MAT10251 STATISTICAL ANALYSIS PROJECT
This project leads you through a statistical analysis of residential property data from a given non-capital city or town in Australia.
The data for this project was obtained from http://www.realestate.com.au/buy during January 2020.
Part A covers parts of Topics 1 and 2, Part B parts of Topics 5 to 9.
MAT10251 STATISTICAL
You will need to work on this project throughout Session 1.
Project Data
The data for this project can be accessed from the MySCU site for MAT10251 in Task 2 – Project in Assessment Tasks and Submission under ASSESSMENT.
The data set provided contains 10 randomly chosen samples of size 100.
To obtain your data
(1) Click on the Project Data file. This will download an Excel file.
(2) Select the 4 columns (Price $000 to Type) of data for the sample specified by the last digit of your student ID number.
(3) Copy this into a new Excel file.
There are 10 sample data sets each of four (4) columns (Price $000 to Type)
Your sample number matches the last digit of your SCU student ID number. For example, if your student ID number ends in 2 your sample is Sample 2 and you will be analyzing residential property data from Gold Coast Queensland in columns K to N and cells K2:N102.
Project Situation
Your statistical analysis of residential property data is to enable you to answer questions from a relative who is seeking to buy a property in the particular town or city of your sample and has asked you for information and advice.
In each part of the project, you are required to analyze your sample data in response to given questions and provide a written answer. You can assume that each written answer is a part of a letter or email to your relative.
Project Preparation MAT10251 STATISTICAL ANALYSIS PROJECT
You are expected to use Excel when completing the project.
Your written answers presenting findings and conclusions should be considered as a part of a letter or email to your relative. Each written answer should be a word document into which your Excel output has been copied.
In addition, your statistical workings for Part B should appear as appendices to your written answer. This should include all necessary steps and appropriate Excel output.
Each part of the project should be submitted as a SINGLE Word document, with appropriate Excel output added.
Note:
- You should not need to read beyond the study guide and textbook to complete the project.
Project Submission
- Each part of the project should be submitted as a SINGLE Word file with Excel output.
- The given cover sheets should be the first pages of your submitted project and are not part of the page limit.
- DO NOT submit your appendices, which are not part of the page or word limit, for Part B as a separate file.
- Ensure that the page setup of your submitted document is A4 Portrait, with an appropriate format so that it is easily readable if printed.
- Use line spacing of at least 1.5.
- Please name your file
“Family Name_First Name_Part_A/B/_Campus”
For example; Jayne_Nicola_Part_A_Lismore
Penalties For Incorrect Sample MAT10251 STATISTICAL ANALYSIS PROJECT
- If you use a sample that does not correspond to the last digit of your student ID number, to be entered on the cover sheet, a maximum of two marks may be deducted, as this causes the marker extra work and frustration.
Incorrect Format
- If the page setup of your submitted Word file is not as required (that is, A4 Portrait, with the appropriate format so that it is easily readable if printed), with at least 1.5 line spacing or your project is not submitted as a single Word document a maximum of two marks may be deducted, as this causes the marker extra work and frustration.
- If your submitted file is not a Word file, for example, it is a pdf or a zip file, a maximum of two marks may be deducted, as this causes the marker extra work and frustration.
- In addition, if your file is not named as requested or the required cover sheets are not included or correctly completed a maximum of two marks may also be deducted, as this can cause the marker extra work and frustration.
MAT10251 STATISTICAL ANALYSIS
PROJECT – PART A
Due Week 4 Tuesday 24 March 202
If you are a late enrolment in MAT10251, email Nicola Jayne nicola.jayne@scu.edu.au with the date you enrolled in MAT10251 for a revised due date
Value: 10%
Objectives: 1 to 5
Topics: 1 and 2
Purpose: To
- introduce you to the project data, situation and Excel
- use Excel to graph data and calculate statistics
- interpret and communicate Excel results
Part A Preliminary Analysis of Sample Data
Your relative is interested in buying a property in the town or city specified by your sample and asks you to obtain information on the property prices in this location.
Your relative is considering purchasing a two or three-bedroom property, as they are either downsizing since their children have left home or they are new home buyers. Therefore, they are interested in the typical price of two and three-bedroom properties. They are also interested in the difference in price between units and houses and the relationship between a number of bedrooms and price. myscu
Tasks – Part A Submission
Complete the following
1) Download and save your data.
