The following table shows students' test scores on the first two tests in an introductory chemistry class.Firsttest, xAnswerSecondtest, y62 85 9160 86Chemistry Test Scores8946 89 84 87 67 74 8593 98 54 61 98 82 84 75 81 88Copy DataStep 2 of 2: If a student scored a 70 on his first test, make a prediction for his score on the second test. Assume the regression equation is appropriate forprediction. Round your answer to two decimal places, if necessary.TablesFFFF

The question is about regression Given : To find : Pred. on the second test if a student scored…

Answered: The following table shows students'…

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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The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 40inches. Is the result close to the actual weight of 352pounds? Use a significance level of 0.05.a. Chest size (inches) 41 54 44 55 39 51 Weight (pounds) 328 528 418 580 296 503 a.What is the regression equation? b. The best predicted weight for a bear with a chest size of 39 inches is _______pounds.
The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 58 inches. Is the result close to the actual weight of 572 pounds? Use a significance level of 0.05. Chest size (inches) 46 57 53 41 40 40 Weight (pounds) 384 580 542 358 306 320 LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y=nothing+nothingx (Round to one decimal place as needed.)
The following table shows students' test scores on the first two tests in an introductory statistics class. First test, x Second test, y 95 41 86 82 43 Statistics Test Scores 52 75 74 43 84 52 70 60 70 91 56 74 72 42 78 57 72 54 63 Copy Data Step 2 of 2: If a student scored a 61 on his first test, make a prediction for his score on the second test. Assume the regression equation is appropriate for prediction. Round your answer to two decimal places, if necessary.
Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed actress/actor ages in various years, find the best predicted age of the Best Actor winner given that the age of the Best Actress winner that year is 29 years. Is the result within 5 years of the actual Best Actor winner, whose age was 51 years? Best Actress 27 30 30 60 30 34 44 29 65 23 45 56 D Best Actor 41 38 37 46 51 46 60 51 39 55 44 34 Find the equation of the regression line. (Round the y-intercept to one decimal place as needed. Round the slope to three decimal places as needed.)
Use the scatterplot of Vehicle Registrations below to answer the questions Vehicle Registrations in the United States, 1925- 2011 Vehicles millions 300 y = 3.0161x - 5819.5 R? = 0.9695 250 200 150 100 50 1920 -50 1940 1960 1980 2000 2020 Year Write a sentence explaining the value of the slope for this regression line. For every increase in year, the number of vehicle registrations in the US increases by 3.0161 million. For every increase in year, the number of vehicle registrations in the US increases by 5819.5. For every increase in vehicle registrations in the US, the number of years increases by 5819.5. For every increase in vehicle registrations in the US, the number of years increases by 3.0161 million. Registrations (in millions)
The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 40 inches. Is the result close to the actual weight of 352 pounds? Use a significance level of 0.05. Chest size (inches) *Weight (pounds) 44 54 328 528 41 55 39 51 418 580 296 503 Click the icon to view the critical values of the Pearson correlation coefficient r. - What is the regression equation? x (Round to one decimal place as needed.)
Suppose Ms. Carr is interested in the relationship between her students' 9th grade math final exam scores and the number of hours they spent studying during the year. She collects information for 15 ninth grade students and uses it to obtain the regression equation, where ?x is the number of hours spent studying during the year and ?̂ is the predicted final exam score. ?̂ =1.48?+75.64 The scatter plot displays her results. What is the predicted ?̂ value when a student spends 13 hours studying? Round your answer to one decimal place. Select the correct interpretation. The above predicted value of ?̂ is the predicted final math test score if a student studies 13 hours during the year. the predicted score of 13 out of 15 students. what any student will score on the final exam if they study at least 13 hours. the math final test score that 13 students beat.
Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed actress/actor ages in various years, find the best predicted age of the Best Actor winner given that the age of the Best Actress winner that year is 27 years. Is the result within 5 years of the actual Best Actor winner, whose age was 43 years? Best Actress 27 32 30 63 30 31 47 30 61 22 46 54 9 Best Actor 43 39 37 46 48 48 62 49 38 56 42 35
Find the GPA of a student if he gives average hours to study by using regression analysis. A random sample of ten students is selected from a class of 60 students, find regression line and also find the GPA of a student if he gives average hours to study by using this regression analysis. Their GPA and the hours to study are given below: GPA 2.5 3.1 3.6 3.2 2.9 3.7 2.9 2.4 3.3 3.5 Hours to study 3 5 7 5 3 8 4 2 5 7 Also interpret the regression coefficient.
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 valuo of v 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 762 621 508 480 (b) x = 641 feet (d) x = 726 feet 515 491 (a) x= 498 feet (c) x = 810 feet 51 46 44 42 38 37 Find the regression equation. ý=x+ (D (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) Choose the correct graph below. OA. OB O B. Oc. OD. 60- 604 60+ 800 B00 G 800 Height (feet) 800 Height (feet) 800 Height (feet) Height (feet) (a) Predict the value of y for x = 498. Choose the correct answer below. OA 40 ОВ. 50 O C. 47 O D. not meaningful (b) Predict the value of y for x 641. Choose the correct answer…
Use the pizza cost and the subway fare in the table below to find the regression equation, letting pizza cost be the predictor (x) variable. (Pizza cost is in dollars per slice, subway fare and CPI are in dollars.) What is the best predicted subway fare when pizza costs $3.91 per slice? Year 1960 1973 1986 1995 2002 2003 2009 2013 2015 2019 Pizza Cost 0.153 0.347 0.998 1.247 1.751 1.996 2.246 2.298 2.751 2.997 Subway Fare 0.149 0.347 1.001 1.347 1.500 1.996 2.252 2.548 2.753 2.748 CPI 29.6 44.4 109.6 152.4 180.0 184.0 214.5 233.0 237.0 252.2 Question content area bottom Part 1 The regression equation is y=enter your response here+enter your response herex. (Round the y-intercept to four decimal places as needed. Round the slope to three decimal places as needed.) Part 2 The best predicted subway fare when pizza costs $3.91per slice is $enter…
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 1 2 2 Test score, y 39 45 50 48 3 5 6 62 72 (a) x = 2 hours (c) x = 15 hours (b) x = 3.5 hours (d) x = 4.5 hours Find the regression equation. y = x+ y= (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.)

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