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Question 1Given the linear correlation coefficient r and the sample size n, determine the critical values of r and use your finding to state whether or not the given r represents a significant linear correlation. Use a significance level of 0.05. r = 0.75, n = 9Critical values: r = ±0.666, no significant linear correlationCritical values: r = 0.666, no significant linear correlationCritical values: r = -0.666, no significant linear correlationCritical values: r = ±0.666, significant linear correlationQuestion 2Construct a scatterplot for the given data. Choose A, B, C, or D. Question 3Find the value of the linear correlation coefficient r. -0.0540.2140.109-0.078Question 4Suppose you will perform a test to determine whether there is sufficient evidence to support a claim of a linear correlation between two variables. Find the critical values of r given the number of pairs of data n and the significance level alpha. n = 11, = 0.01r = 0.765r = ± 0.602r = 0.735r = ± 0.735Question 5Use the given data to find the best predicted value of the response variable. Six pairs of data yield r = 0.789 and the regression equation What is the best predicted value of y for x = 5?22.018.018.519.0Question 6Use the given data to find the equation of the regression line. Round the final values to three significant digits, if necessary. Choose A, B, C, or D. Question 7Is the data point, P, an outlier, an influential point, both, or neither? NeitherOutlierBothInfluential pointQuestion 8Use the given information to find the coefficient of determination. A regression equation is obtained for a collection of paired data. It is found that the total variation is 24.488, the explained variation is 15.405, and the unexplained variation is 9.083. Find the coefficient of determination.0.6290.5901.5900.371Question 9 82.7%17.0%91.1%83.0%Question 10Find the explained variation for the paired data. The paired data below consists of test scores and hours of preparation for 5 randomly selected students. The equation of the regression line is = 44.8447 + 3.52427x. Find the explained variation. 498.103511.72487.4757599.2Question 11Find the unexplained variation for the paired data. The paired data below consists of test scores and hours of preparation for 5 randomly selected students. The equation of the regression line is = 44.8447 + 3.52427x. Find the unexplained variation. 511.72487.475796.103599.2Question 12Find the total variation for the paired data. The paired data below consists of test scores and hours of preparation for 5 randomly selected students. The equation of the regression line is = 44.8447 + 3.52427x. Find the total variation. 599.2498.103511.72487.4757Question 13Find the standard error of estimate for the paired data. The paired data below consists of test scores and hours of preparation for 5 randomly selected students. The equation of the regression line is = 44.8447 + 3.52427x. Find the standard error of estimate. 4.10977.17205.399913.060Question 14Construct the indicated prediction interval for an individual y. The paired data below consists of test scores and hours of preparation for 5 randomly selected students. The equation of the regression line is y-hat = 44.845 + 3.524x and the standard error of estimate is Se = 5.40. Find the 99% prediction interval for the test score of a person who spent 7 hours preparing for the test. 58 < y < 8262 < y < 7835 < y < 10432 < y < 107Question 15Solve the problem. 1.936 < B1 < 4.8740.686 < B1 < 6.1240.322 < B1 < 6.4880.134 < B1 < 6.676Question 16Use computer software to find the multiple regression equation. Can the equation be used for prediction? An anti-smoking group used data in the table to relate the carbon monoxide of various brands of cigarettes to their tar and nicotine content. CO = 1.37 - 5.53TAR + 1.33NIC; Yes, because the R2 is highCO = 1.37 + 5.50TAR - 1.38NIC; Yes, because the P-value is highCO = 1.3 + 5.5TAR - 1.3NIC; Yes, because the adjusted R2 is highCO = 1.25 + 1.55TAR - 5.79NIC; Yes, because the P-value is too lowQuestion 17Use computer software to obtain the multiple regression equation and identify R2, adjusted R2, and the P-value. An anti-smoking group used data in the table to relate the carbon monoxide of various brands of cigarettes to their tar and nicotine content. 0.976, 0.921, 0.0020.943, 0.934, 0.0000.931, 0.902, 0.0000.861, 0.900, 0.015Question 18Use computer software to obtain the multiple regression equation. Use the estimated equation to find the predicted value. A health specialist gathered the data in the table to see if pulse rates can be explained by exercise and smoking. For exercise, he assigns 1 for yes, 2 for no. For smoking, he assigns 1 for yes, 2 for no. He then used his results to predict the pulse rate of a person whose exercise value was 1 and whose smoking value was 1. 70 beats/min74 beats/min81 beats/min77 beats/minQuestion 19Find the indicated multiple regression equation. P-hat = 14.09 + 0.213(Att.) + 0.895(Adapt.)P-hat = 14.09 + 0.895(Att.) + 0.213(Adapt.)P-hat = 14.09 + 0.907(Att.) + 0.014(Adapt.)P-hat = 14.09 + 0.014(Att.) + 0.907(Adapt.)Question 20Use computer software to find the best multiple regression equation to explain the variation in the dependent variable, Y, in terms of the independent variables, X1, X2, X3. Y-hat = 0.42 + 0.99X2Y-hat = 1.38 - 5.53X1 + 1.33X2Y-hat = 1.25 - 1.55X1 + 5.79X2Y-hat = -0.49 + 14.07X1 ................
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