[ Home ]                                 PSYC 220 (Research Methods), Fall 2006   S. J. Gilbert, SUNY-Oneonta                      


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V SPSS ASSIGNMENTS FROM Cronk, "How to Use SPSS," Third Edition

SPSS Assignments    revised 8/29/06

> Each SPSS assignment should contain two parts:

1.                              Part 1: SPSS Output sheets.

                                 Part 2: Answers to questions (see below).

      > Part 1:  The work you do on SPSS will result in output sheets.  These should be emailed directly to me at a special email address created for this purpose: spss220@oneonta.edu . Be sure to include your FAKE NAME (not your real name), Assignment #, Dataset (1-5), and Data Form (A-E) in the body of the email.  You also should make a paper copy for your own use in answering the questions in Part 2.

3.   > Part 2:  Each SPSS assignment appears below.  Each assignment includes reading and instructional material.  In addition, there are questions for you to answer.  The identical questions appear on a computer survey instrument, one for each assignment.  You access the survey by clicking on the appropriate hyperlink that can be found in each assignment..  Enter your answers to questions on the survey, and then press the SUBMIT button.  This will send an email containing your answers, directly to me.  You will receive feedback (comments and grades) from me, at a later time.

 

Grading of SPSS Assignments

>Each assignment is worth 7.5 points.

>7.5 points are awarded for each assignment containing no errors, that is turned in on time, along with the accompanying SPSS output sheets.

>Feedback concerning an assignment containing errors is given to you via email.  REPLY to this email with clearly labeled corrections to each identified error (Note: Do NOT send a new email; REPLY to the email you receive from me).  This process will continue until there are no errors.  1.5 points are deducted for each required resubmission.  Thus, you receive 6.0 points (80%) if 1 resubmission  is required, 4.5 points (60%) if 2 resubmissions are required, etc.  Please note the "deadline" for submitting each SPSS assignment.  0 points will be awarded for assignments not completed after the deadline.

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ASSIGNMENT 1

>>> Read Chapter 1 in the Cronk text.

>>> Dataset #1 contains the data you will be working with for Assignment 1. (Note: Use the form of Dataset #1 [A,B,C,D, or E] that you have been assigned.)  Input the data from DATASET #1 into the DATAVIEW WINDOW of SPSS.  Be sure to SAVE your work onto a floppy disc, for future use.

 

DATASET #1.  20 students in a section of PSYC 100 were given their second test on either WHITE or BLUE paper. The test contained 50 multiple-choice questions; the number of correct answers constituted a student's SCORE on the test.

 

>>> Using the DEFINE VARIABLE WINDOW, give each variable a VARIABLE NAME (e.g., COLOR), and a VARIABLE LABEL (e.g., COLOR OF TEST).
>>> Give the VALUES of the variable SEX the LABELS "1 = male" and "2 = female".
>>> Give the VALUES of the variable COLOR the LABELS "1 = white" and "2 = blue."
>>>  Be sure to SAVE the file on a floppy disc, as well as on the hard drive or "P" drive of your computer; you will need it for future assignments.

          Answer the following Questions using the online Survey Form for Assignment 1


Which variables that you inputted into SPSS would be considered...
(A1-1) DEPENDENT VARIABLES;
(A1-2) MANIPULATED INDEPENDENT VARIABLES;
(A1-3) NON-MANIPULATED (i.e. measured), SUBJECT-CLASSIFICATION VARIABLES?

          

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ASSIGNMENT 2 (Revised, 1/30/06)

>>> Read designated sections of Chapter 2 in the Cronk text.

 

Ch. 2 Entering and Modifying Data
     Skip Section 2.2, pgs. 12-13
        Resume at top of pg. 14

 

>>> Dataset #5 contains the data you will be working with for Assignment 2.  Click on the form of Dataset #5 [A,B,C,D, or E] that you have been assigned.
 

In her Psychology of Personality class, Rachel learned about the "Big Five" personality factors, and was interested in three of them -- Extroversion, Agreeableness, and Conscientiousness.  Rachel gave the three "Big Five" subscales for these factors to 22 women living in Hays Hall.  Rachel thought that the SUM of each subject's scores on the three scales would provide a measure of the construct "CHARISMA."  (Rachel also measured the popularity of each subject -- but this is not relevant to our interests here)

 

>>>Using Compute command of SPSS, create a NEW VARIABLE, labeled CHARISMA, that is the sum of subjects' Extroversion, Agreeableness, Conscientiousness scores.

>>> Using the DESCRIPTIVES procedure, generate descriptive statistics for subjects' CHARISMA SCORE.

>>> Save the OUTPUT FILE containing the descriptive statistics on a floppy disc, as well as on the hard drive or "P" drive of your computer.  You will need this output to answer the questions below.
>>> Send the contents of the OUTPUT FILE containing the descriptive statistics to spss220@oneonta.edu as an email attachment.

 

          Answer the following Questions using the online Survey Form for Assignment 2


(A2-1)  What is the Mean CHARISMA score?
(A2-2)  What are the MINIMUM and the MAXIMUM CHARISMA scores?
(A2-3)  What is Standard Deviation of the distribution of the CHARISMA scores?
 

Look over questions A2-4 and A2-5.  If the answers are not obvious to you, then read this.....

