted by the researcher that the test retest type of Reliability analysis involves the correlated data between the observations which do not pose a statistical problem in assessing the reliability in Reliability analysis.
In Reliability analysis, it is assumed that the errors are uncorrelated to each other. This means that in Reliability analysis, there exists no association among the errors and therefore all the errors in Reliability analysis are different.
In Reliability analysis, to attain reliability in the data, the coding done by the researcher should be consistent. This means that in Reliability analysis, the high values must be coded consistently, such that they have the same meaning across the items.
In the split half type of Reliability analysis, the random assignment of the subjects is assumed. Generally, in this type of Reliability analysis, the odd numbered items fall in one category and the even numbered items fall in the other.
Monday, June 15, 2009
Dissertation Statistics Tutoring
Any student working on a dissertation can benefit from dissertation statistics help. Dissertation statistics help makes the process of writing a dissertation easy, manageable and understandable.
Statistics Solutions is the country's leader in dissertation statistics help. Contact Statistics Solutions today for a free 30-minute consultation.
Dissertation statistics help can provide invaluable help, guidance and assistance to anyone writing a dissertation.The dissertation is the hardest and most challenging part of any student’s academic career. For this reason, it is important to seek dissertation statistics help. Unfortunately, many students do not choose to seek dissertation statistics help until they have reached a ‘stopping point’ or a problem. And while dissertation statistics help can fix that problem, the student has already wasted valuable time as he or she did not seek dissertation statistics help sooner.
Dissertation statistics help provides help throughout the dissertation—from the very beginning, to the very end of the dissertation. Dissertation statistics help is provided by trained professionals who are well versed in all things regarding dissertations and statistics. Dissertation statistics help is also provided by people who have already received their doctoral degrees, and thus dissertation statistics help is provided by people who have gone through every single stress that the student has gone through. This can be important as it is important to be able to understand the needs of the student who is acquiring dissertation statistics help.
Dissertations rely heavily on statistics and unfortunately many students do not know enough about statistics to be successful in their research and design for their project. Here again dissertation statistics help can assist the student. Dissertation statistics help will step in at the very beginning of the project and will help the student design that project properly. Dissertation statistics help will go over every single thing that needs to be done and dissertation statistics help will make sure that the student has the proper tools to complete the project. There will be no “wrong turns’ with dissertation statistics help, as dissertation statistics help will be there assisting the student every single step of the way.
One of the most important advantages of obtaining dissertation statistics help is the availability and accessibility of dissertation statistics help. While all students have advisors, these advisors are not always available. What’s more, most time these advisors tell students what is wrong AFTER the student has already made the mistake. Thus, the student must go back and continually redo aspects of his or her dissertation. Because dissertation statistics help is always available, however, the student will not make costly mistakes because he or she has someone looking over his/her shoulder and ensuring that he or she does not make any mistakes. Thus, much time will be saved simply by having dissertation statistics help.
Dissertation statistics help is well worth any cost associated with it. In fact, if a student is debating whether or not to use dissertation statistics help, a simple phone call can clear any misconceptions about the price of dissertation statistics help. Once the student inquires about the pricing, he or she will quickly see that the time and energy saved by having dissertation statistics help is well worth what the student must pay for the dissertation statistics help.
Dissertation statistics help will make the acquisition of any dissertation easier and more obtainable. While other students who do not seek dissertation statistics help struggle with many aspects of their dissertation, the student who is smart enough to seek dissertation statistics help will finish on-time and with much less stress. Because dissertation statistics help provides guidance, help, and assistance throughout the entire process, the student is sure to finish on-time and with a great amount of success.
Statistics Solutions is the country's leader in dissertation statistics help. Contact Statistics Solutions today for a free 30-minute consultation.
Dissertation statistics help can provide invaluable help, guidance and assistance to anyone writing a dissertation.The dissertation is the hardest and most challenging part of any student’s academic career. For this reason, it is important to seek dissertation statistics help. Unfortunately, many students do not choose to seek dissertation statistics help until they have reached a ‘stopping point’ or a problem. And while dissertation statistics help can fix that problem, the student has already wasted valuable time as he or she did not seek dissertation statistics help sooner.
Dissertation statistics help provides help throughout the dissertation—from the very beginning, to the very end of the dissertation. Dissertation statistics help is provided by trained professionals who are well versed in all things regarding dissertations and statistics. Dissertation statistics help is also provided by people who have already received their doctoral degrees, and thus dissertation statistics help is provided by people who have gone through every single stress that the student has gone through. This can be important as it is important to be able to understand the needs of the student who is acquiring dissertation statistics help.
Dissertations rely heavily on statistics and unfortunately many students do not know enough about statistics to be successful in their research and design for their project. Here again dissertation statistics help can assist the student. Dissertation statistics help will step in at the very beginning of the project and will help the student design that project properly. Dissertation statistics help will go over every single thing that needs to be done and dissertation statistics help will make sure that the student has the proper tools to complete the project. There will be no “wrong turns’ with dissertation statistics help, as dissertation statistics help will be there assisting the student every single step of the way.
One of the most important advantages of obtaining dissertation statistics help is the availability and accessibility of dissertation statistics help. While all students have advisors, these advisors are not always available. What’s more, most time these advisors tell students what is wrong AFTER the student has already made the mistake. Thus, the student must go back and continually redo aspects of his or her dissertation. Because dissertation statistics help is always available, however, the student will not make costly mistakes because he or she has someone looking over his/her shoulder and ensuring that he or she does not make any mistakes. Thus, much time will be saved simply by having dissertation statistics help.
Dissertation statistics help is well worth any cost associated with it. In fact, if a student is debating whether or not to use dissertation statistics help, a simple phone call can clear any misconceptions about the price of dissertation statistics help. Once the student inquires about the pricing, he or she will quickly see that the time and energy saved by having dissertation statistics help is well worth what the student must pay for the dissertation statistics help.
Dissertation statistics help will make the acquisition of any dissertation easier and more obtainable. While other students who do not seek dissertation statistics help struggle with many aspects of their dissertation, the student who is smart enough to seek dissertation statistics help will finish on-time and with much less stress. Because dissertation statistics help provides guidance, help, and assistance throughout the entire process, the student is sure to finish on-time and with a great amount of success.
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