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Social Sciences

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# Quantitative Analysis in Social Science Research (Research Paper Sample)

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It's a research paper Analysis and please follow the instruction that is given source..

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QUESTION 1 (30 points): Select three different examples that demonstrate an ANOVA test. For two of these examples, you should be able to reject the null hypothesis. For one of these examples, you should fail to reject the null hypothesis. Set up the research questions and hypotheses. Describe the main components of the ANOVA and interpret the findings. Create a new fourth example in which you would use an ANOVA test and explain whether or not you think you`d be able to reject the null hypothesis (and why). This example must not already appear as one of the associations in the tables. Your answer should make specific references to the labels and values of the variables.

ANOVA

ANOVA also known as Analysis Of Variance, is commonly be used in cases where there are more than two groups. When thee are only two samples, then we can use the t-test to compare the means of the different samples however, it may become unreliable when we have more than two samples. If we are comparing only two means, then the t-test also known as the independent samples will give the same results as the case of ANOVA. A question therefore arise on whether why not to use multiple t-tests. The t-test can only be used to test differences between two means. When there are more than two means, it is possible to compare each mean with each other mean using many t-tests. However, conducting such multiple t-tests can lead to severe complications and in such circumstances we use ANOVA. This technique is commonly used when an alternative procedure is required for testing the hypotheses concerning means especially in places when there are several populations.

In summary, we can say that ANOVA is used to compare the means of more than two samples. This can best be demonstrated by the use of examples as shown below:

Example 1:

Testing the effect of five different exercises

To make the test, we recruit ten men and assign one type of exercise to two men. Therefore we will have a total of five groups. After several weeks of training, their weights are recorded. From the results, we can therefore be able to establish whether the effect of these exercises on them was significant or not. This can be done comparing the average weight of the men in the different categories. This forms an example of one-way balanced ANOVA. This is because there is only one category that its effects have been considered for the study and balanced as the same number of men has been assigned on each exercise. Therefore the basic idea in the test is to test whether the samples are all alike or not. In this case we will accept the null hypothesis since there was a significant difference in the weights of the men based on the types of exercises that they went through.

Example 2: difference in resistance for different three temperature levels.

The data below resulted from measuring the difference in resistance resulting from subjecting identical resistors to three different temperatures for a pe...

ANOVA

ANOVA also known as Analysis Of Variance, is commonly be used in cases where there are more than two groups. When thee are only two samples, then we can use the t-test to compare the means of the different samples however, it may become unreliable when we have more than two samples. If we are comparing only two means, then the t-test also known as the independent samples will give the same results as the case of ANOVA. A question therefore arise on whether why not to use multiple t-tests. The t-test can only be used to test differences between two means. When there are more than two means, it is possible to compare each mean with each other mean using many t-tests. However, conducting such multiple t-tests can lead to severe complications and in such circumstances we use ANOVA. This technique is commonly used when an alternative procedure is required for testing the hypotheses concerning means especially in places when there are several populations.

In summary, we can say that ANOVA is used to compare the means of more than two samples. This can best be demonstrated by the use of examples as shown below:

Example 1:

Testing the effect of five different exercises

To make the test, we recruit ten men and assign one type of exercise to two men. Therefore we will have a total of five groups. After several weeks of training, their weights are recorded. From the results, we can therefore be able to establish whether the effect of these exercises on them was significant or not. This can be done comparing the average weight of the men in the different categories. This forms an example of one-way balanced ANOVA. This is because there is only one category that its effects have been considered for the study and balanced as the same number of men has been assigned on each exercise. Therefore the basic idea in the test is to test whether the samples are all alike or not. In this case we will accept the null hypothesis since there was a significant difference in the weights of the men based on the types of exercises that they went through.

Example 2: difference in resistance for different three temperature levels.

The data below resulted from measuring the difference in resistance resulting from subjecting identical resistors to three different temperatures for a pe...

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