Suppose I calculate the mean number of CDs in the dorm rooms of 200 SUCO students, along with the standard deviation.  I get:  M = 15, SD = 3.  What does the SD statistic tell us?   If we randomly choose students from the sample of 200, our best guess of the number of CDs possessed by any one of them will be 15 (the mean).  But our guesses will not be perfect; on average, we will underestimate or overestimate the number of CDs these students have, by about 3.

 

But we can be more precise.  If the distribution of CDs in the rooms of these 200 students is roughly NORMAL -- the classic bell-shaped curve -- then certain things will be true, by virtue of the nature of the SD statistic.

 

(1) About 2/3rds of the scores will be within 1 SD of the mean.   That means that about 2/3rds of the 200 students will have between 12 CDs (Mean - 1SD = 15 - 3 = 12) and 18 CDs (Mean + 1 SD = 15 + 3 = 18).

 

(2) About 95% of the scores will be within 2 SDs of the mean.   That means that about 95% of the 200 students will have between 9 CDs (Mean - 2SD = 15 - 6 = 9) and 21 CDs (Mean + 2 SDs = 15 + 6 = 21).

 

(3) About 99% of the scores will be within 3 SDs of the mean.   That means that about 99% of the 200 students will have between 6 CDs (Mean - 3SD = 15 - 9 = 6) and 24 CDs (Mean + 3 SDs = 15 + 9 = 24).

 

Whenever a distribution is roughly normal, and the number of scores considered is reasonably large, then it will be true that around 68% of the scores will be within 1 SD, 95% will be within 2SDs, and 99% within 3 SDs of the mean.  This should help you with Assignment #2

 

(A2-4)  Given the Standard Deviation, what is the range within which we would expect approximately 2/3rds of the CHARISMA scores to fall?
(A2-5)  Given the Standard Deviation, what is the range within which we would expect approximately 95% of the CHARISMA scores to fall?


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ASSIGNMENT 3

>>> Read designated sections of Chapter 3 in the Cronk text.

 

Ch. 3 Descriptive Statistics
   Skip Section 3.2
      Resume at Section 3.3
   Skip Section 3.5

 

>>> Load the form of DATASET #1 that you have been assigned (A,B,C,D, or E) into the DATAVIEW window.

>>> Using the DESCRIPTIVES procedure, generate descriptive statistics for subjects' SCORE on the test.

>>> Using the ANALYZE -> COMPARE MEANS -> MEANS  procedure, generate separate descriptive statistics for the test SCORES of the MALE and the FEMALE subjects.

>>> Using the ANALYZE -> COMPARE MEANS -> MEANS  procedure, generate separate descriptive statistics for the test SCORES of subjects who took BLUE tests and those who took WHITE tests.

>>> Using the ANALYZE -> COMPARE MEANS -> MEANS  procedure, and employing the "LAYERING" feature,  generate separate descriptive statistics for the test SCORES of subjects with each combination of sex and paper color, i.e., MEN who took BLUE tests, MEN who took WHITE tests, WOMEN who took BLUE tests, and WOMEN who took WHITE tests. 

>>> Save the OUTPUT FILE containing the descriptive statistics on a floppy disc, as well as on the hard drive or "P" drive of your computer. You will need this output to answer the questions below.
>>> Send the contents of the OUTPUT FILE containing the descriptive statistics to spss220@oneonta.edu as an email attachment.

 

          Answer the following Questions using the online Survey Form for Assignment 3

 

(A3-1) What is the MEAN test SCORE for all subjects?

(A3-2) What is the LOWEST (minimal) SCORE of any FEMALE subject?

(A3-3) What is the STANDARD DEVIATION of the SCORES of the MALE subjects?

(A3-4) What is the HIGHEST (maximum) SCORE of anyone who took the BLUE test?

(A3-5) What is the MEAN SCORE of subjects who took the WHITE test?

(A3-6) What is the MEAN SCORE of MEN who took the BLUE test?

(A3-7) What is the MEAN SCORE of WOMEN who took the WHITE test?

(A3-8) Which of the four groups (MEN/WHITE, MEN/BLUE, WOMEN/WHITE, WOMEN/BLUE) did best on the test?

(A3-9) Which of the four groups did the worst?
 


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ASSIGNMENT 4

>>> Read Alison's story in Box 3.
 

Box 3.
Alison was interested in determining whether the color of the paper a test was printed on, affected students' performance on the test.  She had a hunch that students will do better on a blue paper test than on a white paper test. To test her hunch, Alison gave the 20 students in a particular PSYC 100 section a 50 multiple choice question psychology test either on blue paper or white paper.  Which color test a student received was determined by a flip of a coin.  Later, Alison calculated the mean test score earned by the blue paper test group, and the mean for the white paper test group, and compared the two means.

       

     Answer Questions (A4-1) - (A4-12) using the online Survey Form for Assignment #4


(A4-1) What is the DEPENDENT VARIABLE in Alison's experiment?
(A4-2) What is the INDEPENDENT VARIABLE in Alison's experiment?
(A4-3)  How many levels of the INDEPENDENT VARIABLE are there? 
(A4-4) In some experiments, each participant is exposed to only one of the levels of the INDEPENDENT VARIABLE -- these are called BETWEEN- or INDEPENDENT GROUPS experiments.  In other experiments, each participant is exposed to all levels of the INDEPENDENT VARIABLE -- these are called WITHIN SUBJECT or REPEATED MEASURES experiments.  Which kind of experiment is Alison's?
(A4-5) Is Alison's INDEPENDENT VARIABLE a MANIPULATED or SUBJECT (classification) variable? 
(A4-6) State a NULL HYPOTHESIS concerning the effect of the independent variable on the dependent variable in Alison's experiment.
(A4-7) State Alison's RESEARCH HYPOTHESIS.
(A4-8) Is Alison's RESEARCH HYPOTHESIS DIRECTIONAL or NON-DIRECTIONAL? 

