APPLIED STAT.IN BUS.+ECONOMICS
6th Edition
ISBN: 9781259957598
Author: DOANE
Publisher: RENT MCG
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Chapter 13, Problem 8ERQ
To determine
Find the critical value of t to test the hypothesis that
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Consider a simple linear regression model
Y=α+βX+ε.
We have collected 15 samples, from which we calculated the summary statistics
∑xi=66, ∑x2i=6568,
∑yi=459, ∑y2i=27933,
∑xiyi=11311.
Suppose one of the data is supposed to be (x1=10, y1=30), but is incorrectly recorded as (x1=7, y1=34). All other observations are correctly recorded.
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The quadratic regression equation shown below is for a sample of n=22.
Determine the critical value(s).
(1) Write out the regression equation (2) What is the sample size used in this investigation? (3) Determine the values of *, ** and ***, ****
Chapter 13 Solutions
APPLIED STAT.IN BUS.+ECONOMICS
Ch. 13.1 - Observations are taken on net revenue from sales...Ch. 13.1 - Observations are taken on sales of a certain...Ch. 13.1 - Prob. 3SECh. 13.1 - A regression model to predict Y, the...Ch. 13.2 - Refer to the ANOVA table below. (a) State the...Ch. 13.2 - Refer to the ANOVA table below. (a) State the...Ch. 13.2 - Prob. 7SECh. 13.2 - Refer to the ANOVA table below. (a) State the...Ch. 13.3 - Observations are taken on net revenue from sales...Ch. 13.3 - Observations are taken on sales of a certain...
Ch. 13.3 - Prob. 11SECh. 13.3 - A regression model to predict Y, the state...Ch. 13.4 - A regression of accountants starting salaries in a...Ch. 13.4 - An agribusiness performed a regression of wheat...Ch. 13.5 - Prob. 15SECh. 13.5 - A regression model to predict the price of...Ch. 13.5 - Prob. 17SECh. 13.5 - Prob. 18SECh. 13.6 - Prob. 19SECh. 13.6 - Prob. 20SECh. 13.7 - Prob. 21SECh. 13.7 - Using the Metals data, construct a correlation...Ch. 13.8 - Prob. 23SECh. 13.8 - Which violations of regression assumptions, if...Ch. 13 - (a) List two limitations of simple regression. (b)...Ch. 13 - (a) What does represent in the regression model?...Ch. 13 - Prob. 3CRCh. 13 - Prob. 4CRCh. 13 - Prob. 5CRCh. 13 - Prob. 6CRCh. 13 - Prob. 7CRCh. 13 - Prob. 8CRCh. 13 - Prob. 9CRCh. 13 - (a) State the formula for the standard error of...Ch. 13 - (a) What is a binary predictor? (b) Why is a...Ch. 13 - Prob. 12CRCh. 13 - Prob. 13CRCh. 13 - (a) What is multicollinearity? (b) What are its...Ch. 13 - Prob. 15CRCh. 13 - (a) State the formula for a variance inflation...Ch. 13 - Prob. 17CRCh. 13 - Prob. 18CRCh. 13 - Prob. 19CRCh. 13 - Prob. 20CRCh. 13 - (a) Name two ways to detect autocorrelated...Ch. 13 - (a) What is a lurking variable? How might it be...Ch. 13 - Prob. 23CRCh. 13 - Instructions for Data Sets: Choose one of the data...Ch. 13 - Note: Exercises marked are based on optional...Ch. 13 - Prob. 27CECh. 13 - Note: Exercises marked are based on optional...Ch. 13 - Note: Exercises marked are based on optional...Ch. 13 - Prob. 30CECh. 13 - Prob. 31CECh. 13 - Prob. 32CECh. 13 - Prob. 33CECh. 13 - Prob. 34CECh. 13 - Prob. 35CECh. 13 - Note: Exercises marked are based on optional...Ch. 13 - Note: Exercises marked are based on optional...Ch. 13 - Note: Exercises marked are based on optional...Ch. 13 - Prob. 39CECh. 13 - Prob. 40CECh. 13 - Prob. 41CECh. 13 - In a model of Fords quarterly revenue TotalRevenue...Ch. 13 - In a study of paint peel problems, a regression...Ch. 13 - A hospital emergency room analyzed n = 17,664...Ch. 13 - Prob. 45CECh. 13 - A researcher used stepwise regression to create...Ch. 13 - A sports enthusiast created an equation to predict...Ch. 13 - An expert witness in a case of alleged racial...Ch. 13 - Prob. 50CECh. 13 - Prob. 51CECh. 13 - Prob. 52CECh. 13 - Which statement is correct concerning one-factor...Ch. 13 - Prob. 2ERQCh. 13 - Prob. 3ERQCh. 13 - Prob. 4ERQCh. 13 - Prob. 5ERQCh. 13 - Prob. 6ERQCh. 13 - Prob. 7ERQCh. 13 - Prob. 8ERQCh. 13 - Prob. 9ERQCh. 13 - Prob. 10ERQCh. 13 - Prob. 11ERQCh. 13 - Prob. 12ERQCh. 13 - Prob. 13ERQCh. 13 - Prob. 14ERQCh. 13 - Prob. 15ERQ
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- Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?arrow_forwardConsider a linear regression model for the decrease in blood pressure (mmHg) over a four-week period with muy=2.8+0.8x and standard deviation chi=3.2. The explanatory variable x is the number of servings fruits and vegetables in a calorie-controlled diet. Using the 68-95-99.7 rule, between what two values would approximately 95% of the observed responses, y, fall when x = 7?arrow_forwardThe following estimated regression equation based on 10 observations was presented. ŷ = 25.1270 + 0.5309x1 + 0.4920x2 Here, SST = 6,738.125, SSR = 6,221.375, sb1 = 0.0818, and sb2 = 0.0563. Perform a t test for the significance of β1. Use α = 0.05. State the null and alternative hypotheses. a. H0: β1 > 0 Ha: β1 ≤ 0 b. H0: β1 ≠ 0 Ha: β1 = 0 c. H0: β1 < 0 Ha: β1 ≥ 0 d. H0: β1 = 0 Ha: β1 > 0 e. H0: β1 = 0 Ha: β1 ≠ 0 5. Find the value of the test statistic. (Round your answer to two decimal places.) 6. Find the p-value. (Round your answer to three decimal places.) p-value = 7. State your conclusion. a. Do not reject H0. There is sufficient evidence to conclude that β1 is significant. b. Reject H0. There is insufficient evidence to conclude that β1 is significant. c. Reject H0. There is sufficient evidence to conclude that β1 is significant. d. Do not reject H0. There is insufficient evidence to conclude that…arrow_forward
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