Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.)Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of sixnotable buildings in a city.Height, xStories, yA60-077553Q6194751946OB.50842Find the regression equation.y = x+(Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.)Choose the correct graph below.Q. A.60049137800800Height (feet)(n) Brodict the value of x for x=503. Choose the correct answer below.Height (feet)47436D...(a) x = 503 feet(c) x 310 feetOC.8000Height (feet)Qwww.(b)x=642 feet(d) x = 730 feetOD.60-0-0800Height (feet) Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.)Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of sixnotable buildings in a city.Height, xStories, y7755361947OA. 31OB. 47O C. 52O D. not meaningful519465084249137(b) Predict the value of y for x=642. Choose the correct answer below.OA. 47OB. 31OC. 40O D. not meaningful(c) Predict the value of y for x = 310. Choose the correct answer below.474362E(a)x=503 feet(c) x=310 feet(b)x=642 feet(d) x 730 feet

Given data is x y 775 53 619 47 519 46 508 42 491 37 474 36

Answered: Find the equation of the regression…

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section4.6: Regression And Median-fit Lines

Problem 6PPS

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Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city.
Calculate the equation of the regression line and calculate the correlation coefficient
Find the equation of the regression line for the data based on time spend forstudying and current CGPA
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in milligrams) for 6 beef hot dogs are shown in the table below. Calories, x Sodium, y150 410180 460120 320120 36070 290190 540 (a) x=160 calories (b) x=90 calories (c) x=130 calories (d) x=220 calories Y=_____x+(___)
Find the fitted regression line for these data.
Run a regression of average hourly earnings (wage) on education (educ), experience (exper), exper2, sex (female), marital status (married) and num- ber of dependents (numdep). Discuss the statistical significance of each of the slope coefficients and interpret the coefficients on female and married. If experience increases from 20 years to 21 years, how are earnings expected to change? If experience increases from 35 years to 36 years, how are earnings expected to change? Compare the results.
Show the best fitted line on scatter diagram and Find the predicted value for each y using the exposure time and the equation obtained in part b (b. Find the equation of regression line between radiation doses on exposure time .usingleast square method)
randomly selected middle school students. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Unsupervised 1.5 2 3 3.5 4 4.5 5.5 Overall Grades 99 96 84 75 68 65 60 Table Step 1 of 6 : Find the estimated slope. Round your answer to three decimal places.
randomly selected middle school students. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Unsupervised 1.5 2 3 3.5 4 4.5 5.5 Overall Grades 99 96 84 75 68 65 60 Table Find the estimated slope, y interscept and correlation coefficient Round your answers to three decimal places.
find the (a) explained variation, (b) unexplained variation, and (c) indicated prediction interval. In each case, there is sujficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. Altitude and Temperature Listed below are altitudes (thousands of feet) and outside air temperatures (°F) recorded by the author during Delta Flight 1053 from New Orleans to Atlanta. For the prediction interval, use a 95% confidence level with the altitude of 6327 ft (or 6.327 thousand feet).
The coefficient of determination of a set of data points is 0.87 and the slope of the regression line is -2.86. Determine the linear correlation coefficient of the data.
A business statistics professor would like to develop a regression model to predict the final exam scores for students based on their current GPAs, the number of hours they studied for the exam, the number of times they were absent during the semester, and their genders. The data for these variables are given in the accompanying table at the bottom of this page. a) Using Excel, construct a regression model using all of the independent variables. Create the dummy variable Gen, which equals 1 for a male and 0 for a female student ( this assignment is arbitrary) complete the regression equation for the model below, where y= Score, x1= GPA, x2= Hours, x3= Absenses, and x4= Gen. y= (__) + (__)x1 + (__)x2 + (__)x3 + (__)x4 b) Test the significance of the overall regression model using a= 0.10. c) interpret the meaning of the regression coefficient for the dummy variable. d) using the p-values, identify which independent variables are significant with a= 0.10. e) construct a regression…

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