 

>>> Read Chapter 6, Section 6.3 in the Cronk text.
>>> Load the form of  DATASET #1 that you have been assigned (A,B,C,D, or E) into the DATAVIEW window.
>>> Make sure you understand the definition in Box 4.


Box 4.
The INDEPENDENT SAMPLES t-test is used when a researcher has divided subjects into TWO GROUPS, and wishes to compare the means of these two groups on a dependent variable that has been measured using an interval or ratio scale of measurement .

 

>>> Perform an INDEPENDENT SAMPLES t-test appropriate to test Alison's hypothesis.

>>> Send the contents of the OUTPUT FILE containing the results of the t-test to spss220@oneonta.edu as an email attachment.

(A4-9) Report the dependent variable means and standard deviations for each of the two groups.
(A4-10) Speculate as to whether the means appear to be significantly different from each other (i.e., more different than you might simply expect by chance).
(A4-11) Using the model phrasing suggested by Cronk on page 58, describe the results of the t-test performed on the data of Alison's experiment.  Be sure to include the relevant statistics (t, df, sig., means, sds) and to state whether or not the results support Alison's hypothesis (i.e., are the results statistically significant?).
(A4-12) Make up a phony t and p that would compel the opposite conclusion from the one you reached in questions (A4-11).


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ASSIGNMENT 5

>>> Read Greg's story in Box 5.
 

Box 5.
Greg noticed that it seemed easier to read and understand printed material when the letters were in a bold font rather than the standard font.  To test out this hunch, Greg gave 20 PSYC 100 students their 100-question final exam in a special format.  The even numbered questions appeared in the standard font, but the odd numbered questions were in a bold font.  Greg calculated a separate mean score for the 50 standard-font (even numbered) questions and the 50 bold-font (odd numbered) questions, and compared these two means.

 

       Answer Questions (A5-1) - (A5-11) using the online Survey Form for Assignment #5


(A5-1) What is the INDEPENDENT VARIABLE in Greg's experiment?
(A5-2) How many levels of the INDEPENDENT VARIABLE are there?
(A5-3) What is the DEPENDENT VARIABLE in Greg's experiment?
(A5-4) In some experiments, each participant is exposed to only one of the levels of the INDEPENDENT VARIABLE -- these are called BETWEEN GROUPS or INDEPENDENT GROUPS experiments.  In other experiments, each participant is exposed to all levels of the INDEPENDENT VARIABLE -- these are called WITHIN SUBJECT or REPEATED MEASURES experiments.  Which kind of experiment is Greg's?
(A5-5) State a NULL HYPOTHESIS concerning the effect of the independent variable on the dependent variable in Greg's experiment.
(A5-6) State Greg's RESEARCH HYPOTHESIS.
(A5-7) Is Greg's RESEARCH HYPOTHESIS DIRECTIONAL or NON-DIRECTIONAL? 

 

>>> Read Chapter 6, Section 6.4 in the Cronk text.
>>> Dataset #2 contains the data you will be working with for Assignment 2. Click on the form of Dataset #2 [A,B,C,D, or E] that you have been assigned.

>>> Make sure you understand the definition in Box 6.


Box 6.
A PAIRED t-test compares the means of two measures taken on the same people. These can be the same measure given twice (e.g., the same 50-item psychology test given first as a pretest, and later as a posttest), or two different measures that use the same or comparable scales (e.g. the 50 even and the 50 odd numbered questions on a 100 question psychology test).

 

>>> Do a PAIRED t-test to test Greg's research hypothesis.

>>> Send the OUTPUT FILE containing the results of the t-test to spss220@oneonta.edu as an email attachment.

(A5-8) Report the MEANS and STANDARD DEVIATIONS for the two sets of scores that you are comparing with your t-test.
(A5-9) Speculate as to whether the means appear to be significantly different from each other (i.e., more different than you might simply expect by chance).
(A5-10) Using the model phrasing suggested by Cronk on page 62, describe the results of the t-test performed on the data of Greg's experiment.  Be sure to include the relevant statistics (t, df, sig., means, sds) and to state whether or not the results support Greg's hypothesis (i.e., are the results statistically significant?).
Ah, but check out Box 7 before you answer this question!

Box 7.
Note:  The significance level (p) reported by SPSS is appropriate for tests of non-directional ("two-tail") hypotheses (e.g., men differ from women on a measure of happiness).  Because you are testing a directional ("one-tail") hypothesis (e.g., men have higher happiness scores than women), you must divide the reported significance level by 2.  Thus, if the (two-tail p reported by SPSS is .064 (which would NOT be statistically significant), the (one-tail) p that actually applies to the test of your hypothesis is .032 (which IS statistically significant).  p = .032 is what you should report.  But note.  The results must be in the SAME direction that your directional hypothesis predicts! 

 

(A5-11) Make up a phony t and p that would compel the opposite conclusion from the one you reached in question (5-10).


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ASSIGNMENT 6

>>> Review Alison's story in Box 3.
>>> Read Jenny's story in Box 8.
 

