An educator wants to see the number of absences(X) a student in her class has affects theStudent's final GPA(Y)a) Find Correlation coefficienteb) Draw a Scatter plot (Ic) Find the Regression equation of Y on Xd) Predict the student's GPA when X = 6X45283107y2.52.342.13.31.72.3

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Answered: An educator wants to see the number of…

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 table below gives the number of hours spent unsupervised each day as well as the overall grade averages for five 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 0 1 3 4 5 Overall Grades 95 92 85 81 62 Table Step 3 of 6 : Determine if the statement "Not all points predicted by the linear model fall on the same line" is true or false.
7. The table below shows the round-trip fare for flights from one city on major airlines. These were the lowest prices found online in early 2010. The airlines varied, but the travel dates were all the same. Determine the linear regression for the cost of a round-trip ticket given the distance traveled, use your regression to estimate the cost of a 1500-mi flight, and state the correlation coefficient, r, and describe the trend, shape, and strength for the data contained in this problem. Distance (mi.) Cost ($) 205 183 968 180 3097 598 1939 277 1976 313 1033 318 2977 448 1752 408 1143 335
The manager of a car dealership wants to predict the relationship between number of sales persons and the number of cars sold. He collects some data to develop a regression model, which is given below Week Number of cars sold Number of salespersons 1 80 6 2 90 8 3 48 4 4 55 5 5 60 7 6 75 9 7 100 11 8 70 6 9 65 7 10 98 10 (i) Run a regression analysis which explains the number of cars sold in terms of number of salespersons, and estimate the regression line (ii) Interpret the regression coefficient, and determine the significance of the regression coefficient (iii) Interpret the overall model fit…
The equation of a regression line, unlike the correlation, depends on the units we use to measure the explanatory and response variables. Here is the data on percent body fat and preferred amount of salt. Preferred amountof salt x 0.2 0.3 0.4 0.5 0.6 0.8 1.1 Percent body fat y 21 30 23 30 39 24 31 In calculating the preferred amount of salt, the weight of the salt was in milligrams. (a) Find the equation of the regression line for predicting percent body fat from preferred amount of salt when weight is in milligrams. (Round your answers to one decimal place.) ŷ = + x (b) A mad scientist decides to measure weight in tenths of milligrams. The same data in these units are as follows. Preferred amountof salt x 2 3 4 5 6 8 11 Percent body fat y 21 30 23 30 39 24 31 Find the equation of the regression line for predicting percent body fat from preferred amount of salt when weight is in tenths of milligrams. (Round your intercept to one decimal place and your slope to two…
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Last years Data Management class decided to see if there was a relationship between the score (out of 10) a student got on the two-variable stats quiz, and their score (out of 30) on the unit test. Use the given data to Quiz Score Test Score 6 8 10 9 10 20 26 29 26 30 a) Calculate the correlation coefficient. b) Perform a linear regression.
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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 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 table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven 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 0.5 1 2.5 3 4 5 5.5 Overall Grades 98 95 90 79 75 69 66 Step 1 of 6: Find the estimated slope. Round your answer to three decimal places. Step 2 of 6: Find the estimated y-intercept. Round your answer to three decimal places. Step 3 of 6: Determine if the statement "Not all points predicted by the linear model fall on the…
you are going to buy some calves. What should a healthy weight be? let x be the age of the calf (in weeks), and let y be the weight of the calf (in kg) the calves you want to buy are 12 weeks old. Predict the healthy weight you should expect. x=1 3 10 16 26 36 y=42 50 75 100 150 200 state the correlation coefficient and regression line equation.
Use the regression equation to predict the value of y for x = - X y -5 - 3 4 11 6 - 6 A. 7.921 B. - 0.995 C. -4.765 O D. -6.405 1 - 1 - 1 3 - 2 0 4 1 2 - 4 3 -5 -3.8. Assume that the variables x and y have a significant correlation. - 4 8
If a correlation isr= 0.00, then SP = 0 and the regression equation is O Ý =X +0 O Ý =X + X O Ý =0 + X O Ý =Ÿ + 0

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An educator wants to see the number of absences(X) a student in her class has affects the Student's final GPA(Y) a) Find Correlation coefficiente b) Draw a Scatter plot (A c) Find the Regression equation of Y on X d) Predict the student's GPA when X = 6 X 4 5 2 8 3 10 7 y 2.5 2.3 4 2.1 3.3 1.7 2.3