SPSS Statistical Labs (Must Know Logistic Regression / Discriminant Analysis / Principal Component Analysis)
LAB 3 – Principal Component Analysis Question 1 Using the textbook checklist, conduct and write up the results of a Principal components analysis with varimax rotation for the attached data set. The data is a 10 item questionnaire called the religious commitment inventory (RCI). The RCI is a religious commitment inventory with 10 likert scale type answers from 1 = “not at all true of me” to 5 = “totally true of me.” Treat the items as continuous data. **Make sure that when you screen for any missing data, do not replace it, just make sure you report it. Then conduct your PCA with the 4 criteria that the textbook uses, and finally summarize your results using that same list/sample. ***No need to examine for univariate outliers, since all answers are on the Likert scale from 1 to 5 (just double check that all answers are indeed between 1 and 5 and that no data entry errors were made). ***Please list the Mahalanobis distance critical value for any multivariat outliers found (there will likely be many multivariate outliers in this data set, since you are using 10 variables, delete all outliers that need to be deleted, just leave the ID number in and report how many outliers had to be deleted) ****After you have removed outliers, please make sure to screen your data for normality and report your conclusions in the Results write up. Use the range between -1 and +1 as acceptable range for skewness. **Use the standard for item load onto a component of .6 or higher and .2 difference between components Please use the following data set to run the above analysis and assumptions testing: File: “ Lab 3_PCA_Data.sav ” LAB 3 – Principal Component Analysis LAB 3 – Principal Component Analysis Question 2 How many missing values are in this data set? A. Zero (none) B. 5 C. 10 D. 20 Question 3 How many multivariate outliers should be removed from this data set based on the Mahalanobis Distance statistic analysis? A. Zero (none) B. 85 C. 10 D. 20 Question 4 Correct reporting of the chi-square statistic for Mahalanobis Distance in this case is: 2 χ ( ___?____ ) = ___?____, p < ___?____ Question 5 Based on your examination of normality for all variables, how many variables have skewness numbers outside of the acceptable range of +/- 1? A. B. C. D. Zero (none) 1 5 10 Question 6 What is the value of Kaiser-Meyer-Olkin measure of sampling adequacy in this case? A. B. C. D. .500 .800 .868 .450 Question 7 What is the value of chi-square for Bartlett’s test of sphericity in your output? A. B. C. D. .868 6900 8342 45 Question 8 Based on your examination of KMO measure of sampling adequacy and Bartlett’s test of sphericity, which conclusion is most accurate regarding sampling adequacy in this data set? A. Not enough information is provided to make a conclusion regarding sampling adequacy B. Sampling adequacy was unacceptable since the KMO measure was well above the cutoff value of .50 and Bartlett’s test was significant C. Sampling adequacy was acceptable since the KMO measure was well below the cutoff value of .50 and Bartlett’s test was not significant D. Sampling adequacy was acceptable since the KMO measure was well above the cutoff value of .50 and Bartlett’s test was significant LAB 3 – Principal Component Analysis Question 9 Since this is an actual scale with 10 items you can also run a reliability analysis, Cronbach’s alpha, to determine the scale’s reliability. What was the RCI’s Cronbach’s alpha (run this for the entire scale together, I know in general you might divide it up and look at Cronbach’s alpha separately for each factor but that would give away how many components there should be in this so I am keeping it all together to make sure you can run a Cronbach’s alpha)? Hint: Use the dataset with outliers removed for this question. A. B. C. D. 10 79.6 .796 .949 Question 10 If someone were analyzing a set of new data to determine the underlying structure of a new theory, and determine if the variable set could be reduced, which of the following analyses would most likely be conducted FIRST. A. principal components analysis B. factor analysis C. con rmatory factor analysis D. Cronbach’s alpha Question 11 What is happening when you are comparing the correlations to the reproduced correlations in a factor analysis/PCA? A. B. C. D. parsimony, which reduces the factors to the least amount examining the fit between the model and the data examining the percentage of variance necessary to accept the model examining the factors fi **SPSS OUTPUT REQUIRED**
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