Your assignment for STAT193 Statistics in Practice covers various tasks involving data analysis using your own unique dataset. It focuses on topics such as variable classification, creating histograms, hypothesis testing, t-tests, ANOVA, and interpreting statistical results.

Here’s a summary of the key tasks:

1. Classify Variables: You are required to classify the variables (e.g., Gender, Age, Ethnicity) into categorical (nominal or ordinal) or numerical (discrete or continuous) and state their possible values or ranges.

2. Weekly Income Analysis:

   • Create a histogram of weekly income and comment on its distribution.
   • Provide a point and interval estimate for the mean income, using a 99% confidence level.
   • Conduct a hypothesis test comparing the mean weekly income of New Zealanders to that of South Koreans.

3. Marital Status and Ethnicity Association: Perform a chi-square test to examine whether there is an association between marital status and ethnicity, using the provided dataset.

4. Qualification Levels and Income: You’ll perform both a two-sample t-test (comparing income between two groups based on education) and an ANOVA to test differences in income among multiple qualification levels.

Would you like assistance with any specific part of this assignment, such as clarifying a method or calculating a test?

5 Related Questions:

1. How do you classify variables as categorical or numerical?
2. What does skewness in a histogram tell you about the distribution?
3. How is a hypothesis test conducted to compare two means?
4. What are the assumptions of an ANOVA test?
5. How do residuals help in validating an ANOVA test?

Tip:

Always include a sketch or graph to visualize data, as this makes your analysis clearer and easier to interpret.