According to the nutrition research, recommendation on the consumption of fiber for children and teenagers is the following ( y is theamount of fiber per day (in grams), x is the age):y 21 24 26 28 29 33 | 38 43 442468 10 12| 14 16 | 18X0.1. Can you conclude that the model specifies a(a) Test for the significance of regression using the analysis of variance with a =useful linear relationship between these two variables?Weconclude that the model specifies a useful linear relationship at a = 0.1.(b) Estimate o?.Round your answer to three decimal places (e.g. 98.765).2%D(c) Estimate the standard error of the slope and intercept in this model.Round your answers to three decimal places (e.g. 98.765).se( B1)ise( B o) =i

Answered: Image /qna-images/answer/b3cb5cdd-32bf-4eae-a6b7-c6861abfe0d6.jpg

Answered: According to the nutrition research,…

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 4 of 6 : Find the estimated value of y when x=3. Round your answer to three decimal places. Answer How to enter your answer (opens in new window)
According to the nutrition research, recommendation on the consumption of fiber for children and teenagers is the following (y is the amount of fiber per day (in grams), x is the age): y 20 22 26 29 31 33 37 40 41 2 4 6 8 10 12 14 16 18 ४ = (a) Test for the significance of regression using the analysis of variance with a useful linear relationship between these two variables? We (b) Estimate ². Round your answer to three decimal places (e.g. 98.765). (c) Estimate the standard error of the slope and intercept in this model. Round your answers to three decimal places (e.g. 98.765). (B₁) se (Bo) se B = = conclude that the model specifies a useful linear relationship at a = 0.05. Mo 0.05. Can you conclude that the model specifies a
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 1 2 3 4 4.5 5 5.5 Overall Grades 98 95 93 90 89 72 69 Table Copy Data Step 2 of 6 : Find the estimated y-intercept. Round your answer to three decimal places.
The accompanying data represent the weights of various domestic cars and their gas mileages in the city. The linear correlation coefficient between the weight of a car and its miles per gallon in the city is r= - 0.972. The least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable is y= - 0.0070x + 44.4405. Complete parts (a) and (b) below. Click the icon to view the data table. ..... (a) What proportion of the variability in miles per gallon is explained by the relation between weight of the car and miles per gallon? The proportion of the variability in miles per gallon explained by the relation between weight of the car and miles per gallon is %. (Round to one decimal place as needed.) (b) Interpret the coefficient of determination. % of the variance in is by the linear model. Data Table (Round to one decimal p Full data set gas mileage Miles per Weight (pounds), x Weight (pounds), x Miles per Gallon, y Car Car Gallon, y…
The following data shows memory scores collected from adults of different ages. Age (X) Memory Score (Y) 25 10 32 10 39 9 48 9 56 7 Use the data to find the regression equation for predicting memory scores from age. The regression equation is: Ŷ = 4.33X + 0.11 Ŷ = -0.11X + 4.33 Ŷ = -0.11X + 13.26 Ŷ = -0.09X + 5.4 Ŷ = -0.09X + 12.6 Use the regression equation you found in question 6 to find the predicted memory scores for the following age: 28 For the calculations, leave two places after the decimal point and do not round: Use the regression equation you found in question 6 to find the predicted memory scores for the following age: 43 For the calculations, leave two places after the decimal point and do not round: Use the regression equation you found in question 6 to find the predicted memory scores for the following age: 50 For the calculations, leave two places after the decimal point and do not round:
The table below gives the number of hours ten randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. 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 Studying 0 0.5 1.5 2 2.5 3 4.5 5 5.5 6 Midterms Grades 60 63 64 69 73 76 82 90 91 95 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 "All points predicted by the linear model fall on the same line" is true or false Step 4 of 6:…
A small independent organic food store offers a variety of specialty coffees. To determine whether price has an impact on sales, the managers kept track of how many kilograms of each variety of coffee were sold last month. The data and summary statistics (including the averages, standard deviations and the correlation coefficient) are shown in the table. If the "price per kilogram" is the predictor variable and "kilograms sold" is the response variable, then use a regression line to predict the the amount of kilograms sold for a "price per kilogram" equal to $15. Round your numbers to 3 decimal places.
4. A runner was tested on a treadmill. During the test, his speed x (in km/h) and his heart rate y were measured. The results are shown in the table. y 122 132 145 161 178 190 x 8 10 12 14 16 18 (a) Test for the significance of regression using the analysis of variance with a = 0.05. Find the P-value for this test. Can you conclude that the model specifies a useful linear relationship between these two variables? (b) Estimate ². (c) Estimate the standard error of the slope and intercept in this model. (d) Test the hypothesis that the increase in the speed of 1 km/h results in the runner's heart rate average increase of 7 points at a = 0.05. Suppose that the alternative hypothesis is that the average increase of the runner's heart rate in this situation does not equal 7 points.
A researcher is interested in examining the relationship between spousal abuse and child abuse. Specifically, they are interested in determining whether there is a predictive relationship between spousal abuse and child abuse in 5 county social services offices. Calculate the linear regression line for the following data. Note you have already calculated the first step to this analysis (Pearson's Correlation)
The table below gives the number of hours five randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, y = bo + b₁x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. 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 Studying 0 1 2 3 5 Midterm Grades 68 69 73 77 85 Step 6 of 6: Find the value of the coefficient of determination. Round your answer to three decimal places. Table Copy Data
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 2 3 5 6 Overall Grades 90 89 87 77 61 Table Step 2 of 6 : Find the estimated y-intercept. Round your answer to three decimal places.
B b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables? The scatter diagram indicates a positive linear relationship between a = average number of passing yar and y = the percentage of games won by the team. c. Develop the estimated regression equation that could be used to predict the percentage of games won given the avera passing yards per attempt. Enter negative value as negative number. WinPct =| |)(Yds/Att) (to 4 decimals) d. Provide an interpretation for the slope of the estimated regression equation (to 1 decimal). The slope of the estimated regression line is approximately So, for every increase : of one yar number of passes per attempt, the percentage of games won by the team increases by %. e. For the 2011 season, the average number of passing yards per attempt for the Kansas City Chiefs was was 5.5. Use th regression equation developed in part (c) to predict the percentage of games won by the Kansas City Chiefs.…

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