Box 8.
Jenny was intrigued by Alison's experiment on the effect of blue vs. white paper on how students did on tests.  She agreed with Alison's hunch that students will do better on a blue paper test than on a white paper test and wanted to replicate that aspect of Alison's experiment.  But Jenny went farther.  She reasoned that students should do POORER on a test written on RED paper than one written on the standard white paper.  To test her hunch, Jenny gave a different group of 20 students in a PSYC 100 section a 50 question multiple-choice sychology test either on blue, white, or red paper.  Which color test a student received was determined by a roll of dice (1 or 2 = blue; 3 or 4 = white; 5 or 6 = red).  Later, Jenny calculated the mean test score earned by the blue, white and red paper test groups, and compared the three means.

   

     Answer Questions (A6-1) - (A6-9) using the online Survey Form for Assignment #6


(A6-1) What is the DEPENDENT VARIABLE in Jenny's experiment?
(A6-2) What is the INDEPENDENT VARIABLE in Jenny's experiment?
(A6-3)  How many levels of the INDEPENDENT VARIABLE are there? 
(A6-4) In some experiments, each participant is exposed to only one of the levels of the INDEPENDENT VARIABLE -- these are called BETWEEN GROUP or INDEPENDENT GROUPS experiments.  In other experiments, each participant is exposed to all levels of the INDEPENDENT VARIABLE -- these are called WITHIN SUBJECT or REPEATED MEASURES experiments.  Which kind of experiment is Jenny's?
(A6-5) Is Jenny's INDEPENDENT VARIABLE a MANIPULATED or SUBJECT variable? 
(A6-6) State a NULL HYPOTHESIS concerning the effect of the independent variable on the dependent variable in Jenny's experiment.
(A6-7) If we consider the WHITE group to be a CONTROL group, to which the BLUE and RED groups are compared, then  Jenny actually has TWO research hypotheses.  State Jenny's two RESEARCH HYPOTHESES.
(A6-8) Are Jenny's two RESEARCH HYPOTHESES DIRECTIONAL or NON-DIRECTIONAL? 

 

>>> Read Chapter 6, Section 6.5 in the Cronk text.
>>> Dataset #3 contains the data you will be working with for Assignment 6. Click on the form of Dataset #3 [A,B,C,D, or E] that you have been assigned.

>>> Read Box # 9.


Box 9.
An INDEPENDENT SAMPLES (BETWEEN GROUP) ANOVA compares the means of MORE THAN TWO groups of subjects on a dependent variable that has been measured using an interval or ratio scale of measurement. 

 

RESEARCH hypotheses and STATISTICAL hypotheses differ. You need to understand how.  So please read the following carefully.

 

Suppose I gather PSYC, SOC, and POLI-SCI majors and measure how funny they are.  My RESEARCH hypotheses might be: (a) PSYC majors are funnier then SOC majors; and (b) SOC majors are funnier than POLI-SCI majors.  These are two DIRECTIONAL, RESEARCH hypotheses.

 

Statistically, the first step in testing these two RESEARCH hypotheses is to do an INDEPENDENT SAMPLES (BETWEEN GROUP) ANOVA, directly comparing the funniness means of the three groups.  The primary STATISTICAL HYPOTHESIS in an ANOVA always is NON-DIRECTIONAL; it is the hypothesis that the means differ from each other more than would be expected by chance.  If the STATISTICAL ANOVA hypothesis is NOT SUPPORTED -- if the three means DON'T differ more than would be expected by chance -- then we conclude that neither of our RESEARCH HYPOTHESES are SUPPORTED (i.e., PSYC majors are NOT funnier than SOC majors, and SOC majors are NOT funnier than POLI-SCI majors).

 

But, what if the STATISTICAL hypothesis of the ANOVA -- that the three groups differ in funniness -- IS SUPPORTED (at p < .05)?  Then, we instruct SPSS to perform a SHEFFE POST-HOC test.  This is like doing three INDEPENDENT SAMPLES t-tests (comparing the funniness means of PSYC vs. SOC majors, SOC vs. POLI-SCI majors, and PSYC vs. POLI-SCI majors).  The first two comparisons are direct tests of our two RESEARCH HYPOTHESES.

 

>>> Perform an Analysis of Variance (ANOVA) on the data from Jenny's experiment.  Be sure to instruct SPSS to include descriptive statistics (Mean & Standard Deviation of the dependent variable measure for each group), and the Sheffe Post-Hoc Comparison test.

>>> Send the OUTPUT FILE containing the results of the ANOVA and the Post-Hoc Comparison test to spss220@oneonta.edu as an email attachment.

(A6-9) Using the model phrasing suggested by Cronk on page 66, write a short paragraph describing the results of the ANOVA and Sheffe tests, and interpreting the meaning of these results. Include the following information:
(a) a statement of the Means and Standard Deviations of the three groups;
(b) a statement of the result of the ANOVA in terms of the F, df-between, df-within, and significance level
        (e.g., F(2, 197) = 18.716, p = .001);
(c) a statement of the decision the ANOVA compels concerning whether or not you can ACCEPT the STATISTICAL HYPOTHESIS that the three group means differ more than chance expectation; and

(d) what conclusions the Sheffe tests suggest concerning whether or not there are significant differences between each pair of means addressed in your RESEARCH HYPOTHESES (i.e., whether the results support your specific, directional RESEARCH HYPOTHESES).

