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ECON1274 Business Statistics

Question

Answered

Questions:

Problem Description:

You have just started work for a real estate company as a data analyst. Your manager has asked you to look at www.realestate.com.au/sold, an online real estate appraiser where you can explore, research and share information on Australian property. She then asks you to develop a model to appraise the prices of homes in one suburb of Melbourne, their main sales area, and write a short business report on the trends and your conclusions. She explains that the real estate company is very multi-cultural, as are the people in the suburbs it serves, so you will have to explain your conclusions in a way that is accessible to them.

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 are provided to assist you with predicting better housing prices.

Part A:

  1. Collect property data by postcode that includes the variables House prices, Sizeand number of rooms. Organise the data into a table using EXCEL
  2. Calculate the descriptive statistics for each of the variables (House prices, Sizeand number of rooms). from the data and display in a table. Show the output from Excel.
  1. Describe each of the variables and write a brief summary. Be sure to comment on the
  1. central tendency,
  2. variability and
  3. c)  shape.
  1. 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 groupthe data for this question)
  1. Create a box-and-whisker plot for the distribution of House Pricesand describe the shape. Is there evidence of outliers in the data? List the outliers if you there are any.
  1. Which of the central tendencies would best describe the house pricesand why?
  2. Estimate the 95% confidence interval for the population mean House Priceand interpret your result. Do you have to make any assumptions for the estimation? Explain why?

Part B:

  1. Your real estate agent recently stated that houses in the suburb typically had an average price around 1200 ($000), but have recently changed. Test his claim at the 5% level of significance. Show all your calculations.
  1. Run a simple linear regression using the House pricesand the sizedata and

a)  Show the output from Excel and

b)  Set up the linear regression equation

c)  Interpret the coefficients

3.  Draw a scatter plot

  1. What is the value of correlation coefficient? Interpret the correlation coefficient.
  1. Is the coefficient estimate for the Sizestatistically different than zero at the 5% level of significance? Set-up the correct hypothesis test using the results found in the table in question 2 using both the critical value and p-value approach.
  1. Run a multiple linear regression using the House prices, size and number ofbedrooms Show the output from Excel.
  2. Set up the multiple regression equation.
  1. Interpret the slope coefficient estimates. Discuss whether the signs are what you are expecting and explain your reasoning.
  1. Interpret the value of the Adjusted R2. Is there a large difference between the R2and the  Adjusted  R2?  If  so,  what  may  explain  the  reasoning  for  this?
  1. Is the overall model/equationstatistically significant at the 5% level of significance? Use the value of significance-F for testing.
  1. Test each of the slopes individually at the 5% level of significance. Based on the results of the regressions, what other factors would have influenced the Property prices?

Provide a couple possible examples and indicate their predicted relationship with the review score if they were included. Use the p-value approach for testing.

  1. Predict the average price of a property with a sizeof 600 square meters and has 3 bedrooms. Show the predicted regression equation.
  1. Complete the micro-credential: Cross-cultural Communication.
  1. Combine PART A and B : Combine Stage 1 and Stage 2 . Write a market appraisalof outlining what agents can confidently recommend investors buying/selling property in your suburb. Write your findings in a brief business report that includes:
  • a title
  • table of contents
  • introduction
  • data analysis
  • trends and conclusions
  1. Write a reflection on how you structured / presented the information so that it was suitable for a multicultural, possibly multilingual audience (using knowledge learned in the micro-credential).

 

 

 

 

 

 

ECON1274 Business Statistics

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