2) Download the Project Part A cover sheets, name and save this file as
“Family Name_First Name_Part_A_Campus”
3) Enter your Sample Number on page 2 of the Part A coversheets.
4) Statistical Output: For your sample perform the following tasks:
- Price of two and three-bedroom properties
Use Price $000 (1st column of data) for two and three-bedroom residential properties for sale to explore the typical price of a two or three-bedroom residential property, by using Excel to:
- Construct a frequency histogram or polygon for the price of two and three-bedroom residential properties.
- Calculate descriptive statistics for the price of two and three-bedroom residential properties.
Notes:
- The required data for two and three-bedroom residential properties are in the first rows of your sample.
- Analyze the price of two and three-bedroom properties together. Do NOT separate into two or three bedrooms or into units or houses.
b) Difference between unit and house prices
Use Price $000 (1st column of data) and Type (4th column of data) for all 100 residential properties for sale to explore the difference between unit and house prices, by using Excel to:
- Construct separate boxplots, on the same plot or separately, for house prices and for unit prices.
Hint: Sort data on Type to obtain two samples. One for house prices and the other for unit prices.
c) Relationship between the number of bedrooms and price
Explore the relationship between the number of bedrooms and price using Number of Bedrooms (2nd column of data) as the independent variable and Price $000 (1st column of data) as the dependent variable for all 100 properties by using Excel to:
- Construct a scatter plot for the number of bedrooms and price
- Calculate the correlation coefficient for the number of bedrooms and price.
5) Written Answer – Email or letter
Using the instructions given on pages 4 and 5 of the Part A coversheets, introduce your data and the results of your preliminary investigation of residential property prices
This should be three to five pages and 400 to 800 words.
Use an appropriate style, without statistical jargon and equations, to clearly communicate your results.
6) Complete Coversheets 1 and 2, save and submit Part A of the project online using Project Part A link in Submit Project by the due date of Tuesday 24 March 2020.
Marking Criteria – Part A
Read the marking criteria carefully and consider them when preparing your Part A Submission.
See the marking and feedback sheet, page 3 Part A coversheets, for allocation of marks.
Statistical Calculations
- To obtain full marks your graphs and plots must be correct, including correct labels on both axes and a title.
Marks will be deducted if:
- Graph or plot incorrect
Examples
- Gaps between classes of non-zero frequency in a histogram for continuous data
- Incorrect independent and dependent variables in a scatter plot.
- Line graph instead of a histogram
- Excel, PhStat, Excel Workbooks, or similar, is not used.
- Axes incorrectly or not labeled.
- No title.
- For a histogram or frequency polygon, inappropriate classes are used.
- The scale on axes distorts graphs.
- To obtain full marks for descriptive statistics copy the output table of the Descriptive Statistics command in Data Analysis or the Descriptive Summary and/or Boxplot command in PhStat or Descriptive workbook. You may delete unnecessary statistics in these tables.
- Marks will be deducted if any descriptive statistics are incorrect, so check:
- Your sample size.
- Whether you are calculating sample statistics or population parameters.
Written Answer – Email or letter
- 400 to 800 words and three to five pages – marks will be deducted if this is greatly exceeded.
- To obtain full marks must:
- Be well structured.
- Clearly communicate the results of the Excel output in language appropriate for your audience.
- Include appropriate graphs and plots with appropriate statistics.
- Provide information on the average/typical price of a two or three-bedroom residential property, how the price of two and three-bedroom residential properties vary, and any pattern to the price of two and three-bedroom residential properties.
- Provide information on the difference in the price of units and houses.
- Provide information on the relationship between the number of bedrooms and the price of residential properties. Comment on the strength, shape, and sign of the relationship.
- Marks will be deducted if:
- There is little or no comment on, or interpretation of, the Excel output.
- Unnecessary statistical jargon and equations appear.
- It is confusing or not readable.
- It is handwritten.
- For each major spelling and/or grammatical error half a mark will be deducted, up to a maximum of two marks.
- Also up to two marks may be deducted for poor structure and/or presentation.
MAT10251 STATISTICAL ANALYSIS
PROJECT – PART B
Due: Week 11 Sunday 17 May 2020
Value: 25%
Objectives: 1 to 5
Topics: 5 to 9
Purpose: To apply your knowledge of statistical inference and regression to answer questions about residential property prices by analysing the data and communicating the results.
Part B Further Analysis of Data – Using Statistical Inference and Regression Analysis
In response to your letter or email in Part A, your relative asks for further information and clarification. You use the graphs and statistics obtained in Part A and techniques from statistical inference and regression and correlation to provide this information.
