Reference no: EM131524769
Advanced Statistics Assignment
Part A.
Dependent t test In this activity, we are interested in finding out whether participation in a creative writing course results in increased scores of a creativity assessment. For this part of the activity, you will be using the data file "Activity 6a.sav". In this file, "Participant" is the numeric student identifier, "CreativityPre" contains creativity pre-test scores, and "CreativityPost" contains creativity post-test scores. A total of 40 students completed the pre-test, took the creativity course, and then took the post-test.
1. Exploratory Data Analysis/Hypotheses.
a. Perform exploratory data analysis on CreativityPre and CreativityPost. Using SPSS, calculate the mean and standard deviation of these two variables.
b. Construct an appropriate chart/graph that displays the relevant information for these two variables.
c. Write the null and alternative hypotheses used to test the question above (e.g., whether participation in the course affects writing scores).
2. Comparison of Means
a. Perform a dependent t test to assess your hypotheses above (note that many versions of SPSS use the term "paired samples t test" rather than dependent t test; the test itself is the same.
b. Write one or two paragraphs that describe the dataset, gives your hypothesis, and presents the results of the dependent sample t test. Be sure that your writing conforms to APA style.
Part B.
Independent t test In this activity, we will start with the data file used in Part A ("Activity 6a.sav"). Suppose, however, you [the researcher] encountered a small problem during data collection: after the post-tests were collected, you realized that the post-test form did not ask for the students' identification number.
As such, it will be impossible to match pre-test scores to post-test scores. Rather than simply give up, you start thinking about the data you do have, and try to determine whether you can salvage your project.
In assessing the situation, you realize that you have 40 pre-test scores and 40 post-test scores, but no way to link them. While it will result in a weaker comparison, you determine that you are still able to compare pre-test vs. post-test scores; you will use a between-subjects design rather than a within-subjects design.
1. Create the data set.
a. Using the "Activity 6a.sav" file as a starting point, create a new dataset that you can use with the between subjects design. Hint: you will no longer need the variables CreativePre and CreativeTest. Instead, you have only one variable for the score on the creativity test. A second (or grouping) variable will serve to indicate which test the student took.
b. Submit the dataset as one of the Activity 6 files. Name the file in the following format: lastnamefirstinitialPSY7107-6a.sav (example: smithbPSY7107-6a.sav).
2. Exploratory Data Analysis/Hypotheses.
a. Perform exploratory data analysis on CreativityPre and CreativityPost. Using SPSS, calculate the mean and standard deviation of these two variables.
b. Construct an appropriate chart/graph that displays the relevant information for these two variables.
c. Write the null and alternative hypotheses used to test the question above (e.g., whether participation in the course affects writing scores).
3. Comparison of Means
a. Perform an independent t test to assess your hypotheses above (note that many versions of SPSS use the term "independent samples t test" rather than simply "independent t test".
b. Write one or two paragraphs that describe the dataset, gives your hypothesis, and presents the results of the dependent sample t test. Be sure that your writing conforms to APA style.
4. Comparison of Designs
a. In this activity you used the same dataset to analyze both a between- and within-subjects design. Create a single paragraph (using the material you wrote above), that presents both sets of results.
b. Explain, in 300-500 words, whether the two tests resulted in the same findings. Did you expect this to be the case? Why or why not? What have you learned in this activity?
Part C.
ANOVA All of us have had our blood pressure measured while at our physician's office. How accurate are these measurements? It may surprise you to learn that there is something called "white coat syndrome"-the tendency of some people to exhibit elevated blood pressure in clinical (medical) settings only. In other words, for these people the very fact that the physician is taking their blood pressure causes it to increase. In this activity, you will be using the "Activity 6c.sav" data file to determine whether you find support for the existence of white coat syndrome. In this study, 60 participants were randomly assigned to one of three groups. The "settings" variable indicates the location in which the participants' blood pressure was recorded: 1=home, 2=in a doctor's office, and 3=in a classroom setting. The "SystolicBP" variable contains the participants' systolic pressure (the "upper" number). The "DiastolicBP" variable contains the participant's diastolic pressure (the "lower" number).
1. Exploratory Data Analysis/Hypotheses.
a. Perform exploratory data analysis on both the SystolicBP and DiastolicBP variables. Using SPSS, calculate the mean and standard deviation of these two variables. Be sure that your analysis is broken down by setting (e.g., you will have six means, six SD's, etc.).
b. Create two graphs-one for systolic and one for diastolic pressure. Each graph should clearly delineate the three groups.
c. Write a null and alternative hypothesis for the comparison of the three groups (note that your hypothesis will state that the three groups are equivalent; be sure to word your null hypothesis correctly).
2.ANOVA.
a. Using the "Activity 6c.sav" data file, perform two single factor ANOVAs: one using SystolicBP and one using DiastolicBP as the dependent variable.
b. If appropriate for either or both of the ANOVAs, perform post hoc analyses to determine which groups actually differ.
c. Write one paragraph for each ANOVA (be sure to use APA style). At a bare minimum, each paragraph should contain the three means, three SD's, ANOVA results (F, df), post hoc tests (if applicable), effect size, and an interpretation of these results.