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. (3 Marks) 2. Run a simple linear regression using the House prices and the size data and a) Interpret the coefficients. b) Show the output from Excel including a scatter plot. (3 Marks) 3. What is the value of correlation coefficient? Interpret the correlation coefficient. (2 Marks) 4. Is the coefficient estimate for the Size statistically 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. Interpret the coefficient estimate of the slope. (2 Marks)
ECON1274/1248 Business Statistics Group project Sem 2 2018 ECON 1274 /1248– BUSINESS STATISTICS Assessment Task Two – Group PROJECT Project Guideline: This is a group assignment with a minimum group size of two and a maximum group size of four. All group members must be enrolled in the same lecture class. The assignment must be provided in the form of a (brief) business report approximately 8-10 pages (including the cover page). The structure of your (brief) business report must include 1] A Title, 2] An Executive Summary, 3] An Introduction, and 4] Conclusions. You must submit an electronic copy of your assignment in Canvas. Hard copies will not be accepted. SHOW YOUR WORK for calculation based questions. This assignment requires the use of Microsoft Excel. If you have Windows, you will also need to use the Data Analysis ToolPak. INSTRUCTIONS TO STUDENTS 1. Due date: Stage 1 : Part A is due Week 8. via Turnitin Stage 2: Part A and Part B by end of week 13. via Turnitin Final Submission: In-class interview week 15. 2. Lodgement: This project must be submitted via Turnitin together with the assignment cover page. One submission per team is required. You need to also submit a copy of EXCEL data analysis file. A hardcopy of the project should be submitted to your lecturer. You must submit to your lecturer in person during class time two other forms by end of Week 4, Friday 27th July 2018: a. Team submission form. b. Equity of contribution form. Both forms as well as the assignment cover page can be accessed from the following subdirectory on Canvas Each student within a team may be awarded different result for this piece of assessment based on the performances of final in-class interview. You are advised to retain a copy of your project. 3. Penalty for lateness Late submissions will be penalised at a rate of 10% of the overall mark per day. 4. Table of contents and referencing Your project must provide a table of contents, references and any appendices, if required. These do not count towards your word limit. Students are required to acknowledge all sources of information and to include a bibliography of cited texts. For guidelines on referencing, see a document on canvas titled, “Guidelines for Referencing.” Note that failure to acknowledge sources and to properly reference information will result in the material not be included in your assessment or a mark deduction for the question. Students are to use their own words to demonstrate understanding of the Statistic theory and its application. ECON1274/1248 Business Statistics Group project Sem 2 2018 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. (1 ½ mark) You must provide table of contents and references. (½ mark) 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 marks) 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. (1 mark) 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. (3 Marks) 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) (3 marks) 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? (3 Marks) 6. Which of the central tendencies would best describe the house prices and why? (2 marks) 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? (3 Marks) http://www.realestate.com.au/sold ECON1274/1248 Business Statistics Group project Sem 2 2018 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. (3 Marks) 2. Run a simple linear regression using the House prices and the size data and a) Interpret the coefficients. b) Show the output from Excel including a scatter plot. (3 Marks) 3. What is the value of correlation coefficient? Interpret the correlation coefficient. (2 Marks) 4. Is the coefficient estimate for the Size statistically 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. Interpret the coefficient estimate of the slope. (2 Marks) 5. Run a multiple linear regression using the House prices, size and number of bedrooms data. Show the output from Excel. (1 Mark) 6. Set up the multiple regression equation. (1 mark) 7. Interpret the slope coefficient estimates. Discuss whether the signs are what you are expecting and explain your reasoning. (2 Marks) 8. Interpret the value of the Adjusted R2. Is there a large difference between the R2 and the Adjusted R2? If so, what may explain the reasoning for this? (2 Marks) 9. Is the overall model/equation statistically significant at the 5% level of significance? Use the value of significance-F for testing. (2 Marks)