For questions 15-20, use the following regression output obtained by regressingbirth weight (the y variable called birthwt) on the number of cigarettes smokedby women while pregnant (the x variable called cigs):SUMMARY OUTPUTRegression StatisticsMultiple RR Square0.1510.023Adjusted R SquareStandard Error0.02220.129Observations1,388Coefficients Standard Errort Stat P-valutUpper 95%Lower 95%Intercept (bo)119.770.57209.270.003118.65120.89cigs (b;)-0.510.09-0.34-5.680.001-0.69Looking at the output above, is the impact of cigarettes on birth weightstatistically significant at a = 0.05?No answer text provided.yesnowe do not have enough information For questions 15-20, use the following regression output obtained by regressingbirth weight (the y variable called birthwt) on the number of cigarettes smokedby women while pregnant (the x variable called cigs):SUMMARY OUTPUTRegression StotisticsMultiple RR Square0.1510.023Adjusted R Square0.022Standard Error20.129Observations1,388Coefficients Standard Error tStat P-valueUpper 95%Lower 95%Intercept (bo)119.770.57209.270.003118.65120.89cigs (b;)-0.69-0.510.09-5.680.001-0.34Given the 72 above (denoted R Square), what does this value tell us?O 2.3 percent of the variation in birth weight is being explained by the variation incigarettesO none of these are correctO 2.3 percent of the variation in birth weight is NOT being explained by the variation incigarettesO 2.3 percent of the observations smoked

