Question

URGENT PLEASE HELP!

The director of a training program for a large insurance company has the business objective of determining which training method is best for training underwriters. The three methods to be evaluated are​ classroom, online, and courseware app. The 30 trainees are divided into three randomly assigned groups of 10. Before the start of the​ training, each trainee is given a proficiency exam that measures mathematics and computer skills. At the end of the​ training, all students take the same​ end-of-training exam. Develop a multiple regression model to predict the score on the​ end-of-training exam, based on the score on the proficiency exam and the method of training used. Complete parts a through f below.

THE BLANKS ARE JUST "INCREASE" OR "DECREASE"

Data Table 1 End of Proficiency Method Training 13 19 17 classroom classroom classroom classroom classroom classroom classroom classroom classroom 95 98 100 103 106 108 39 26 41 27 37 130 81 classroom online online online online online online online online online online courseware app courseware app courseware app courseware app courseware app courseware app courseware app 37 35 42 89 97 97 112 115 119 120 119 92 97 63 93 74 75 79 53 101 102 105 106 51 35 45 courseware app courseware app courseware app 112 119 43 81 Print Done otherwise. Define the dummy variable X3 as X31 if the training method is online, X3 0 otherwise Зі Round to three decimal places as needed.) b. Interpret the regression coefficients in (a) Taking into account the effect of the training method, for each additional point scored on the proficiency exam, the predicted end-of-training exam score is estimated to by points. Holding constant the score on the proficiency exam, the estimated effect of an underwriter being trained by the classroom the end-oaf raining exam score bypoints. Holding constant the score on method rather than the courseware app method or the online method is to the proficiency exam, the estimated effect of an underwriter being trained by the online method rather than the courseware app method or the classroom method is the end-of-training exam score bypoints. to the end-of-training exam score by points. to (Round to three decimal places as needed.) c. At the 0.05 level of significance, determine whether each independent variable makes a contribution to the regression model. Determine the hypotheses. Choose the correct answer below. H1: At least one of the coefficients are not 0. Find the t statistic for β1 . t statistic(Round to two decimal places as needed.) Find the probability of getting a t statistic at least this extreme. p-value (Round to three decimal places as needed.) Does this variable make a contribution to the regression model? Choose the correct answer below. O A. No, because the p-value is less than the significance level 0 B. Yes, because the p-value is less than the significance level. ° C. No, because the p-value is greater than the significance level. 0 D. Yes, because the p-value is greater than the significance level Find the t statistic for p2 t statistic (Round to two decimal places as needed.) Find the probability of getting a t statistic at least this extreme. p-value(Round to three decimal places as needed.) Does this variable make a contribution to the regression model? Choose the correct answer below. O A. No, because the p-value is less than the significance level. ( B. Yes, because the p-value is less than the significance level. C. No, because the p-value is greater than the significance level. D. Yes, because the p-value is greater than the significance level. Find the t statistic for B3. statistic(Round to two decimal places as needed.) Find the probability of getting a t statistic at least this extreme. p-value-(Round to three decimal places as needed.)

Answer 1

(a)

y	X1	X2	X3
14	94	1	0
18	96	1	0
18	97	1	0
39	101	1	0
40	101	1	0
26	105	1	0
41	110	1	0
28	110	1	0
36	111	1	0
65	130	1	0
37	79	0	1
35	85	0	1
43	90	0	1
44	97	0	1
61	97	0	1
62	112	0	1
93	115	0	1
74	117	0	1
76	120	0	1
79	119	0	1
55	92	0	0
53	95	0	0
54	100	0	0
52	102	0	0
34	102	0	0
47	104	0	0
57	106	0	0
55	109	0	0
41	111	0	0
80	117	0	0

(b) using software the regression alalysis showed following information

Analysis of Variance
Source	DF	Sum of	Mean	F Value	Pr > F
		Squares	Square
Model	3	8689.38517	2896.46	30.91	<.0001
Error	26	2435.98149	93.6916
Corrected Total	29	11125
Root MSE	9.67944	R-Square	0.781
Dependent Mean	48.56667	Adj R-Sq	0.7558
Coeff Var	19.93022
Parameter Estimates
Variable	DF	Parameter	Standard	t Value	Pr > |t|
		Estimate	Error
Intercept	1	-63.47383	17.0023	-3.73	0.0009
X1	1	1.12017	0.16112	6.95	<.0001
X2	1	-22.20429	4.33744	-5.12	<.0001
X3	1	8.38412	4.33025	1.94	0.0638

regression equation y=-63.47+1.12X1-22.2X2+8.38X3

(b and c) X1 has significant positive impact and X2 has significant negative impact, X3 has non-significant positive impact at 5% level of significance

(d) (1-alpha)*100% confidence interval for beta=beta±t(alpha/2,error df)*SE(beta)

95% confidence interval for X1=1.12±t(0.05/2, 26)*0.1611=1.12±2.06*0.1611=1.12±0.33=(0.79,1.55)

95% confidence interval for X2=-22.2±t(0.05/2, 26)*4.34=-22.2±2.06*4.34=

95% confidence interval for X3=8.38±t(0.05/2, 26)*4.33=1.12±2.06*4.33

(e) after adding the interaction term the following information is generated, and none of the interaction term is significant at alpha=0.05 so adding interaction term is not required

Analysis of Variance
Source	DF	Sum of	Mean	F Value	Pr > F
		Squares	Square
Model	5	8847.69985	1769.54	18.65	<.0001
Error	24	2277.66682	94.90278
Corrected Total	29	11125
Root MSE	9.74181	R-Square	0.7953
Dependent Mean	48.56667	Adj R-Sq	0.7526
Coeff Var	20.05863
Parameter Estimates
Variable	DF	Parameter	Standard	t Value	Pr > |t|
		Estimate	Error
Intercept	1	-9.32082	45.52686	-0.2	0.8395
X1	1	0.59847	0.4376	1.37	0.1841
X2	1	-88.94048	55.9612	-1.59	0.1251
X3	1	-52.5468	50.60616	-1.04	0.3095
X12	1	0.64098	0.53458	1.2	0.2422
X13	1	0.58745	0.48635	1.21	0.2389

X12 is interaction of X1 and X2

X13 iis interaction of X1 and X2

( f) first model is appropriate i.e. without interaction model

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