WASON CARD SORT:

1
WASON CARD SORT DATA ANALYSIS
Week 3 Practical
2
WEEK 3 PRACTICAL
WASON CARD SORT
LECTURE 1
PRACTICAL
WEEK 1
NO LECTURE
NO PRACTICAL
WEEK 2
NONPARAMETRICS 1
1ST PRACTICAL
WEEK 3
NONPARAMETRICS 2
1ST ANALYSIS IN SPSS
WEEK 4
SAMPLING DISTRIBUTIONS
1ST ANALYSIS BY HAND
WEEK 5
HYPOTHESIS TESTING
2ND PRACTICAL
WEEK 6
RELATED T-TEST
2ND ANALYSIS IN SPSS
WEEK 7
2ND ANALYSIS BY HAND
INDEPENDENT T-TEST
WEEK 8
3RD PRACTICAL
INDEPENDENT ANOVA
WEEK 9
3RD ANALYSIS IN SPSS
DEPENDENT ANOVA
WEEK 10
NO PRACTICAL
NO LECTURE
3
LEARNING OUTCOMES
WASON CARD SORT
BY THE END OF THE SESSION, YOU SHOULD BE ABLE TO
Use SPSS to test the first experimental
hypothesis of the Wason card sorting experiment
and produce a related graph.
Use SPSS to test the second experimental
hypothesis of the Wason card sorting experiment
and produce a related graph.
Use the graphs to interpret your chi-square
findings.
Make a start on writing up your RESULTS and
DISCUSSION sections for your lab report.
4
WASON CARD SORT
METHOD RECAP
DESIGN
Half of the people in the room did the concrete
first, half did the abstract.
ABSTRACT
CONCRETE
ABSTRACT
CONCRETE
then
then
Research Questions
Base your hypotheses on the following research
questions
Q1 Is performance better on some versions of the
Wason card sorting task than others the first
time it is performed?
ABSTRACT
CONCRETE
ABSTRACT
CONCRETE
then
then
Q2 Is performance on the abstract task affected
if it follows a concrete scenario?
ABSTRACT
CONCRETE
ABSTRACT
CONCRETE
then
then
5
WASON CARD SORT
RESULTS
The third column shows whether the individual got
their first problem right or wrong.
The first column shows subject number. And yes,
there are 180.
1
RIGHT
2
WRONG
The second column shows which type of problem
each individual solved first.
The fourth column shows whether the individual
got the abstract problem right or wrong.
1
ABSTRACT
2
CONCRETE
1
RIGHT
2
WRONG
6
WASON CARD SORT
RESULTS
Lets make the data look a little more meaningful
by changing the numeric values into textual
values. Go to variable view and select values.
For first_problem, CORRECT1 and CORRECTA,
associate the values (e.g., 1, 2) with the
appropriate value labels (e.g., abstract,
concrete wrong, right).
first_problem
1
ABSTRACT
2
CONCRETE
CORRECT1
1
RIGHT
2
WRONG
CORRECTA
1
RIGHT
2
WRONG
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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?
CONCRETE (1st)
ABSTRACT (1st)
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 gt crosstabs.
Lets go there now.
8
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?
CONCRETE (1st)
ABSTRACT (1st)
vs.
In order to build a chi-square table, we need to
put our various categories into rows and columns.
Lets 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.
9
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?
CONCRETE (1st)
ABSTRACT (1st)
vs.
First problem solved First problem correct Crosstabulation First problem solved First problem correct Crosstabulation First problem solved First problem correct Crosstabulation First problem solved First problem correct Crosstabulation First problem solved First problem correct Crosstabulation First problem solved First problem correct Crosstabulation
First problem correct First problem correct Total
Right Wrong Total
First problem solved Abstract Count 8 82 90
First problem solved Abstract Expected Count 20,5 69,5 90,0
First problem solved Concrete Count 33 57 90
First problem solved Concrete Expected Count 20,5 69,5 90,0
Total Total Count 41 139 180
Total Total Expected Count 41,0 139,0 180,0
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
?2 (1) 19.74, p lt .001
10
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?
Chi-square value
Significance level
Degrees of freedom
?2 (1) 19.74, p lt .001
11
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 Dont 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
12
WASON CARD SORT
RESULTS
Q2 Is performance on the abstract task affected
if it follows a concrete scenario?
ABSTRACT (1st)
ABSTRACT (2nd)
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 gt crosstabs.
Lets go there now.
13
WASON CARD SORT
RESULTS
Q2 Is performance on the abstract task affected
if it follows a concrete scenario?
ABSTRACT (1st)
ABSTRACT (2nd)
vs.
In order to build a chi-square table, we need to
put our various categories into rows and columns.
Lets 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.
14
WASON CARD SORT
RESULTS
Q2 Is performance on the abstract task affected
if it follows a concrete scenario?
ABSTRACT (1st)
ABSTRACT (2nd)
vs.
First problem solved Abstract problem correct Crosstabulation First problem solved Abstract problem correct Crosstabulation First problem solved Abstract problem correct Crosstabulation First problem solved Abstract problem correct Crosstabulation First problem solved Abstract problem correct Crosstabulation First problem solved Abstract problem correct Crosstabulation
Abstract problem correct Abstract problem correct Total
Right Wrong Total
First problem solved Abstract Count 8 82 90
First problem solved Abstract Expected Count 9,5 80,5 90,0
First problem solved Concrete Count 11 79 90
First problem solved Concrete Expected Count 9,5 80,5 90,0
Total Total Count 19 161 180
Total Total Expected Count 19,0 161,0 180,0
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
?2 (1) 0.53, p .47
15
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 Dont 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 Grahams webpage, or ask a
tutor for help
16
WASON CARD SORT
DISCUSSION
GET TOGETHER IN GROUPS OF THREE OR FOUR AND
REFLECT ON TODAYS EXPERIENCE USING THE FOLLOWING
QUESTIONS
Why have I done this particular statistical test?
What do the data actually tell me with respect to
my experimental hypotheses?
What implications do the data have for the
studies outlined in the intro?
17
LEARNING OUTCOMES
SAMPLING DISTRIBUTIONS
BY THE END OF THE SESSION, YOU SHOULD BE ABLE TO
Use SPSS to test the first experimental
hypothesis of the Wason card sorting experiment
and produce a related graph.
Use SPSS to test the second experimental
hypothesis of the Wason card sorting experiment
and produce a related graph.
Use the graphs to interpret your chi-square
findings.
Make a start on writing up your RESULTS and
DISCUSSION sections for your lab report.