Question

You may need to use The American Association of Individual investors (AAR) On-Line Discount Broker Survey polis members on their experiences with discount brokers. As part of the survey, members were asked to rate the quality of the speed of execution with their broker as well as provide an overall satisfaction rating for electronk trades. Possible responses (scores) were no opinion (0), unsatisfied (1), somewhat satisfied (2), satisfied (3). and very satisfied (4). For each broker suvery scores were computed by calculating a weighted average of the scores provided by each respondent. A portion of the survey results follow. Brokerage Speed Satisfaction Scottrade, Inc. 3.3 Charles Schwab 3.4 3.9 Fidelity Brokerage Services 3.6 3.7 TD Ameritrade 3.2 2.9 E*Trade Financial 3.8 2.8 Vanguard Brokerage Services 3.8 3.6 USAA Brokerage Services Thinkerswim 2.6 2.6 2.7 2.3 Wells Fargo Investments 4.0 4.0 Interactive Brokers 2.5 2.5 Zecco.com These ratings data on x = the quality of the speed of execution and yoverall satisfaction with electronic trades provided the estimated regression equation = 0.205 +0.908x. At the 0.05 level of significance, test whether speed of execution and overall satisfaction are relat (Use the Ftest.) State the null and alternative hypotheses. 0 Ho: P₂ 20 O Ho: Pono H₂: Bo=0 O Ho: B0 H: A-0 O Moi Bo=0 H₂: Poo O Ho: PO H₂ B 0 Set up the ANOVA table. (Round your for F to two decimal places and all other values to three decimal places.) Source of Variation p-value Sum of Squares Degrees of Freedom Mean Square Regression

please help

Answer 1

Solution

we will solve it by using excel and the steps are

Enter the Data into excel

Click on Data tab

Click on Data Analysis

Select Regression

Select input Y Range as Range of dependent variable.

Select Input X Range as Range of independent variable

click on labels if your selecting data with labels

click on ok.

So this is the output of Regression in Excel.

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.774
R Square	0.598
Adjusted R Square	0.554
Standard Error	0.400
Observations	11.000
ANOVA
	df	SS	MS	F	Significance F
Regression	1.000	2.142	2.142	13.409	0.005
Residual	9.000	1.438	0.160
Total	10.000	3.580
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	0.205	0.827	0.247	0.810	-1.666	2.075	-1.666	2.075
Speed	0.908	0.248	3.662	0.005	0.347	1.468	0.347	1.468

The null and alternative hypothesis

H0:β₁=0

H1: β₁≠0

ANOVA
	df	SS	MS	F	Significance F
Regression	1.000	2.142	2.142	13.41	0.005
Residual	9.000	1.438	0.160
Total	10.000	3.580

F-statistic : 13.41

Significance F : 0.005

Reject H0. We conclude that the relationship between speed of execution and overall satisfaction is significant.