Part B Submission
You should submit a single word document consisting of:
- Part B coversheets
- Written answer either as a letter or an email or emails. See instructions on page 4 of Part B coversheets
- Appendices for Part B contain full statistical work for the required statistical tasks. This should follow the format given on pages 5 of Part B coversheets
MAT10251 STATISTICAL
Part B Preparation
Graphs and statistics from Part A are required in the statistical and written answers in Part B. Therefore, check these and make any required corrections.
While the submission date for Part B is Sunday 17 May 2020, you should be working on Part B during Weeks 6 to 11.
It is recommended that you follow the following timetable:
- Question 1, covering Topic 5, should be completed in Week 6
- Question 2, covering Topic 6, should be completed in Week 8
- Question 3, covering Topic 7, should be attempted in Week 9
- Question 4, covering Topic 8, should be attempted in Week 10
- Question 5, covering Topic 9, should be attempted in Week 11
Task 1 Part B – Appendices Statistical Inference and Regression and Correlation Tasks (38 marks)
The following statistical tasks should appear as appendices to your written answers. These should include all necessary steps and appropriate Excel output.
These appendices should come after your written answer within your single Word document for Part B.
Statistical Inference
Choose a level of significance for any hypothesis tests and a level of confidence for any confidence intervals. Enter these values on page 2 of the Part B coversheets along with the sample number from Part A.
For your sample answer the following questions using appropriate statistical inference and regression techniques.
Question 1 – Topic 5 (5.5 marks)
Your relative is considering buying a unit which from your previous research you have shown appear to be cheaper than houses. However, your relative is concerned that if they only consider units their choice will be limited.
To explore if their choice will be limited if they restrict their search to units use Type (4th column of your data) for all 100 residential properties for sale and an appropriate statistical inference technique to:
- Estimate the population proportion of residential properties for sale, in the location and state specified by your sample, which is units.
Hint: Sort data on Type to enable you to easily count the number of properties in your sample which are units
Question 2 – Topic 6 (7.5 marks)
Your relative has a maximum of $330,000 to purchase a residential property. If the average price of two or three-bedroom residential properties is more than this your relative will consider the location to be too expensive.
Explore if your relative will find the location specified by your sample too expensive by using Price $000 (1st column of data) for two and three-bedroom residential properties for sale, your output from Part A, and an appropriate statistical inference technique to answer the following question
- In the location specified by your sample, is the mean two and three-bedroom residential property price more than $330,000?
Notes:
- The required data for two and three-bedroom residential properties are in the first rows of your sample
- If you have sorted your data on Type in Question 1 download your data again.
Question 3 Topic 7 (6 marks)
From your previous research, you have shown that units appear to be cheaper than houses. Your relative asks you to estimate how much they would save if they purchased a unit instead of a house.
To provide a justified answer use Price $000 (1st column of data) and Type (4th column of data) for all 100 properties for sale, your output from Part A, and an appropriate statistical inference technique to answer the following question.
- Estimate the mean difference in price between units and houses for sale in the location specified by your sample.
Hint: Sort data on Type to obtain two samples. One for house prices and the other for unit prices.
MAT10251 STATISTICAL
Questions 4 and 5 Simple and Multiple Linear Regression (19 marks)
Your relative asks what factors influence the price of a residential property and if you can estimate the price of residential property from these factors.
To answer this you develop a simple linear regression model to estimate price from the number of bedrooms and a multiple linear regression model to estimate price from the number of bedrooms, a number of bathrooms, and type. Then you choose and interpret the linear model that best fits your data.
Question 4 Simple Linear Regression Model Topic 8
Use Number of Bedrooms (3rd column of data) as the independent variable and Price $000 (1st column of data) as the dependent variable for all 100 properties and your output from Part A to develop and then explore a simple linear relationship between the two variables by:
- Calculating the least-squares regression line, correlation coefficient, and coefficient of determination.
- Interpreting the gradient and vertical intercept of the simple linear regression equation.
- Interpreting the coefficient of determination.
MAT10251 STATISTICAL
Question 5 Multiple Linear Regression Model Topic 9
To explore whether being a house or unit and the number of bathrooms also influences the price, add the Number of Bathrooms (3rd column of data) and Type (4th column of data) as additional independent variables to the simple linear regression model in Question 4. Then develop and explore the relationship between price and the three independent variables by:
- Calculating the multiple regression equation and coefficient of determination.
