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PSYCH 404

Data Analysis

Assignment 2

INSTRUCTIONS: Answer all parts of each question.  Be sure to turn in your work – your SPSS printouts, your own calculations and your answers to each question.  You may NOT work with another person on this assignment.  This is because knowing how to use SPSS is a skill that will be valuable to you in this class and in the future.  

1. Using the SPSS file, “Chapter 1 Data,” calculate percentile ranks for MATH scores.  In SPSS, click on TRANSFORM in the menu bar and then on the RANK CASES option in the drop down box.  Transfer MATH into the variable(s) window, then click on RANK TYPES.  Be sure to click the RANK and FRACTIONAL RANK AS % boxes. Click on CONTINUE and then OK.  SPSS will create two new variables in your data file.  One will give you the rank of each score; while the other will present the percentile rank.  Each new variable will have the same name as the original variable name but will be preceded by an r for RANK and a p for PERCENTILE.  What does the percentile rank tell you?  What is the percentile rank for a raw score of 60 on the MATH scale?

2. Using the SPSS file, “Chapter 1 Data,” calculate z-scores for the SPELLING scores.  To calculate z-scores in SPSS simply select the DESCRIPTIVES option from the ANALYZE menu and click the SAVE STANDARDIZED VALUES AS VARIABLES option.  A new variable will be added to your data file prefixed by a Z.  See chapter 6 in the Pallant text for information on DESCRIPTIVES.  Why are z-scores important?  What will the mean and standard deviation of a new distribution of z-scores be?

3. Using the SPSS file, “Chapter 1 Data,” perform a linear transformation for the READING scores assuming a standard deviation of 10 and a mean of 50.  Use the COMPUTE procedure in the TRANSFORM menu in SPSS.  NOTE:  You will need to have created the standard score variable before attempting a linear transformation.  See chapter 8 in the Pallant text for step-by-step instructions on how to compute a new variable. Why are linear transformations important?