Problem Description:

www.realestate.com.au/sold is an online real estate appraiser where you can explore, research and share Australian property. Your task is to develop a model to appraise the prices of homes in different suburbs of Melbourne.
You will need to collect information of a sample of 50 houses for a given suburb. Your teacher will provide you with the suburb code. The variables you will need to collect for your analysis are house prices in $000, house size (area in square metres) and number of bedrooms in the house.
To calibrate and predict better housing prices for these models, there will be simple formulas in descriptive statistics, inferential statistics and multiple linear regression formulas to help assist with predicting better housing prices. Note Parts A and Part B both parts using the original data set collected from Realestate. Com.
Your business report must include

1] A Title,

2] An Executive Summary,

3] An Introduction, and

4] Conclusions. 
You must provide table of contents and references.
Part A
1. Collect property data by postcode that includes the variables House prices, Size and number of rooms. Organise the data into a table using EXCEL 
2. Calculate the descriptive statistics for each of the variables (House prices, Size and number of rooms). from the data and display in a table. Show the output from Excel. 
3. Describe each of the variables and write a brief summary. Be sure to comment on the
a) central tendency,
b) variability and
c) shape. 
4. Draw a Histogram and a Frequency polygon graph that displays the distribution of House Prices. Be sure to comment on the shape of distribution. (you need to group the data for this question)
5. Create a box-and-whisker plot for the distribution of House Prices and describe the shape. Is there evidence of outliers in the data? 
6. Which of the central tendencies would best describe the house prices and why? 
7. Estimate the 95% confidence interval for the population mean House Price and interpret your result. Do you have to make any assumptions for the estimation? Explain why?