Choosing among statistics:
◦ 1. number of independent variables
◦ 2. level of measurement (nominal to ratio)
◦ 3. number of dependent variables
◦ 4. level of measurement (nominal to ratio)
◦ 5. other considerations (normality)
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Cross-tabulation

1 Independent variable (categorical)
◦ Men versus women

1 Dependent variable (categorical)
 Bought or didn’t buy
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How do you measure the covariation?

1. “inter-ocular” test
◦ does it “hit you between the eyes?”
◦ does it look big?
◦ is this a managerially important result?
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Male
Female
Bought [Did not]
70%
[30%]
40%
[60%]
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Covariation
one categorical independent variable
 e.g., male or female
one categorical dependent variable
 e.g., blonde, not blonde
◦ 10% of males are blonde, 40% of females
◦ significant covariation?
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2. Statistics (exact probability)
calculate the difference between:
◦ observed rates
◦ expected rates (chance)
 if observed is different than chance,
 non-independence between variables
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OBSERVED
Male
Female
Blonde
10
40
• TOTAL 50
Not |
90 |
60

TOTAL

100

100

200
|
150
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Calculate Chi-square:
Sum of (Observed-Expected)
2
Expected
[do this for each cell]
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Male
Female
TOTAL
Blonde
10
25
[9]
40
25
[9]
50
Not
90
75
[3]
60
75
[3]
150
| TOTAL
| 100
12
|
100
12
|
200
X2= 24
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2. Interpret result:
◦ to X2 w/ (k-1)*(n-1) “degrees of
freedom”
(Table X2 1 d.f. p < .05 = 3.84)
◦ Because X2 obs = 24 > 3.84,
 REJECT Ho
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Crosstabulation
Count
SEX
Total
male
female
DIANAFUN
yes
no
83
94
239
95
322
189
maybe
67
83
150
Marketing Research
Total
244
417
661
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Crosstab
% within SEX
SEX
Total
male
female
DIANAFUN
yes
no
34.0%
38.5%
57.3%
22.8%
48.7%
28.6%
maybe
27.5%
19.9%
22.7%
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Total
100.0%
100.0%
100.0%
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Chi-Square Tests
Pearson Chi-Square
N of Valid Cases
Value
34.365a
661
df
2
Asymp. Sig.
(2-sided)
.000
a. 0 cells (.0%) have expected count less than 5. The
minimum expected count is 55.37.
Marketing Research
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Crosstabulation
Count
SEX
Total
male
female
DIFUN1
none
yes
94
83
95
239
189
322
Marketing Research
Total
177
334
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Crosstabulation
% within SEX
SEX
Total
male
female
DIFUN1
none
yes
53.1%
46.9%
28.4%
71.6%
37.0%
63.0%
Marketing Research
Total
100.0%
100.0%
100.0%
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Chi-Square Tests
Pearson Chi-Square
N of Valid Cases
Value
30.197b
511
df
1
Asymp. Sig.
(2-sided)
.000
a. Computed only for a 2x2 table
b. 0 cells (.0%) have expected count less than 5. The
minimum expected count is 65.47.
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