TASK 1: LOCATE AND SELECT DATA

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, 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

The sample size should be at least 30 for each year (2018,2019,2020) for each suburb. So, for one suburb, the total at least the number of houses recorded should be 90 for three years period.

Q2. Based on the descriptive statistics from Q1, briefly comment on central tendency and variability of three suburban for the 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 the high house price (more than average price; You should have the average house price of each suburb from question 1) are more likely to 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 average land size for the suburb)? What is the probability of low house price 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 choice of techniques used and all calculations) and report your findings clearly and use 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 available number of rooms and the house price. Use simple linear regression model to analyze question (i) and (ii) and report your findings (including all output from Excel (p-values of independent variables, multiple R, R-squared, physical meaning of co-efficient) 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 Chi-Square Hypothesis test at 0.05 level to ensure that, whether house price level and land size are independent. Use the following table for Chi – square test: