Hypothesis Testing Assignment - Statistics Analysis, 2024

This homework assignment focuses on hypothesis testing using real-world datasets. The student performs left and right-tailed hypothesis tests on datasets related to crime statistics and survey responses. The analysis includes calculating p-values, constructing confidence intervals, and making conclusions based on the significance level. The assignment covers topics such as the decline in crime levels, underrepresentation of women in certain professions, and survey scores. The student applies statistical methods to draw inferences and evaluate the validity of null and alternative hypotheses. The assignment explores the application of hypothesis testing in different contexts, providing insights into data analysis and statistical reasoning.

HYPOTHESIS TESTING
STUDENT ID:
[Pick the date]

Part One: Crime Analysis From 2016-17
Step 1:
H0 : μTotal perent change ≥ 0
Ha : μTotal perent change <0
Left tailed hypothesis test
Step 2:
Step 3
99% confidence interval for percent change
Analysis of Results
As the p value for the test is lower than the significance level and thus, null hypothesis will
be rejected and alternative hypothesis will be accepted. Hence, the conclusion can be drawn
that the crime level has decreased over the time. The hypothesised value of 0 is included in
the confidence interval. Hence,, the confidence interval result is in agreement with the
hypothesis test result.
Part Two: Gender Perception in the Workforce
Step 1:
H0 : p ≤ 0.1
Ha : p >0.1
Right tailed hypothesis test
Step 2:
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Analysis of Results
As the p value for the test is lower than the significance level and thus, null hypothesis will
be rejected and alternative hypothesis will be accepted. Hence, it can be concluded that the
underrepresentation of women exceeds by 10%.
The underrepresentation of women is quite severe in certain professions such as electrician,
mechanic, aircraft pilot, maintenance worker, plumber, machinist. However, there are certain
professions where there is overrepresentation of women such as dispatcher, flight attendant,
pharmacist, customer service representative, library assistant. These values do not to skew the
representation of women especially the extreme values on the lower end since these are quite
extreme unlike representation values on the upper end. IN wake of this, it would be
recommended that instead of taking all the fields, selective fields ought to be considered
where the representation problem is believed to be most acute and hence require urgent
intervention.
Part Three: Survey Data/Construct Your Own Hypothesis Test
The hypothesis being considered is whether female respondents like shopping or not. Hence,
it is being tested whether the average score on shopping exceeds 3
Step 1:
H0 : μ≤ 3
Ha : μ>3
Right tailed hypothesis test
Step 2 & Step 3:
3

Analysis of Results
The objective of the hypothesis testing was to check if average score for all female
population with regards to shopping would exceed3 or not. The null hypothesis assumed that
this score does not exceed 3 while the opposite was assumed by the alternative hypothesis.
The t statistic has been computed as 7.797 with a p value of 0.000. As the p value for the
right hypothesis test is lower than the significance level and thus, null hypothesis will be
rejected and alternative hypothesis will be accepted. Hence, it can be concluded that survey
score is higher than 3. In terms of population the appropriate set would comprise of all
females in the age group of 15-30 years.
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