Pearson eText Business Statistics: First Course -- Instant Access (Pearson+)
8th Edition
ISBN: 9780136880974
Author: David Levine, David Stephan
Publisher: PEARSON+
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A researcher wants to investigate the influence of the average no. of nights spent per year by the tourists from Japan on the average amount spent by them. Table 3 shows the related data obtained from the Department of Statistics Malaysia website. Table 4 shows a portion of Microsoft Excel output for the regression analysis performed based on the data in Table 3.
Table 3: Data on the nights spent by tourists from Japan and amount spent
Year
Average no. of nights spent
Average amount spent (in RM billion)
2010
5.9
1.1
2011
6.1
1.1
2012
6.1
1.4
2013
6.3
1.5
2014
6.4
1.8
2015
6.1
1.6
2016
6.2
1.3
2017
6.3
1.2
2018
6.6
1.7
2019
6.9
2.3
Table 4: Regression analysis
Coefficients
Standard Error
t Stat
P-value
Intercept
B0
1.4555
-3.7583
0.0056
Average no. of nights spent
B1
0.2312
4.7934
0.0014
a. Note that the value of B0 and B1 are missing from Table 4.…
A random sample of 102 observations is selected to estimate the relationship between the price of a used car (y) and its odometer readings (x). The estimated
simple regression line is:
ý = 6533 – 0.03x
(0.004)
where the value 0.004 in bracket is the standard error of the point estimator for the slope in the regression model.
Question 15. What percent of the variability of the used car values can be explained using this model?
O 60%
O 36%
O 80%
O 64%
O 95%
O o o o
3. (a). Differentiate the different types of linear regression and describe the use of regression in geographical study.
(b). Calculate the value of the slope, b, for observations of n = 22, r2 = 0.73, standard deviation of x = 2.3 and the regression sum of square = 1324.
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- Accountants at the Tucson firm, Larry Youdelman CPAs believed that several traveling executives were submitting unusually high travel vouchers when they returned from business trips. First they took a sample of 200 vouchers submitted from the past year. Then they developed the following multiple regression equation relating expected travel cost to number of days on the road (X1) and distance traveled (X2) in miles: ^y= $95.00 + $50.50x1+$0.40x2 The coefficient of correlation for the model is 0.72 a) If Donna Battista returns from 300 mile trip that took her out of town for 6 days, the expected amount that she should claim as expense= $[__] (round your response to two decimal places)arrow_forwardSuppose you are estimating a wage regression, where salary is the dependent variable and age, years of education and a dummy variable for male are your independent variables. You are interested in measuring how salary differs between those who have at least a college education with those who have less than a college education. If a person is considered as having a college education when she has more than 12 years of education, how can you measure the difference in salary between college and non-college educated individuals? Select one: a. Multiply coefficient for years of education in original regression by 12 O b. Re-estimate model replacing years of education with a dummy variable for college c. Re-estimate model replacing years of education with a dummy variable for college and one for no college O d. Re-estimate model interacting years of education with a dummy variable for college e. Calculate the difference in predicted salary between an individual with 14 years of education and…arrow_forwardb) pleasearrow_forward
- A startup team is interested in creating a productivity app. In estimating the cost of creating the app, they collected sample data and developed the following regression equation: where 1 = number of developers b₂ a. What is the value of b2 in the equation? 2= number of hours spent creating the app Is cost of software and testing ($'000) y = total cost of creating app ($'000) b. Does it make sense to interpret by in this equation? OYes y = -8.825+20.4861 +0.56x2 + 1.02x3 O No $ c. Predict the cost of creating an app involving 3 developers, 650 hours and $18,000 in software and testing costs. Accessibility Investigate 8arrow_forwardThe distance between the Y value in the data and the predicted Y value from the regression equation is known as the residual. What is the value for the sum of the squared residuals? a. SSresidual = r2(SSX) b. SSresidual = r2(SSY) c. SSresidual = (1 – r2)(SSX) d. SSresidual = (1 – r2)(SSY)arrow_forwardA set of n=20 pairs of x and y scores had SSx=10,SSy=40,and SP=30.What is the slope for the regression equation for predicting y from x?arrow_forward
- A. Do these data provide sufficient evidence that there is a positive linear relationship between the two variables? B. What does R^2 imply? C. Using the regression model, predict the blood pressure level associated with a sound pressure of 7.5 decibels.arrow_forwardThis table reports the regression coefficients when the returns of the size-institutionalownership portfolio (columns 1 and 2) returns are regressed on three variables: a constant(column 3), the stock market returns (column 4), and the change of the value weighted discountof the closed end fund industry (column 6). Columns 5 and 7 report the corresponding t-statistics of the coefficient estimates. Note that a t-statistic with an absolute value above 1.96means the coefficient estimate is significantly different from 0 at the 1% level. Column 8reports the R square of the regressions. Column 9 reports the mean institutional ownership ofeach portfolio. The last column reports the F-statistics for a multivariate test of the null hypothesis that the coefficient on ΔVWD in the Low (L) ownership portfolio is equal to theHigh (H) ownership portfolio. Two-tailed p-values are in parentheses. 1. What is the main finding of this Table? 2. What is the explanation for…arrow_forwardAcrylamide is a chemical that is sometimes found in cooked starchy foods and which is thought to increase the risk of certain kinds of cancer. The paper "A Statistical Regression Model for the Estimation of Acrylamide Concentrations in French Fries for Excess Lifetime Cancer Risk Assessment"t describes a study to investigate the effect of x = y = acrylamide concentration (in micrograms per kg) in French fries. The data in the accompanying table are approximate values read from a graph that appeared in the paper. frying time (in seconds) and %3D Frying Time Acrylamide Concentration 150 155 240 115 240 190 270 180 300 140 300 265arrow_forward
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