wason card sort: data analysis
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WASON CARD SORT:DATA ANALYSIS
Week 3 Practical
WEEK 3 PRACTICALWASON CARD SORT
WEEK 1
WEEK 2
WEEK 3
WEEK 4
WEEK 5
WEEK 6
WEEK 7
WEEK 8
WEEK 9
WEEK 10
LECTURE 1 PRACTICAL
NONPARAMETRICS 1 1ST PRACTICAL
NONPARAMETRICS 2 1ST ANALYSIS IN SPSS
SAMPLING DISTRIBUTIONS 1ST ANALYSIS BY HAND
HYPOTHESIS TESTING 2ND PRACTICAL
RELATED T-TEST 2ND ANALYSIS IN SPSS
INDEPENDENT T-TEST
INDEPENDENT ANOVA
DEPENDENT ANOVA
NO LECTURE
2ND ANALYSIS BY HAND
3RD PRACTICAL
3RD ANALYSIS IN SPSS
NO PRACTICAL
NO LECTURE NO PRACTICAL
LEARNING OUTCOMES
BY THE END OF THE SESSION, YOU SHOULD BE ABLE TO:
Use the graphs to interpret your chi-square findings.
Use SPSS to test the second experimental hypothesis of the Wason card sorting experiment and produce a related graph.
Use SPSS to test the first experimental hypothesis of the Wason card sorting experiment and produce a related graph.
Make a start on writing up your RESULTS and DISCUSSION sections for your lab report.
WASON CARD SORT
Research Questions
WASON CARD SORT
Base your hypotheses on the following research questions:
METHOD RECAP
Q2: Is performance on the abstract task affected if it follows a concrete scenario?
Q1: Is performance better on some versions of the Wason card sorting task than others the first time it is performed?
DESIGN
Half of the people in the room did the concrete first, half did the abstract.
ABSTRACT CONCRETEthen ABSTRACT CONCRETE then
ABSTRACT CONCRETEthen ABSTRACT CONCRETE then
ABSTRACT CONCRETE thenABSTRACT CONCRETEthen
WASON CARD SORT RESULTS
The first column shows subject number. And yes, there are 180.
The second column shows which type of problem each individual solved
first.
1 = 2 =
ABSTRACT CONCRETE
The third column shows whether the individual got their first problem right
or wrong.
The fourth column shows whether the individual got the abstract problem right or wrong.
1 = 2 =
WRONG RIGHT
1 = 2 =
WRONG RIGHT
WASON CARD SORT RESULTS
Let’s make the data look a little more meaningful by changing the numeric values into textual values. Go to variable view and select values.
1 = 2 =
ABSTRACT CONCRETE
CORRECTA
CORRECT1
first_problem
For first_problem, CORRECT1 and CORRECTA, associate the values (e.g., 1, 2) with the appropriate value labels (e.g., abstract, concrete; wrong, right).
1 = 2 =
WRONG RIGHT
1 = 2 =
WRONG RIGHT
WASON CARD SORT RESULTS
ABSTRACT (1st) CONCRETE (1st)
Q1: Is performance better on some versions of the Wason card sorting task than others the first time it is performed?
vs.
If we are interested in comparing categorises of responses, then the
chi-square test is appropriate.
In SPSS, the chi-square test is hidden away underneath
descriptive statistics > crosstabs.
Let’s go there now.
WASON CARD SORT RESULTS
Q1: Is performance better on some versions of the Wason card sorting task than others the first time it is performed?
In order to build a chi-square table, we need to put our various
categories into rows and columns.
Let’s put first_pr as a row and CORRECT1 as a column. This will
show us the frequency distributions.
Under statistics, we also need to make sure the chi-square test is
performed, so tick that.
Under cells, also make sure that both observed and expected are clicked.
ABSTRACT (1st) CONCRETE (1st) vs.
WASON CARD SORT RESULTS
Q1: Is performance better on some versions of the Wason card sorting task than others the first time it is performed?
The second table (after case processing summary) confirms
our 180 observations and displays the frequency distribution of right and wrong responses for the two
kinds of Wason card sort test.
The third table provides us with the chi-square value, which may
be reported as:
χ2 (1) = 19.74, p < .001
Chi-Square Tests
19.740b 1 .00018.193 1 .00020.887 1 .000
.000 .000
19.631 1 .000
180
Pearson Chi-SquareContinuity Correctiona
Likelihood RatioFisher's Exact TestLinear-by-LinearAssociationN of Valid Cases
Value dfAsymp. Sig.
(2-sided)Exact Sig.(2-sided)
Exact Sig.(1-sided)
Computed only for a 2x2 tablea.
0 cells (.0%) have expected count less than 5. The minimum expected count is20.50.
b.
ABSTRACT (1st) CONCRETE (1st) vs.