 

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ASSIGNMENT 7

 

>>> Review Greg's story in Box 5.
>>> Read Ken's story in Box 10.
 

Box 10.
Ken could see how it would be easier to read and understand material in a bold font than material in a standard font.  Ken noticed that in some of his textbooks, certain blocks of material (like a quotation) are written in italics, and he always found that hard to read.  Ken speculated that just as students would do better on test questions written in a bold font (than in a standard font), they would do poorer on questions written in italics (than in a standard font).  To test these predictions, Ken gave 21 students in a section of ANTH 100 their 150 question final exam in a special format.  Questions 1,4,7,10....148 appeared in a standard font, questions 2,5,8,11....149 were in a bold font, and questions 3,6,9,12....150 were in an italics font.  Ken calculated the students' mean scores on the standard, bold, and italic questions, and then compared the means.

      

      Answer Questions (A7-1) - (A7-8) on the online Survey Form for Assignment #7


(A7-1) What is the INDEPENDENT VARIABLE in Ken's experiment?
(A7-2) How many levels of the INDEPENDENT VARIABLE are there?
(A7-3) What is the DEPENDENT VARIABLE in Ken's experiment?
(A7-4) In some experiments, each participant is exposed to only one of the levels of the INDEPENDENT VARIABLE -- these are called BETWEEN or INDEPENDENT GROUPS experiments.  In other experiments, each participant is exposed to all levels of the INDEPENDENT VARIABLE -- these are called WITHIN SUBJECT or REPEATED MEASURES experiments.  Which kind of experiment is Ken's?
(A7-5) State a NULL HYPOTHESIS concerning the effect of the independent variable on the dependent variable in Ken's experiment.
(A7-6) If we consider the STANDARD FONT questions to be the CONTROL treatment, to which the BOLD FONT and the ITALIC FONT treatments are compared, then Ken actually has TWO research hypotheses.  State Ken's two RESEARCH HYPOTHESES.
(A7-7) Are Ken's RESEARCH HYPOTHESES DIRECTIONAL or NON-DIRECTIONAL? 

 

>>> Read Chapter 6.7 in the Cronk text. 
>>> Dataset #4 contains the data you will be working with for Assignment 7. Click on the form of Dataset #4 [A,B,C,D, or E] that you have been assigned.

>>> Make sure you understand the definition in Box 11.


Box 11.
A REPEATED MEASURES ONE-WAY ANOVA in many ways resembles the PAIRED SAMPLE t-test (Assignment #5), but it compares the means of MORE than two measures (rather than just two measures) taken on the same people. As with the PAIRED SAMPLE t-test, it only makes sense to compare the means of measures that are taken on the same scale.

 

Note:  The following discussion will resemble one that you read in Box 9, for Assignment 6.  There the discussion related to a BETWEEN (or INDEPENDENT) GROUPS design.  Here it relates to a REPEATED MEASURES (or WITHIN -SUBJECT) design. 

 

RESEARCH hypotheses and STATISTICAL hypotheses differ.  Suppose I gather 100 students, have them listen to 10 minute samples of CLASSICAL MUSIC, 50's ROCK, and contemporary HIP-HOP music, and measure how much they like each on a 1 (hate) to 10 (love) scale.  My RESEARCH hypotheses might be: (a) students will like HIP-HOP better than ROCK; and (b) students will like CLASSICAL less than ROCK.  These are two DIRECTIONAL research hypotheses.

 

Statistically, the first step in testing these two hypotheses is to do a ONE-WAY REPEATED MEASURES ANOVA, directly comparing the mean ratings given to the three kinds of music.  The primary STATISTICAL HYPOTHESIS in an ANOVA always is NON-DIRECTIONAL; it is the hypothesis that the means differ from each other more than would be expected by chance.

 

If the STATISTICAL ANOVA hypothesis is NOT SUPPORTED -- if the three means DON'T differ more than would be expected by chance -- then we conclude that neither of our RESEARCH HYPOTHESES are SUPPORTED (i.e., students do NOT like HIP-HOP better than ROCK, and students do NOT like CLASSICAL less than ROCK).

 

But, what if the STATISTICAL ANOVA hypothesis -- that the three mean music ratings differ -- IS SUPPORTED (at p < .05)?  Then, you must do what you learned in Assignment 5!  Instruct SPSS to do a PAIRED SAMPLES (WITHIN-SUBJECTS) t-test, comparing the means for HIP-HOP and ROCK (testing the first RESEARCH HYPOTHESIS), and a second t-test comparing  the means for CLASSICAL and ROCK (testing the second RESEARCH HYPOTHESIS).  These two t-tests directly test your two RESEARCH  HYPOTHESES.

 

>>> Do a REPEATED MEASURES ONE-WAY ANOVA on these three variables.  But before you hit the 'OK' button to run the analysis, read this note....

    

Note: You will want the output to include the mean and standard deviation for each variable.  In order to obtain these statistics, you must click on the OPTIONS button on the lower right hand corner of the 'Repeated Measures' dialog box, and then click on DESCRIPTIVES.  Then click on the CONTINUE button, and finally, on the OK button.