For the given data Select the correct choice

Answered: For questions 15-20, use the following…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Consider the following computer output from a multiple regression analysis relating the cost of car insurance to the variables: number of car accidents, driver's credit score, and safety rating of the car. Answer Coefficients Coefficients Standard Error 680 Intercept Car Accidents (In last 3 years) Credit Score -74.80 Safety Rating - 104.25 122.40 Does the sign of the coefficient for the variable number of car accidents make sense? 79.71 14.75 8.89 11.46 t Stat P-value 8.531 0.0000 0.0000 8.298 -8.414 -9.097 0.0000 0.0000 O Yes, because it is expected that as the number of car accidents increases then the cost should also increase. O No, because it is expected that as the number of car accidents increases then the cost should also increase. O Yes, because it is expected that as the number of car accidents increases then the cost should decrease. O No, because it is expected that as the number of car accidents increases then the cost should decrease. Keyp- Keyboard Short Tables
Consider the following computer output from a multiple regression analysis relating the price of a used car to the variables: age of car, mileage, and safety rating. Intercept Age (Year) Mileage (in Thousands) Safety Rating Does the sign of the coefficient for the variable age make sense? Answer Coefficients 23287.65 7671.28 -551.27 Coefficients 894.16 Standard Error 3327.39 8976.75 45.10 96.36 t Stat 6.999 0.855 - 12.223 9.280 P-value 0.0000 0.3965 0.0000 0.0000 O No, because it is expected that as age increases then the price should decrease. O Yes, because it is expected that as age increases then the price should also increase. O No, because it is expected that as age increases then the price should also increase. O Yes, because it is expected that as age increases then the price should decrease. Tables Key Keyboard Shor
The accompanying data are the number of wins and the earned run averages (mean number of earned runs allowed per nine innings pitched) for eight baseball pitchers in a recent season. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x = 5 wins Click the icon to view the table of numbers of wins and earned run average. (b) x = 10 wins (c) x = 21 wins (d) x = 15 wins ERA 6- ERA 6- AERA 6- ERA 6- 4- 4- 4- 4- 2- 2- 2- 2- 0+ 6 0- 0- 0- 12 18 24 6. 12 18 24 12 18 24 6 12 18 24 Wins Wins Wins Wins (a) Predict the ERA for 5 wins, if it is meaningful. Select the correct choice below and, if necessary, fill in the answer box within your choice. A. ŷ= (Round to two decimal places as needed.) B. It is not meaningful to predict this value of y because…
Please solve the question in the image asap. Here are the answer choices:
Use the value of the linear correlation coefficient to calculate the coefficient of determination. What does this tell you about the explained variation of the data about the regression line? About the unexplained variation? r=0.926
Answer the questions based on the following data table. What is the value of the correlation coefficient (r) between the variables? (round to 2 decimals) How much of the variation between the variables is explained by the regression model (R-sqr)? (round to 2 decimals) How far off (std error) will the regression model typically be in predicting y? At what level is the regression statistically significant (i.e.,Sig.F)? decimals) What is the slope (coefficient of x) of the linear regression equation? 2 decimals) What is the y-intercept of the linear regression equation? (round to 2 If given an x value of 3.6, what value of y does the regression equation predict? (round to 2 decimals) (round to (round to 2 decimals)
Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right arm blood pressure be the predictor (x) variable Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 95 mm Hg. Use a significance level of 0.05 Right Arm 103 102 94 79 80 D Left Arm 176 170 144 146 145 : Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is y= +x (Round to one decimal place as needed.) ater/ Enter your ahswer in the edit fields and then click Check Answer
For questions 15-20, use the following regression output obtained by regressing birth weight (the y variable called birthwt) on the number of cigarettes smoked by women while pregnant (the x variable called cigs): SUMMARY OUTPUT Regression Statistics Multiple R 0.151 R Square 0.023 Adjusted R Square Standard Error 0.022 20.129 Observations 1,388 Coefficients Standard Error tStat P-value Lower 95% Upper 95% Intercept (bo) 119.77 0.57 209.27 0.003 118.65 120.89 cigs (b,) -0.51 0.09 -5.68 0.001 -0.69 -0.34 The appropriate representation of the population model being estimated above is cigs = Bo + Bi birthwt + e %3D cigs = bo + bi birthwt + ê none of these are correct birthwt = Bo + Bicigs +e
You may need to use the appropriate technology to answer this question. Following is a portion of the computer output for a regression analysis relating y = maintenance expense (dollars per month) to x = usage (hours per week) of a particular brand of computer terminal. Analysis of Variance SOURCE DF Adj SS Adj MS Regression 1 1575.76 1575.76 Error 8 349.14 43.64 Total 9 1924.90 Predictor Coef SE Coef Constant 6.1092 0.9361 X 0.8951 0.1490 Regression Equation Y = 6.1092 + 0.8951 X #1) Write the estimated regression equation. ŷ = #2) Find the value of the test statistic. (Round your answer to two decimal places.)Find the p-value. (Round your answer to three decimal places.) #3)Use the estimated regression equation to predict monthly maintenance expense (in dollars per month) for any terminal that is used 15 hoursper week. (Round your answer to the nearest cent.) $ _____per month
The following data gives the number of employees at the bookstore and the number of minutes students wait in line to buy books at the beginning of the term. The independent variable is the number of employees and the dependent variable is the number of minutes. What is the y intercept? SSxx = 56.857; SS=2095.714; SSxy=-322.571 SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square XA356899 0.96 0.93 0.91 y 67 54 47 33 31 25 12
Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 80 mm Hg. Use a significance level of 0.05. Right Arm 100 99 93 77 77 Q Left Arm 174 168 148 148 146 Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is ŷ=+x. (Round to one decimal place as needed.) mm Hg. Given that the systolic blood pressure in the right arm is 80 mm Hg, the best predicted systolic blood pressure in the left arm is (Round to one decimal place as needed.) Data table Critical Values of the Pearson Correlation Coefficient r α = 0.05 α = 0.01 0.950 0.990 0.959 0.878 0.811 0.917 0.754 0.875 0.707 0.834 0.666 0.798 0.632 0.765 0.602 0.735 0.576 0.708 0.553 0.684 0.532 0.661 0.514 0.641 0.497 0.623 0.482…
An automobile rental company wants to predict the yearly maintenance expense (Y) for an automobile using the number of miles driven during the year () and the age of the car (, in years) at the beginning of the year. The company has gathered the data on 10 automobiles and run a regression analysis with the results shown below:. Summary measures Multiple R 0.9689 R-Square 0.9387 Adj R-Square 0.9212 StErr of Estimate 72.218 Regression coefficients Coefficient Std Err t-value p-value Constant 33.796 48.181 0.7014 0.5057 Miles Driven 0.0549 0.0191 2.8666 0.0241 Age of car 21.467 20.573 1.0434 0.3314 Use the information above to estimate the annual maintenance expense for a 10 years old car with 60,000 miles.

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