A researcher developed a regression model to predict the tear rating of a bag of coffee based on the plate gap in bag-sealing equipment. Data were collected on 28 bags in which the plate gap was varied. An analysis of variance from theregression showed that b, = 0.7909 and Sp.= 0.2294.a. At the 0.05 level of significance, is there evidence of a linear relationship between the plate gap of the bag-sealing machine and the tear rating of a bag of coffee?b. Construct a 95% confidence interval estimate of the population slope, B1......

Answered: A researcher developed a regression…

Big Ideas Math A Bridge To Success Algebra 1: Student Edition 2015

1st Edition

ISBN:9781680331141

Author:HOUGHTON MIFFLIN HARCOURT

Publisher:HOUGHTON MIFFLIN HARCOURT

Chapter4: Writing Linear Equations

Section: Chapter Questions

Problem 14CR

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1. Which one can describe the regression estimation? A) Predict the mean value of the dependent variable bascd on valucs of the cxplanatory variables. B) Predict the mcdian valuc of the dependent variable based on valucs of the explanatory variables. C) Predict the mcan valuc of the independent variables on the basis of the dependent variable. D) Predict the median value of the independent variables on the basis of the dependent variable.
A regression model to predict Y, the state burglary rate per 100,000 people, used the following four state predictors: X1 = median age, X2 = number of bankruptcies per 1,000 population, X3 = federal expenditures per capita (a leading predictor), and X4 = high school graduation percentage. Click here for the Excel Data File (a) Using the sample size of 45 people, calculate the tcalc and p-value in the table given below. (Negative values should be indicated by a minus sign. Leave no cells blank - be certain to enter "0" wherever required. Round your t-values to 3 decimal places and p- values to 4 decimal places.) Predictor Intercept AgeMed Coefficient SE tcalc p-value 4,641.0430 798.0634 -28.8630 12.4684 Bankrupt 20.1604 12.1079 FedSpend HSGrad% -0.0181 0.0181 -30.3196 7.1136 (b-1) What is the critical value of Student's tin Appendix D for a two-tailed test at a = .01? (Round your answer to 3 decimal places.) -value =
A random sample of records of electricity usage of homes gives the amount of electricity used and size (in square feet) of 135 homes. A simple linear regression to predict the amount of electricity used (in kilowatt-hours) based on size has an * = 0.71. Assume that a linear model is appropriate. Interpret r. O A. The prediction error using the regression line to predict electricity use is 71% smaller than the prediction error using y to predict it. B. The prediction error for predicting electricity use is about the same when using the regression line and y. C. The prediction error using the regression line to predict electricity use is 29% larger than the prediction error using y to predict it. D. The prediction error using the regression line to predict electricity use is 71% larger than the prediction error using y to predict it. O E. The prediction error using the regression line to predict electricity use is 29% smaller than the prediction error using y to predict it.
In a sample of cars reviewed by Motor Trend magazine, the mean horsepower (hp) was 150 hp with a standard deviation of 36 hp. The mean weight (lbs) was 2500 lbs with a standard deviation of 720 lbs. Assume the relationship between weight and horsepower is linear and has a correlation of r = +0.55. What is the slope of the linear regression model predicting weight (y-variable) from horsepower (x-variable)? 9 13 15 11
A regression model to predict Y, the state burglary rate per 100,000 people, used the following four state predictors: X₁ = median age, X₂ = number of bankruptcies per 1,000 population, X3 = federal expenditures per capita (a leading predictor), and X4 = high school graduation percentage. Click here for the Excel Data File (a) Using the sample size of 50 people, calculate the tcalc and p-value in the table given below. (Negative values should be indicated by a minus sign. Leave no cells blank - be certain to enter "0" wherever required. Round your answers to 4 decimal places.) Predictor Intercept AgeMed Bankrupt FedSpend HSGrad% Coefficient t-value = 4,198.5808 -27.3540 17.4893 -0.0124 -29.0314 SE 799.3395 12.5687 12.4033 0.0176 7.1268 tcalc p-value (b-1) What is the critical value of Student's t in Appendix D for a two-tailed test at a = .01? (Round your answer to 3 decimal places.)