 

(A7-8) Using the model phrasing suggested by Cronk on page 73, write a brief statement of the relevant statistics produced by the REPEATED SAMPLES ONE-WAY ANOVA procedure (i.e., the means, standard deviations, F, dfs, and p).  Make sure your description includes answers to the following questions: (a)  Do the results enable you to accept the STATISTICAL ANOVA HYPOTHESIS that the means for the test questions written in the three font styles differ more than would be expected by chance; (b) Do the results warrant performing POST-HOC t-tests comparing the means of each pair of scores; and (c) If the answer to (b) is "yes," then what conclusions do the results of each POST-HOC PAIRED t-test warrant concerning Ken's two RESEARCH HYPOTHESES? 

>>> Send the contents of the of the OUTPUT FILE containing the results of the ANOVA and the POST-HOC t-tests (if necessary), to spss220@oneonta.edu  as an email attachment.

 


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ASSIGNMENT 8

>>> Read Rachel's story in Box 12.
 

Box 12.
In her Psychology of Personality class, Rachel learned about the "Big Five" personality factors, and was interested in how three of them -- Extroversion, Agreeableness, and Conscientiousness -- related to each other, and to how many friends a student has.  Rachel gave the three "Big Five" subscales that measure Extroversion, Agreeableness, and Conscientiousness, to 22 women living in Hays Hall.  In addition, she asked the women to make a list of people on campus whom they consider to be a friend.  Rachel counted the number of  names on each subject's list and used that number as a measure of popularity.  Rachel expected each personality scale to show a positive relationship with her measure of popularity. 

 

       Answer Questions (A8-1) - (A8-5) using the online Survey Form for Assignment #8

 

Need help in understanding (A8-1) - (A8-3)?  Well, even if you think you don't, check out this Guide to Understanding Hypothesis Testing in Correlation Studies!


(A8-1) Name two variables that Rachel expected to have a positive relationship with each other.
(A8-2) State a NULL HYPOTHESIS and a DIRECTIONAL (one-tail) ALTERNATE (RESEARCH) HYPOTHESIS concerning the expected relationship between these two variables.
(A8-3) If the Null Hypothesis were true, then what value CORRELATION COEFFICIENT would you expect to obtain for these two variables?

 

>>> Read Chapter 5, Section 5.1 in the Cronk text.  If you have the 3rd Edition, review Appendix E, Section E.3.  If you have the 4th Edition, review Chapter 4, Section 4.4.
>>> Load the form of DATASET #5 that you have been assigned (A,B,C,D, or E) into SPSS.

>>> Produce a SCATTERPLOT that graphically shows the actual relationship between the variables you chose in (8-1). 

(A8-4)  Does the shape of the scatter suggest that a significant correlation has been obtained?  Why (or why not)?

>>> Perform the CORRELATION procedure, making an inter-correlation table showing the relationships among all four variables that Rachel measured.

>>> Send the contents of theOUTPUT WINDOW containing the SCATTERPLOT and INTER-CORRELATION TABLE to spss220@oneonta.edu as an email attachment.

(A8-5) Using the model phrasing suggested by Cronk on page 41 (for a significant result) or page 42 (for a result that is not significant), describe the results of the correlation procedure for the two variables you chose in (8-1). Be sure to include the relevant statistics (r, df, sig.), and to state whether or not the results support Rachel's hypothesis (i.e., are the results statistically significant?).

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ASSIGNMENT 9

>>> Read Chapter 5, Sections 5.3 & 5.4 in the Cronk text.
>>> Review Rachel's story in Box 12, and the intercorrelation table you produced for Assignment 8.
>>> Read Dan's story in Box 13.
 

Box 13.
Rachel showed Dan the intercorrelation table she had made.  Dan was intrigued, and wondered how well you could predict a young woman's popularity, from knowledge of her levels of Extroversion, Agreeableness, and Conscientiousness.  To find out, Dan obtained Rachel's data, and performed a Multiple Regression Analysis, with POPULAR as the DEPENDENT (Y) VARIABLE, and Extroversion (X1), Agreeableness (X2), and Conscientiousness (X3) as three INDEPENDENT, or PREDICTOR variables..

>>> Load the form of  DATASET #5 that you have been assigned (A,B,C,D, or E) into SPSS.
>>> Do the MULTIPLE REGRESSION that Dan did.

>>> Send the contents of the OUTPUT FILE containing MULTIPLE REGRESSION to spss220@oneonta.edu as an email attachment.

 

       Answer Questions (A9-1) - (A9-5) using the online Survey Form for Assignment #9
 

(9-1) What percentage of the overall variance in subjects' POPULARITY scores is explained by (related to) the three predictor variables?
(9-2) What percentage of the overall variance in subjects' POPULARITY scores is NOT explained by (related to) the three predictor variables?

>>> Report and interpret the statistics (F, dfs, p) that show whether the percentage described in (9-1) represents a statistically significant level of prediction, i.e., whether the R SQUARE is greater than that which we would expect to occur by chance.

>>> Read Box 14.
 

Box 14.
The Multiple Regression also tells us whether each predictor (independent) variable significantly contributes to the prediction of the outcome (dependent) variable after the contribution of the other predictor variable(s) have been factored out--in effect telling us whether each predictor accounts for a UNIQUE portion of the variance in the outcome variable -- a portion NOT explained by any other predictor, or combination of predictors.

 

(9-3) Report the relevant statistics (t, p), and determine whether they support the contention that Extroversion predicts a SIGNIFICANT, UNIQUE portion of the variance in POPULARITY.
(9-4) Report the relevant statistics (t, p), and determine whether they support the contention that Agreeableness predicts a SIGNIFICANT, UNIQUE portion of the variance in POPULARITY.
(9-5) Report the relevant statistics (t, p), and determine whether they support the contention that Conscientiousness predicts a SIGNIFICANT, UNIQUE portion of the variance in POPULARITY.

