The requirement for this paper and the excel will be provide, and i’ll upload two file named “computer lab”, which is the tutorial for how to do this paper. please have a look on this two file before you start.
Using Excel, compute the descriptive statistics (mean, max, min, variance) for the variable “LIFESAT” for the following below.
i) Males and Females
ii) Those who live alone vs. those who don’t live alone.
iii) Those in income category 1 vs. those in income category 6.
Briefly discuss any important differences between the results in each group. Do the differences accord with your a priori expectations? Explain.
Estimate the following population regression functions using Ordinary Least Squares (OLS).
For each part, present your estimated sample regression function and briefly discuss whether or not was different to what you had expected?
Estimate the following multiple regression model:
Carefully present your estimated sample regression function and interpret each of your regression coefficients.
i) For a hypothetical male who is aged 26, has no medical condition, lives alone and makes $75,000 per year working 50 hours per week, estimate their life satisfaction score based on your results from Part (C).
ii) If the person in part i) got married and moved in with his wife at aged 35, what would his life satisfaction score be now given everything else was the same?
Please show all your calculations.
Looking at the population regression function specified in Part (C) what other variables do you think can be used in this model to explain life satisfaction. Justify your choice of variables.
Calculate the sum of squared residuals for the estimated multiple regression model in Part (C).
Choose some other estimator or make up any other set of estimates for your coefficients (i.e. change ̂ ̂ ̂ ̂ ̂ ̂ and ̂ ). Re-calculate the new sum of squared residuals based on your new coefficients.
What can you conclude about the original sum of squared residuals and the new sum of squared residuals?
Discuss the statistical significance of each estimated coefficient in the multiple regression model for Part (C). Comment on the overall significance of the model. Show your calculations/workings for all the tests involved in this question.
Notes: This is an individual assignment. All Excel worksheets excluding the original data should be attached at the end of your submitted hard copy assignment. These should clearly demonstrate the work undertaken independently by each student. Submissions should be made both in hardcopy (report only) and online on D2L (report and excel files). On-campus students must submit to the campus specific faculty office while the off campus students should mail the assignments to the Division of Student Affairs (DSA) or contact DSA for submissions (visit http://www.deakin.edu.au/current-students/study-information/exams-assessment/assignments.php).
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