3. LINEAR REGRESSION AND CORRELATION COEFFICIENT:Consider the following data set:X-7-5 -1y1121-4(a) Use your calculator to find the linear regression equation for the data setabove.(b) Find the correlation coefficient for the data set.Calculator Tips: It's probably good to remember how to find the line of bestfit and the correlation coefficient by hand. But such computations can be verytedious if the data set is big.Your graphing calculator can find the linear regression equation and the cor-relation coefficient. Click here or here for video tutorials on performing linearregression and finding the correlation coefficient, r, using a calculator. The twolinked videos use different versions of the TI-89 calculator. The course textbookalso has instructions at the end of section 1.3 (pg. 80-82).

Answered: Image /qna-images/answer/0e64b1d6-29e1-477b-8cc9-e9f1d6b37d11.jpg

Answered: 3. LINEAR REGRESSION AND CORRELATION…

Calculus: Early Transcendentals

8th Edition

ISBN:9781285741550

Author:James Stewart

Publisher:James Stewart

Chapter1: Functions And Models

Section: Chapter Questions

Problem 1RCC: (a) What is a function? What are its domain and range? (b) What is the graph of a function? (c) How...

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In R there is a dataset called diamonds that contains measurements of about 500 diamonds sold in the US. There are three variables present: price (price in US dollar), carat (weight of the diamond), and table (width of top of diamond relative to the widest point). The attached image is a screenshot of the R dataset with the regression table and all that. ANSWER THIS QUESTION IN WORDS: Discuss the regression between the variables table and price. You should address the explanatory variable, response variable, correlation, and sign. You should interpret the slope, the t and p-value, and how much is explained by the response.
An educator wants to see how the number of absences for a student in her class affects the student's final grade by formulating the equation of the regression line. The data obtained from a sample are shown. Required: Slope of the regression line Only the final answer should be rounded-off to TWO decimal places. 12 Number of absences (x) 10 2 0 7 4 Final Grade (y) 65 68 70 94 77 96
Below is the actual data on the speed a person walks or runs in miles/hour and the calories the person burns per lap. Find the linear equation of best fit for this data. Compare the model to the data. Does the model seem to fit the data? Explain. What is the significance of the y-intercept? What is the slope and what does it mean? What is the x-intercept and what does it mean? What is the correlation coefficient and what does it mean? Speed (mph) Calories/lap 1 42 2 31 3 27 4 41 5 40 6 40 7 39 8 38 r answers to the nearest hundredth. The y-intercept means that if a person runs at ----------mph they will burn__________ per lap. The slope means that for each mph you increase your speed, you will burn an additional------------calories pay lap
What are the coefficients of correlation between miles per gallon and horsepower? Between miles per gallon and the weight of the car? What are the directions and strengths of these coefficients? Do the coefficients of correlation indicate a strong correlation, weak correlation, or no correlation between these variables? See Step 4 in the Python script. Write the multiple regression equation for miles per gallon as the response variable. Use weight and horsepower as predictor variables. See Step 5 in the Python script. How might the car rental company use this model?
4) How to conduct multiple regression in Excel (Provide the steps)? Driving Experience (years) Monthly Auto Insurance Premium 5 $64 2 87 12 50 9 71 15 44 6 56 25 42 16 60 Does the insurance premium depend on the driving experience or does the driving experience depend on the insurance premium? Do you expect a positive or a negative relationship between these two variables?
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. (a) x 503 feet (c) x = 318 feet (b) x = 649 feet (d) x = 724 feet 766 494 484 520 44 620 508 Height, x Stories, y 51 46 43 39 38 (c) Predict the value of y for x=318. Choose the correct answer below. O A. 34 B. 50 O C. 47 O D. not meaningful (d) Predict the value of y for x=724. Choose the correct answer below. O A. 34 O B. 41 50
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, y (a) x= 150 calories (c) x= 120 calories (b) x= 90 calories (d) x=60 calories 160 180 130 130 80 190 415 465 350 380 270 540 (c) Predict the value of y for x= 120. Choose the correct answer below O A. 347 151 O B. 279.801 O C. 414.501 O D. not meaningful (d) Predict the value of y for x= 60. Choose the correct answer below. O A. 414.501 O B. 212.451 tes O C. 279.801
If you know that the equation of the simple linear regression between the final exam result and the mid-year examination result for students in engineering statistics is as follows: Final exam = 50 + 0.5 x midterm according to the above equation, then the regression coefficient is:
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. Height, x Stories, y (b) x = 649 feet (d) x = 724 feet 766 620 520 508 494 484 (a) x = 503 feet 51 46 44 43 39 38 (c) x = 318 feet Find the regression equation. (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) Choose the correct graph below. O A. O B. O C. O D. 60- 60- 60 60- 0- 800 800 800 Height (feet 800 Height (feet) Height (Teet) Stories Stories:
The following table shows the approximate amount of trash produced in an industrialized country from 1980 to 2000. Let x represent the year after 1980 (1980 is year 0) and y represent the amount of trash (millions of tons). Year Million Tons 1980 150 1990 202 2000 220 (a) Draw the graph for this data. (b) Find the equation of the regression line for the data. (Round your answers to one decimal place.)y = x + (c) Use the equation to predict the amount of trash y that will be produced in 2010 and 2015. (Round your answers to one decimal place.) 2010: _______million tons 2015: _______ million tons
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 number of hours 6 students spent for a test and their scores on that test are shown below. Hours spent studying, x Test score, y 4 47 (a) x=3 hours (c) x= 13 hours (b) x= 2.5 hours (d) x= 3.5 hours 5 6 40 45 52 63 72 Find the regression equation. y=x+ (O (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.)

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