 

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ASSIGNMENT 10

>>> Load the form of  DATASET #1 that you have been assigned (A,B,C,D, or E)  into SPSS.
>>> Review Alison's story in Box 3, Assignment 4.
>>> Read Box 15.
 

Box 15.
The INDEPENDENT VARIABLE of Alison's experiment was COLOR of PAPER

(white vs. blue).  Alison made sure that exactly 10 of her 20 subjects got a WHITE paper test, and 10 got a BLUE paper test.  What Alison didn't do was assure that MEN and WOMEN were equally represented in the WHITE and the BLUE groups.  Ideally, the selection of subjects should have produced the following breakdown.

                      COLOR OF PAPER

 

WHITE

BLUE

MEN

n = 5

n = 5

WOMEN

n = 5

n = 5

                                                            N(white) =10        N(blue) = 10   

 

With such a breakdown, differences in the mean test score of subjects in the WHITE vs. BLUE test groups could not be attributed to one group containing mostly men and the other group containing mostly women, because both groups had the same proportion of men to women.

 

But what if the breakdown looked like this?

                      COLOR OF PAPER

 

WHITE

BLUE

MEN

n = 8

n = 2

WOMEN

n = 2

n = 8

                                                            N(white) =10        N(blue) = 10   

 

Here, the proportion of MEN to WOMEN in the WHITE group appears to be SIGNIFICANTLY different from the proportion of MEN to WOMEN in the BLUE group.  In such a situation, differences between the mean test scores of subjects in the WHITE and the BLUE group MIGHT be due, at least in part, to differences between how well MEN (who make up most of the WHITE group) and WOMEN (who make up most of the BLUE group) do on tests.  This would seriously compromise the INTERNAL VALIDITY of Alison's experiment.

 

>>> Read Chapter 7, Section 7.2 in the Cronk text.

 

      Answer Questions (A10-1) - (A10-4) using the online Survey Form for Assignment #10

 

(10-1) To determine whether the proportion of MEN to WOMEN SIGNIFICANTLY differed in the two groups, Alison did a CHI SQUARE test of INDEPENDENCE, with SEX and COLOR as the two variables.  State the NULL HYPOTHESIS and the ALTERNATE (Research) HYPOTHESIS of Alison's CHI SQUARE test.  Note:  The only two variables being tested are SEX and COLOR.  Your hypotheses should make no mention of test scores, or the internal validity of Alison's experiment; your hypotheses for this CHI SQUARE test should only deal with the question of whether the COLOR of the test a subject received was RELATED to the SEX of the SUBJECT.

 

>>> Make a CROSSTABULATION TABLE and perform Alison's CHI SQUARE test.

>>> Send the contents of the OUTPUT FILE containing the CROSSTABULATION TABLE and CHI SQUARE test to spss220@oneonta.edu as an email attachment.

(10-2)  Describe the essential information contained in the CROSSTABULATION table.  What conclusion do the data appear to suggest, concerning whether or not the proportion of MALES to FEMALES differ in the WHITE vs. BLUE groups?
(10-3) Report and interpret the relevant CHI SQUARE TEST statistics (CHI-SQ, df, p).
(10-4) Has the internal validity of Alison's WHITE vs. BLUE paper experiment been compromised by the SEX VARIABLE?  What tells you that?

 

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ASSIGNMENT 11

>>> Review Alison's story in Box 3.
>>> Read Sonia's story in Box 16.
 

Box 16. 
Sonia was Alison's research partner, and also was interested in the effect of blue vs. white paper on how students did on tests. Sonia wondered whether the color of paper would affect men and women the same way.  That's why Sonia insisted that they record the sex of her subjects.  So Sonia reanalyzed the data, looking at how both the role of the color of the paper (BLUE vs. WHITE) AND the sex of subject (MALE vs. FEMALE) affected test scores. Sonia predicted that men would perform equally well on blue and white paper tests, but that women would perform significantly better on blue tests than on white tests.  In other words, Sonia expected that the color of paper would have no effect on the scores of men, but would have a substantial effect -- favoring blue tests -- on the scores of women.

 

     Answer Questions (A11-1) - (A11-9) using the online Survey Form for Assignment #11


(A11-1) What is the DEPENDENT VARIABLE in Sonia's experiment?
(A11-2) How many INDEPENDENT VARIABLES are there in Sonia's experiment?
(A11-3) What is the total number of conditions (cells) in Sonia's experiment? 
(A11-4) How would you characterize Sonia's Experiment? (a) Between-Groups Factorial Design; (b) Repeated-Measures (totally within-group) Factorial Design; or (c) Mixed-Design (1 Between group variable and 1 Repeated measures variable). 

>>>Box 17 represents the structure of Sonia's experiment.  The letters A-G represent means.  For example, the letter A represents the mean test score of men who took the test on blue paper.  The letter H represents the mean test score for all women.

                                                       Box 17.

  BLUE WHITE  
MEN     A      B     G
WOMEN     C      D     H
      E          F  

 

(A11-5)  What letter represents the mean score of women who took white tests?

 

>>>The ANOVA provides answers to three statistical questions: (1) is there a main effect for the factor (independent variable) COLOR OF PAPER; (2) is there a main effect for the factor (independent variable) SEX OF SUBJECT; and (3) is there an interaction of the two factors (COLOR x SEX).  