- Interpreting the values of the multiple regression coefficients.
- Interpreting the value of the coefficient of determination. Compare the value with the corresponding value for the simple linear regression model.
Then determine the best model to estimate price by:
- Using appropriate tests to determine which independent variables make a significant contribution to the regression model.
- Then state or calculate the simple or multiple regression equation which best fits the data.
Notes:
- You may need to transform or manipulate the given data, before using Excel for the corresponding statistical calculations.
- Use Excel for all statistical calculations. You do not need to repeat any Excel calculations by hand. However, make sure that you define your random variables and include any steps not given by Excel. For example, a hypothesis test includes the null and alternative hypotheses, along with the decision to reject or not reject the null hypothesis.
- Mention any assumptions you need to make, where appropriate justify these from Part A output.
- Question 4 fits a linear model even if from your scatter plot you decide that a non-linear relationship better fits the data or that no apparent relationship exists. However, mention this in your written answer and/or the corresponding appendix.
- Comment on why a test or confidence interval has been chosen. Where appropriate include and refer to Part A output.
- Make sure you interpret confidence intervals and write conclusions to hypothesis tests.
Task 2 – Written Answer – Email or letter (12 marks)
For Questions 1, 2, 3, and Questions 4 and 5 combined present the results of your calculations, with your interpretation and conclusions as either a letter or email/emails to your relative.
Use the instructions given on page 4 of the Part B coversheets.
This should be 400 to 900 words and two to five pages.
It should be submitted as a Word file with Excel output included.
Make sure you:
- Introduce each question and put it in context
- Answer each question in non-statistical language.
- Present the result of your calculations and tests without unnecessary statistical jargon
- Include a conclusion which answers the given question.
In particular, for Questions 4 and 5
- Include and justify the best model.
- Discuss and interpret the values of the regression coefficients and coefficient of determination of the best model.
Marking Criteria – Part B
Read these marking criteria carefully and consider them when preparing Part B.
See the marking and feedback sheet, page 3 Part B coversheets, for allocation of marks.
Statistical Calculations
- For statistical inference calculations (Questions 1, 2, 3, and 5) marks will be given for:
- Choice of appropriate statistical technique/s.
- Random variable/s defined.
- Correct hypotheses for tests.
- Correct Excel output.
- Correct interpretation of results.
- For regression coefficients and coefficient of determination (Questions 4 and 5) use either:
- The Regression command in Data Analysis and copy resultant tables.
- Or the simple/multiple regression command in PhStat and copy the resultant tables.
- Or the Simple Linear and Multiple Regression workbooks and copy the resultant tables.
- For regression coefficients and coefficient of determination (Questions 4 and 5) marks will be deducted if Excel is not used and also for incorrect equations or coefficients, so check:
- Your independent and dependent variables.
- Your sample size.
MAT10251 STATISTICAL
Written Answer – Email/Emails or Letter
- 400 to 900 words and two to five pages – marks will be deducted if this is greatly exceeded.
- To obtain full marks must:
- Be well structured and analyzed
- Clearly communicate the results of the Excel output in language appropriate for your audience
- Include an introduction to each question and a conclusion
- Include appropriate Excel output
- Answer the questions in non-statistical language.
- Marks will be deducted if:
- There is little or no comment on, or interpretation of, the Excel output
- Unnecessary statistical jargon and equations appear
- It is confusing or not readable
- For each major spelling and/or grammatical error half a mark will be deducted, up to a maximum of two marks
- Also up to two marks may be deducted for poor structure and presentation.
- For Questions 1 to 3, and Questions 4 and 5 combined in (), the following rubric will be used
| Mark | Acceptable | |
| Poor | 0 (0) | Question not introduced and/or results not presented. Confused response. Incorrect and/or inconsistent comments and conclusions. Unnecessary statistical jargon, especially symbols, equations, and definitions (copied from the textbook) Question unanswered. |
| Acceptable | 1 (2) | Question introduced and results presented. Minimal interpretation and/or conclusions on how to use the information and/or only minimally relates information obtained to residential property prices. Only minor errors and inconsistencies in comments and conclusions. Question answered. |
| More than acceptable | 2 (4) | Results presented and questions introduced and answered, clearly and concisely. Includes interpretation and/or conclusions on how to use the information and/or relates information obtained to residential property prices. No errors or inconsistencies in comments and conclusions. Questions answered and justified |
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