Assignment task 2:
- Provide the complete summary statistics for Market Price ($000) and Age of house (years).
- Describe the shape of the distributions for Market Price ($000) and Age of house (years).
- Test whether the population’s average Market Price ($000) is different from 777.
- Construct a 95% confidence interval for the Market Price ($000), also Interpret the confidence interval.
- Provide an introduction section on the rationale of your model , sample size, and the dependent and independent variables (including their unit of measurement) in this model.
- Plot the dependent variable against each independent variable using scatter plot/dot function in Excel. Examine these scatter plots and correctly assess the strength and the nature of the relationship between the dependent and the independent variables?
- Present the multiple regression model with complete regression summary output in your assignment.
- Provide the simple linear regression data analysis for the market price as the response variable and the Land size in Square meters as the explanatory variable. Write down the least square regression equation and correctly interpret the equation.
- Write a clear interpretation of the slope of the regression line from question 4. You must refer to the variables of interest.
- What is the value of the coefficient of determination for the relationship between the dependent and independent variable from question 4. Interpret this value accurately and in a meaningful way.
- State the 95% confidence interval for the slope coefficient and interpret this interval from question 4.
- Compare the multiple regression model (question 3) and simple linear regression model (question 4) and evaluate the goodness of fit between these two modelling techniques.
- Predict the market price of a house (in $) with a building area of 250 square meters. Explain why your answer is valid.
- By performing an appropriate hypothesis test what decision and conclusion would you draw about the hypothesis that the Land size in Square meters useful in predicting the market price of a house (in $)? Use the data provided to justify your answer, as appropriate. When answering this research question.
- For statistical analysis involving hypothesis testing in this assignment, you are required to: Formulate the null and alternative hypotheses for full model.
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- State your statistical decision using significant value (ߙ) of 5% for this test.
- State your conclusion in this context.
This assignment is due in week 12 by Monday 8pm. Please submit your assignment in Word document with all the working attached that have been done in excel in the main navigation menu in STAT6003. The Learning Facilitator will provide feedback with reference to the criteria below via the Grade Centre in the LMS portal. Feedback can be viewed in My Grades.
The histograms are generated from Insert Tab in Excel. The descriptive statistics shows the values of skewness and kurtosis. The negative value of skewness for price of houses means that the data is skewed to left meaning its left tail is longer while the positive value of skewness for age of house means that the data is skewed to right meaning its right tail would be longer (Remenyi, et al., 2011). Although negative, the skewness value of price of houses is very much closer to 0 (i.e. -0.09) meaning that the data is symmetrical for prices of house. Whereas, the skewness value of +0.4 means that the data is moderately skewed to right.