STATISTICAL ANALYSIS

Data Analysis Project – Part B

Part 3 - Further statistical inference (18 marks – 6 marks per question)

Topics 8 – 1 0 covered: ANOVA / Chi-Square Tests / Non-parametric statistics

1. Is there a difference in house prices over the four periods (March, June, September, and December)?
2. Is house price (high, medium, low) independent of time period in June 2006?
   House prices are defined as
   
3. For June 2006 is there a difference between the medians of the two rent options (that is, between the rents of two-bedroom units and the rents of separate houses)?

Suggestions:

• Perform appropriate hypothesis tests to answer the above questions.

• Justify your choice of test.

• Mention any assumptions you must make, and also any concerns about the validity of these. If you doubt the validity of your assumptions, you may need to extend your approach to statistical methods which haven’t been explicitly covered in your course, but are a natural extension of those that we have addressed. Any method that you do choose to utilise will be covered in your text, and will be actionable using Excel (either within the standard Data Analysis option, or the added Data Analysis Plus option).

• Make sure you write a conclusion to your hypothesis tests.

Part 4 – Regression and Correlation (12 marks)

Topic 11 covered: Simple linear regression and correlation

1. For June 2006, what is the relationship between the two-bedroom unit rents (in $) and house prices (in $’000s)? In particular, if two-bedroom units are renting for $350 per week, what would you predict the price of houses in the same LGA to be?

Use rent to predict house price – therefore rent is the dependent variable

Assume various conditions have been met

Suggestions:

• Plot your data graphically and calculate the least squares regression line, correlation coefficient and coefficient of determination.

• Comment on the graph and the statistics.

• If appropriate, construct a suitable interval as an answer to a question, if not explain why not.

• Ignore any regions that do not have data for both two-bedroom unit rents and house prices.

• From the graph is there a relationship between the two? Comment on strength, shape, positive/negative etc. Is the relationship what you would expect?

• What do the gradient and the intercept of the least squares regression line represent?

• What do the values of correlation coefficient and coefficient of determination tell you? Are these values what you expected from your graph? Discuss.

• Mention any assumptions you must make, and also any concerns about the validity of these.

• Make sure you interpret your interval.

Price: $21.17

Solution: The downloadable solution consists of 13 pages, 817 words and 15 charts.
Deliverable: Word Document