Statistics for economics

Prepare a report that addresses the following:
1. Use numerical descriptive measures to summarize the characteristics of the houses in the data (i.e., age, number of rooms, number of bathrooms, selling price).

2. Use graphical representation to summarise the characteristics of the houses in the data.

3. Define a house as “new” if it has less than 50 years of age, and “old” if it has 50 or more years of age. When you consider the population of houses that this data is selected from, is there evidence that the average number of rooms is statistically different from each other in the “new” and “old” houses?

4. Is there statistical evidence that the average price of houses with one bathroom is different
than the average price of houses with more than one bathroom?

5. Estimate a regression model with house selling price as the dependent variable and the age of the house, number of rooms, and number of bathrooms as explanatory variables. Comment on the impact of each of these explanatory variables on house prices.

Criteria for Assessment
See above for detailed assessment criteria for each question. In addition, note the following criteria:
1. Your work must be well presented, using Microsoft Word (use Insert: Equation to add equations and variables) and Microsoft Excel where appropriate.
2. Marks will be deducted if the work is not well organized or untidy.
3. You must provide FULL explanations and details to obtain full marks.
This assignment is designed to assess learning outcomes:
1. Construct and interpret descriptive statistics by making appropriate use of software packages such as Microsoft Excel.
2. Explain the basic concepts of statistical inference and be able to construct confidence intervals and correctly perform hypotheses tests using data.
3. Demonstrate basic understanding of linear regression, and be able to perform regression analysis to estimate economic parameters using real–world data.