Help needed with this assignment, I have attached all the documents thanks very much.

Marketer Hours of Training Sales Revenue 3 157342 WO N P 6 106531 4 79616 3 169001 8 151869 2 137902 154489 10 64666 1 U 99506 10 5 100932 11 8 92002 12 3 143320 13 104003 14 5 43962 15 3 74106 16 173353 17 12 80360 18 6 99572 19 4 141900 20 4 59033 21 8 122907 22 6 153182 23 9 94736 24 10 121728 25 4 87223 26 3 103910 27 12 174544 28 9 203131 29 5 65773 30 7 104493 31 6 102172 32 131855 33 8 65997 34 6 126796 35 7 94582 36 3 109534 37 11 83385 38 10 57245 39 5 87777 40 5 90605 41 3 121771 42 4 136043In this assignment you are required to use the relevant built-in function in Excel to estimate a simple linear regression model. As essential preparation for this assignment you should have worked through the computing exercise sets. Suppose the managers of a telemarketing company are interested in the relationship between the following two variables: 0 The sales revenue in dollars {say Y) generated by a telemarketer in his/her first year of completed service. 0 The number of hours of preliminary training provided to a new telemarketer (say )3. Using a random sample of data for 42 telemarketers that recently completed their rst year of service with the company, you are required to estimate a conditional expectation function of the following form by least squares regression using the Microsoft Excel regression tool. E(Y|X)=B1+BzX To generate your own personalised data set you will need to follow the steps below. 1. Open the 'Assignment Data Generation File' attachment in the 'Computing Assignment' link on the left hand menu of the vUWS site for this unit. If the Excel le opens in 'Protected View', just click on 'Enable Editing' before undertaking the following steps. 2. Once you have opened the Data Generation File in Excel, you should enter the last four digits of your student number in the range of cells E2 to H2, Q with the fth digit in E2, the sixth digit in F2, the seventh digit in G2, and the eighth digit in H2. This will generate your personalised data set in the range A1:C43 (with the headings 'Marketer', 'Hours of Training' and 'Sales Revenue' in A1, B1 and C1, respectively). Note that the marker of your assignment will be able to check that you use the correct data set corresponding to your student number. 3. Open a new m Excel workbook and copy the range A1:C43 containing your data set in the Data Generation File to the new workbook. Close the Data Generation File, then give your new Excel workbook a name and save it on your computer or storage medium (memory stick, etc.). Apart from entering the last four digits of your student number and copying your generated data, you will not be able to edit the Data Generation File. Each student is required to submit in M Word document format (at the end of Week 13 to hisfher tutor): 0 Main Report: Answers to parts (b) to (e). o Annexure: A softcopy of hisfher part (a) (see below) tabulated regression results in including a copy of the data set used and the summary results table from using the built-in regression tool in Excel. Students are not required to submit any list of residuals, residual p_l_9_t_s_ or line t plots. You must submit your assignment with an assignment coversheet. The assignment coversheet is also available in the 'Computing Assignment' link on the unit webpage. (a) Use the built regression tool in Excel and your personalized data set (see above) to estimate the simple regression of sales revenue in dollars (Y) generated by a telemarketer in his/her first year of completed service on the number of hours of preliminary training provided to a new telemarketer (X). (2 marks) When answering the following questions, assume all the assumptions of the neoclassical (stochastic regressor) simple regression (NSR) model with multivariate normally distributed random disturbances are satised. (b) Clearly state your estimated conditional expectation function (sample regression line). Note that you do not need to estimate your equation manually, but rather you should simply write down your sample regression line using the estimated intercept and coefcient of X given in your summary regression output from Excel. (1 mark) (c) With reference to your estimated equation, calculate (using a calculator) a 90% condence interval for the coefcient of X (132 ) in the model. In performing this calculation, use the relevant estimated standard error of the estimator of the coefcient of X given in your summary Excel regression output. Give an interpretation of the condence interval you calculate. (2 marks) (d) Again with reference to your estimated equation, perform a test of the null hypothesis that the coefcient of number of hours of preliminary training provided to a telemarketer (B2) equals zero against the alternative that it is greater than zero, using the d = 0.05 (i.e. 5%) level of signicance. In presenting your answer to this question you are required to use the 6-step hypothesis testing procedure given in the unit summary lecture notes. Again in answering this question, you should use the relevant estimated standard error of the estimator of the coefficient of X given in your summary Excel regression output. (3 marks) (e) Give an interpretation of the realized coefficient of determination value (r ) given in your summary Excel regression output. (2 marks)