The mean travel time from one stop to the next on the Coast Starlight Amtrak is 129 minutes, with a standard deviation of 113 minutes. The mean distance travelled from one stop to the next is 108 miles with standard deviation of 99 miles. The correlation between travel time and distance is 0.636. a). Find the equation of the regression line for predicting travel time.
A sample of 40 individuals collects their shoe size and the height (cm) for CSI data. The scatter plot and results from a simple linear regression are recorded: HEIGHT = 126.76238 + 4.8782178 SHOE SIZE Sample size: 40R (correlation coefficient) = 0.77918855P-value < 0.0001 (a) Does the scatterplot and results show a linear correlation between shoe size and height? (b) How can you tell? (c) Will it be appropriate to use the linear regression equation given in the output? (d) Krusty the Clown wears size 8.5 shoes. According to the linear regression equation, how tall is Krusty the Clown? (e) Sideshow Bob wears size 14 shoes. According to the linear regression equation, how tall is Sideshow Bob?
A researcher developed a regression model to predict the cost of a meal based on the summated rating (sum of ratings for food, decor,and service) and the cost per meal for 12 restaurants. The results of the study show that b1=1.4379 and Sb1=0.1397. a. At the 0.05 level of significance, is there evidence of a linear relationship between the summated rating of a restaurant and the cost of a meal? b. Construct a 95% confidence interval estimate of the population slope, β1. a. Determine the hypotheses for the test. Choose the correct answer below. A. H0: β1=0 H1: β1≠0 B. H0: β0≤0 H1: β0>0 C. H0: β1≤0 H1: β1>0 D. H0: β0≥0 H1: β0<0 E. H0: β1≥0 H1: β1<0 F. H0: β0=0 H1: β0≠0 Compute the test statistic. The test statistic is ? (Round to two decimal places as needed.) Determine the critical value(s). The critical value(s) is(are) ? (Use a comma to separate answers as needed.…
The administration of a midwestern university commissioned a salary equity study to help establish benchmarks for faculty salaries. The administration utilized the following regression model for annual salary, y : ?(?) β0+β1x ,where ?=0 if lecturer, 1 if assistant professor, 2 if associate professor, and 3 if full professor. The administration wanted to use the model to compare the mean salaries of professors in the different ranks. a) Explain the flaw in the model. b)Propose an alternative model that will achieve the administration’s objective. c) If the global F-test for the model you proposed in 2 is conducted, what would be the value of the numerator degrees of freedom?
The fish in my pond have mean length 10 inches with a standard deviation of 2 inches and mean weight 4 pounds with a standard deviation of .6 pounds. The correlation coefficient of length and weight is .9. If the length of a particular randomly selected fish is reported to be 15 inches, then what should we predict for the weight of that fish using simple linear regression?
Low-Density Lipoprotein (or LDL) is considered the "bad" cholesterol because it forms plaques in arteries, raising the risk for heart attack and stroke. Suppose you are interested in predicting LDL (in mg/dL) using one's age (in years). Assume that LDL levels and age are normally distributed and that the correlation between the two variables is 0.534. Based solely on the regression effect, a person whose age is at the 60th percentile is predicted to have an LDL level ____. [Source: Ldl cholesterol: Definition, risks, and how to lower it. (2020, March 09). Retrieved from https://www.webmd.com/heart-disease/ldl-cholesterol-the-bad-cholesterol] Question 4 options: A) above the 60th percentile B) exactly at the 60th percentile C) exactly at the 40th percentile D) I need more information to answer this E) below the 60th percentile
A regression model to predict Y, the state burglary rate per 100,000 people, used the following four state predictors: X₁ = median age, X₂ = number of bankruptcies per 1.000 population, X3 = federal expenditures per capita (a leading predictor), and X4 = high school graduation percentage. Click here for the Excel Data File (a) Using the sample size of 50 people, calculate the calc and p-value in the table given below. (Negative values should be indicated by a minus sign. Leave no cells blank - be certain to enter "0" wherever required. Round your answers to 4 decimal places.) Predictor Intercept AgeMed Bankrupt FedSpend HSGrad% Answer is complete but not entirely correct. *calc 5.2526 -2.1764✔✔ 1.4101✔ Coefficient 4,198.5808 -27.3540 17.4893 -0.0124 -29.0314 SE 799.3395 12.5687 12.4033 0.0176 7.1268 -0.7045 -4.0736 p-value 0.0000 0.0348 0.2935 0.4848 0.0002

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