Hypothesis Testing in Statistics

STATISTICS
HYPOTHESIS TESTING
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1

Test 1: Hypothesis testing
Step 1: The developed hypotheses are as shown:
Hypothesis 1: The number of visits to a medical doctor in the past 6 months caused by fights,
conflicts, arguments, or physical attacks is equal to the number of visits not caused by the same.
Hypothesis 2: There is no difference between the group of the number of visits to a medical
doctor in the past 6 months caused by fights, conflicts, arguments, or physical attacks and the
group of the number of visits not caused by the same.
Step 2: Key Assumptions
The assumptions made for data used in the test were that the dependent variable was continuous
while the independent variable had two categorical groups. Other assumptions made were that
there were no significant outliers, there was the observation of independence between the two
groups, the dependent variable was normally distributed for the two groups and that there were
no significant outliers.
Step 3: Tests used
To evaluate the first hypothesis, an independent t-test was used since it is appropriate in
comparing the means between two unrelated groups on the same dependent variable. In
hypothesis two, a one-way ANOVA test was used since it is used in determining if there are any
statistically significant differences between two unrelated groups.
Step 4: Results

The output of the t-test was that the p-value of the independent sample t-test was 0.888 since the
Levene’s test had a F value of 0.313 and a significance of greater than 0.05 (equal variances
assumed) as shown below.
Table 1: Independent Sample Test
The output of the one-way ANOVA carried out had an F significance (F (1, 66)) of 0.20 with a
p-value of 0.888 as shown below.
Table 2: ANOVA
Step 5: Decision