Data Analysis: ANOVA and Chi-Square

Running head: DATA ANALYSIS: ANOVA AND CHI-SQUARE
Data Analysis: ANOVA and Chi-Square
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DATA ANALYSIS: ANOVA AND CHI-SQUARE
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Table of Contents
SPSS Assignment.......................................................................................................................2
Solution 1.A...........................................................................................................................2
Solution 1.B............................................................................................................................3
Solution 1.C............................................................................................................................3
Solution 2.A...........................................................................................................................4
Solution 2.B............................................................................................................................5
Stat Crunch Assignment.............................................................................................................6
Solution 1...............................................................................................................................6
Solution 2...............................................................................................................................7
Reference....................................................................................................................................9

DATA ANALYSIS: ANOVA AND CHI-SQUARE
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SPSS Assignment
Solution 1.A.
Table 1: ANOVA test
Hypothesis:
Null hypothesis, H0: The mean of the percent of women on voyages across centuries is not
statistically different from each other.
Alternative hypothesis, HA: The mean of the percent of women on voyages across centuries is
statistically different from each other.
Test Statistic and p-value:
From the ANOVA table presented in table 1, the test statistic is F-stat which is equal
to 44.011. The corresponding p-value of the F-stat is 0.000.

DATA ANALYSIS: ANOVA AND CHI-SQUARE
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Decision Rule:
If the p-value of the test statistic is less than the given significance level then it
indicates that there is enough evidence to reject the null hypothesis and accept the alternative
hypothesis (Emerson, 2017).
In the table 1, the p-value of the F-stat is less than 0.05 which indicates to reject the
null hypothesis and accept the alternative hypothesis. This implies that the mean of the
percent of women on voyages across centuries is statistically different from each other.
Solution 1.B.
The table 1 presents the descriptive statistic of the percent of women on voyages
across the centuries. On an average 29.87% of the people on the voyage were women in the
16th century, 28.87% of the people on the voyage were women in the 17th century and 18.34%
of the people on the voyage were women in the 18th century.
Solution 1.C.
In table 1, the column partial eta squared is a measure of the effect size. The value of
the partial eta squared is 0.090. This indicates the proportion if the variance in the variable
called womrat1 (the percent of women on voyages) and the proportion of the variance is
explained by the variable centurydep. So, the variable centurydep can explain the 9% of
variance in the percent of women on voyages.