 

(A11-6) Which comparison provides an answer to the question:  (1) is there a main effect for the factor COLOR OF PAPER?

     A-B      C-D      A-C      B-D      A-B-C-D      E-F      G-H  

 

(A11-7) Which comparison provides an answer to the question:  (2) is there a main effect for the factor SEX OF SUBJECT?

     A-B      C-D      A-C      B-D      A-B-C-D      E-F      G-H  

 

(A11-8) Which comparison provides an answer to the question:  (3) is there an interaction of the two factors (COLOR x SEX)?

     A-B      C-D      A-C      B-D      A-B-C-D      E-F      G-H  

 

(A11-9) Given her hypotheses, which of these three answers is Sonia most interested in?

(1) is there a main effect for the factor COLOR OF PAPER

(2) is there a main effect for the factor SEX OF SUBJECT

(3) is there an interaction of the two factors (COLOR x SEX)

 

>>> Read Chapter 6, Section 6.6 in the Cronk text.
>>> Load the form of  DATASET #1 that you have been assigned (A,B,C,D, or E) into SPSS. 

>>> Perform the appropriate Analysis of Variance (ANOVA) on the data from Sonia's experiment.  Be sure to instruct SPSS to include descriptive statistics.

>>> Send the contents of the OUTPUT FILE containing the results of the ANOVA to spss220@oneonta.edu as an email attachment.

 

(A11-10) Using the model phrasing suggested by Cronk on pages 69 and 70, write a short paragraph describing the results of the ANOVA.  Be sure to include all appropriate descriptive (means & sds) and inferential (Fs, df, p) statistics, and to speak directly to whether or not the results support Sonia's hypotheses.

 

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ASSIGNMENT 12  

>>> Review Greg's story in Box 5.

>>> Review Ronnie's story in Box 17. 
 

Box 17. 
Ronnie was Greg's research partner, and also was interested in the effect of standard vs. bold font on how students did on tests. Ronnie wondered whether the type of font would affect men and women the same way.  That's why Ronnie insisted that they record the sex of the subjects.  So Ronnie reanalyzed the data, looking at how both the role of the type of font (STANDARD vs. BOLD) and the sex of subject (MALE vs. FEMALE) affected test scores. Ronnie predicted that women would perform equally well on standard and bold font questions, but that men would perform significantly better on bold font questions than on standard font questions.  In other words, Ronnie expected that the type of font would have no effect on the scores of women, but would have a substantial effect -- favoring the bold font -- on the scores of men.

 

     Answer Questions (A12-1) - (A12-9) using the online Survey Form for Assignment #12


(A12-1) What is the DEPENDENT VARIABLE in Ronnie's experiment?
(A12-2) How many INDEPENDENT VARIABLES are there in Ronnie's experiment?
(A12-3) What is the total number of conditions (cells) in Ronnie's experiment? 
(A12-4) How would you characterize Ronnie's Experiment? (a) Between-Groups Factorial Design; (b) Repeated-Measures (totally within-group) Factorial Design; or (c) Mixed-Design (1 Between group variable and 1 Repeated measures variable). 

>>>Box 19 represents the structure of Ronnie's experiment.  The letters A-G represent means.  For example, the letter A represents the mean test score of men on the standard font questions. The letter H represents the mean test score for all women.

                                                       Box 17.

  STAND   BOLD  
MEN     A      B     G
WOMEN     C      D     H
      E          F  

 

(A12-5)  What letter represents the mean score of women on standard font questions?

 

>>>The ANOVA provides answers to three statistical questions: (1) is there a main effect for the factor FONT; (2) is there a main effect for the factor SEX OF SUBJECT; and (3) is there an interaction of the two factors (FONT x SEX).  

 

(A12-6) Which comparison provides an answer to the question: Is there a main effect for the factor FONT?

     A-B      C-D      A-C      B-D      A-B-C-D      E-F      G-H  

 

(A12-7) Which comparison provides an answer to the question: Is there a main effect for the factor SEX OF SUBJECT?

     A-B      C-D      A-C      B-D      A-B-C-D      E-F      G-H  

 

(A12-8) Which comparison provides an answer to the question:  Is there an interaction of the two factors (FONT x SEX)?

     A-B      C-D      A-C      B-D      A-B-C-D      E-F      G-H  

 

(A12-9) Given her hypotheses, which of these three answers is Ronnie most interested in?

(1) is there a main effect for the factor FONT of question

(2) is there a main effect for the factor SEX OF SUBJECT

(3) is there an interaction of the two factors (FONT x SEX)

 

>>> Read Chapter 6, Section 6.8 in the Cronk text.
>>> Load the form of  DATASET #2 that you have been assigned (A,B,C,D, or E) into SPSS.

>>> Perform a Mixed-Design Analysis of Variance (ANOVA) on the data from Ronnie's experiment.  Be sure to instruct SPSS to include descriptive statistics.

>>> Send the contents of the OUTPUT FILE containing the results of the ANOVA to spss220@oneonta.edu as an email attachment.

 

(A12-10) Using the model phrasing suggested by Cronk on pages 76 and 77, write a short paragraph describing the results of the ANOVA.  Be sure to include all appropriate descriptive (means & sds) and inferential (Fs, df, p) statistics, and to speak directly to whether or not the results support Ronnie's hypotheses.

 

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