First problem solved * First problem correct Crosstabulation
First problem correct
TotalRight Wrong
First problem solved Abstract Count 8 82 90
Expected Count 20,5 69,5 90,0
Concrete Count 33 57 90
Expected Count 20,5 69,5 90,0
Total Count 41 139 180
Expected Count 41,0 139,0 180,0
WASON CARD SORT RESULTS
Q1: Is performance better on some versions of the Wason card sorting task than others the first time it is performed?
χ2 (1) = 19.74, p < .001
Chi-Square Tests
19.740b 1 .00018.193 1 .00020.887 1 .000
.000 .000
19.631 1 .000
180
Pearson Chi-SquareContinuity Correctiona
Likelihood RatioFisher's Exact TestLinear-by-LinearAssociationN of Valid Cases
Value dfAsymp. Sig.
(2-sided)Exact Sig.(2-sided)
Exact Sig.(1-sided)
Computed only for a 2x2 tablea.
0 cells (.0%) have expected count less than 5. The minimum expected count is20.50.
b.
Degrees of freedom
Chi-square value Significance
level
WASON CARD SORT RESULTS
Q1: Is performance better on some versions of the Wason card sorting task than others the first time it is performed?
You will need to graphically represent your results, too
Don’t forget to give your Figure a number and a title
When you refer to the Figure in the main text, make sure you give the
exact descriptive statistics
Note: no error bars, because this is categorical data
WASON CARD SORT
Q2: Is performance on the abstract task affected if it follows a concrete scenario?
If we are interested in comparing categorises of responses, then the
chi-square test is appropriate.
In SPSS, the chi-square test is hidden away underneath
descriptive statistics > crosstabs.
Let’s go there now.
RESULTS
ABSTRACT (2nd)ABSTRACT (1st) vs.
WASON CARD SORT
In order to build a chi-square table, we need to put our various
categories into rows and columns.
Let’s put first_pr as a row and CORRECTA as a column. This will
show us the frequency distributions.
Under statistics, we also need to make sure the chi-square test is
performed, so tick that.
Under cells, also make sure that both observed and expected are clicked.
RESULTS
Q2: Is performance on the abstract task affected if it follows a concrete scenario?
ABSTRACT (2nd)ABSTRACT (1st) vs.
WASON CARD SORT
The second table (after case processing summary) confirms
our 180 observations and displays the frequency distribution of right and wrong responses for the two
kinds of Wason card sort test.
The third table provides us with the chi-square value, which may
be reported as:
χ2 (1) = 0.53, p = .47
RESULTS
Q2: Is performance on the abstract task affected if it follows a concrete scenario?
Chi-Square Tests
.530b 1 .467
.235 1 .628
.532 1 .466.629 .314
.527 1 .468
180
Pearson Chi-SquareContinuity Correctiona
Likelihood RatioFisher's Exact TestLinear-by-LinearAssociationN of Valid Cases
Value dfAsymp. Sig.
(2-sided)Exact Sig.(2-sided)
Exact Sig.(1-sided)
Computed only for a 2x2 tablea.
0 cells (.0%) have expected count less than 5. The minimum expected count is9.50.
b.
ABSTRACT (2nd)ABSTRACT (1st) vs.
First problem solved * Abstract problem correct Crosstabulation
Abstract problem correct
TotalRight Wrong
First problem
solved
Abstract Count 8 82 90
Expected Count 9,5 80,5 90,0
Concrete Count 11 79 90
Expected Count 9,5 80,5 90,0
Total Count 19 161 180
Expected Count 19,0 161,0 180,0
WASON CARD SORT RESULTS
Q2: Is performance on the abstract task affected if it follows a concrete scenario?
Once again, you will need to graphically represent your results
Don’t forget to give your Figure a number and a title
When you refer to the Figure in the main text, make sure you give the exact descriptive statistics
Note: no error bars, because this is categorical data
If you have trouble, refer back to the Excel graph-making guides on Graham’s webpage, or ask a tutor for help
WASON CARD SORT DISCUSSION
GET TOGETHER IN GROUPS OF THREE OR FOUR AND REFLECT ON TODAY’S EXPERIENCE USING THE FOLLOWING QUESTIONS
Why have I done this particular statistical test?
What implications do the data have for the studies
outlined in the intro?
What do the data actually tell me with respect to my experimental hypotheses?
LEARNING OUTCOMES
BY THE END OF THE SESSION, YOU SHOULD BE ABLE TO:
SAMPLING DISTRIBUTIONS
Use the graphs to interpret your chi-square findings.
Use SPSS to test the second experimental hypothesis of the Wason card sorting experiment and produce a related graph.
Use SPSS to test the first experimental hypothesis of the Wason card sorting experiment and produce a related graph.
Make a start on writing up your RESULTS and DISCUSSION sections for your lab report.
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