BSTA001 - Business Statistics Group Assignment Answers

This assignment is designed to assist you to achieve the following learning outcomes:

a. develops a capability to apply standard statistical tools in various business decision contexts within a professionally responsible framework

b. locates, selects and analyses relevant data, quantitative analytical techniques and resources to support business decision-making
c. effectively interprets and communicates results of quantitative analyses for business decision-making
d. effectively uses a computer-based data analysis package to critically analyze data
e. communicates business information in writing through informal reports and teamwork
➡ Assignment value: 25%
➡ Group of 3-5 students. The group members must be from the same tutorial. Your tutor will put you in groups in tutorials. If you cannot find any group, let your Lecturer/tutor know ASAP. You are NOT allowed to complete this assignment by yourself or in groups of less than 3 members.

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Q1. Collect and Compute the appropriate descriptive statistics of the “sold house price”, “Sold house land size” and “sold house number of rooms” for the year 2018 ,2019 and 2020 of the suburban selected by your tutor. The descriptive statistics measures include central tendency (mean), variability (standard deviation), Mode, Quartiles, Range, and Interquartile range and Show the infographics (e.g., pie chart, bar chart, etc.) of 2018, 2019 and 2020 data for the following variables:
(a) Sold house price
(b) Sold house land size
(c) Sold house number of rooms


Q2. Based on the descriptive statistics from Q1, briefly comment on the central tendency and variability of three suburbs for 2018, 2019 and 2020.
Combine data from all group members in an Excel spreadsheet and use this collated sample to answer the following questions.

Q3. Choose one suburb and perform the following task from 2019 data: The historical data indicates that high house prices (more than average price; You should have the average house price of each suburb from question 1) are more likely to be associated with land size as compare to low house price (Below average house price). What is the probability of high house price given that the house land size is extended (more than the average land size for the suburb)? What is the probability of low house prices given that the land size is non-extended (Land size below average)? Analyze your collated sample and examine whether it is indeed the case. Show the steps in your analysis (including justification for the choice of techniques used and all calculations) and report your findings clearly and use a probability matrix.

Q4. Choose one suburb and perform the following task from 2018 data It is a common perception that the land size and the number of rooms available influence the house price. (i) Explore the relationship between land size and the house price, (ii) Explore the relationship between an available number of rooms and the house price. Use a simple linear regression model to analyze questions (i) and (ii) and report your findings (including all output from Excel (p-values of independent variables, multiple R, R-squared, physical meaning of coefficient) and interpretation of results. (iii) Use the multiple linear regression model and interpret the result of p-values of independent variables, multiple R, Adjusted R-squared, physical meaning of co-efficient and significance of “f “statistics.

Q5. Choose one suburb and perform the following task from 2019 data: Analyze the frequencies of two variables (House price level and land size) with multiple categories to determine whether the two variables are independent. Conduct a Chi-Square Hypothesis test at 0.05 level to ensure that, house price level and land size are independent. Use the following table for Chi-square test:

Q6. What is the average house price of each selected suburb for 2020 (Use the house price average from question 1 and construct a 95% confidence interval for the average house price for each selected suburb of New South Wales for the year 2020)? Note: The population standard deviation of house prices in New South Wales is $20,000.

Q7. A recent study has claimed that the average house price in New South Wales is $872,934. Use your collected data to test this claim for each selected suburb for the year 2020 (Note: Use the sample statistics from question 1). Note: The population standard deviation of house prices in New South Wales is $20,000. Is there any evidence to suggest that the average house price has changed at a 5% level of significance? Report your findings with clear conclusions and all supporting calculations.

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