A Math teacher wishes to determine if the number of absences a student incurs correlates with his or her general weighted average. She chose a sample of 7 students and then surveyed their GWA and number of absences. 1 2 Number of Absences (x) GWA (y) 3 7. 10 97.8 90.2 86.4 87.3 85.4 84.5 78.2 Find the equation of the regression line and predict the GWA of a student who incurred 6 absences.

A Math teacher wishes to determine if the number of absences a student incurs correlates with his or her general weighted average. She chose a sample of 7 students and then surveyed their GWA and number of absences. 1 2 Number of Absences (x) GWA (y) 3 7. 10 97.8 90.2 86.4 87.3 85.4 84.5 78.2 Find the equation of the regression line and predict the GWA of a student who incurred 6 absences.

Name: A Math teacher wishes to determine if the number of absences a studen
Uploaded: 2024-03-20T07:06:41.000Z
Channel: Bartleby
Description: A Math teacher wishes to determine if the number of absences a studentincurs correlates with his or her general weighted average. She chose asample of 7 students and then surveyed their GWA and number of absences.5 7Number ofAbsences (x)GWA (y)91097

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

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 1.5 2.5 3 3.5 4.5 Overall Grades 97 96 88 83 77 70 63 Find the estimated value of y when x=3. Round your answer to three decimal places.
please do all parts! The estimated regression equation for this data set is y=4.4878+1.9549x. Part A: (in image) Part B: is the linear function is the appropriate regression function for this data set? Part C: do the residuals have a constant variance? Part D: are the residuals independent? Part E: are the error terms are normally distributed? y x22 821 818 846 2241 2254 2276 3258 3268 32
The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, y = bo + bjx, for predicting a woman's bone density based on her age. 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. Age 47 49 50 51 58 Bone Density 360 353 336 333 310 Table Copy Data Step 3 of 6: Find the estimated value of y when x = 58. Round your answer to three decimal places.
The systolic blood pressure of individuals is thought to be related to both age and weight. Let the systolic blood pressure, age, and weight be represented by the variables x1, x2, and x3, respectively. Suppose that Minitab was used to generate the following descriptive statistics, correlations, and regression analysis for a random sample of 15 individuals. Relative to its mean, which variable has the greatest spread of data values?
A regional retailer would like to determine if the variation in average monthly store sales can, in part, be explained by the size of the store measured in square feet. A random sample of 21 stores was selected and the store size and average monthly sales were computed. Complete parts a through c. Use a significance level of 0.10 where needed. 1 Click the icon to view the data table between the store size and average monthly sales. Compute the simple linear regression model using the sample data to determine whether variation in average monthly sales can be explained by store size. What is the linear regression model based on the sample data? y= +( )x(Type integers or decimals rounded to two decimal places as needed.) Interpret the slope coefficient. Select the correct choice below and fill in the answer box to complete your choice. (Type an integer or decimal rounded to two decimal places as needed.) For each additional square foot of store size,…
How do you find the best predicated number of viewers for a television star with a salary of 10 million ?
A professor obtains SAT scores and freshman grade point averages (GPAs) for a group of n = 15 college students. The SAT scores have a mean of M = 580 with SS = 22,400, and the GPAs have a mean of 3.10 with SS = 1.26, and SP = 84. Find the regression equation for predicting GPA from SAT scores. What percentage of the variance in GPAs is accounted for by the regression equation? (Compute the correlation r, then find r^2.) Does the regression equation account for a significant portion of the variance in GPA? Use α = .05 to evaluate the F-ratio.
The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting a woman's bone density based on her age. 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. Age 47 48 56 60 67 Bone Density 359 350 334 314 313 Find the estimated y-intercept. Round your answer to three decimal places.
A professor at the University of Alabama was interested in evaluating the relationship between family support and delinquency. Using data collected on 4545 families, the researcher used regression to analyze the relationship. The results are presented below. Variables Entered/Removeda Model Variables Entered Variables Removed Method 1 Family supportb . Enter a. Dependent Variable: Delinquency b. All requested variables entered. Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .249a .062 .062 1.59168 a. Predictors: (Constant), Family support ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 759.204 1 759.204 299.671 <.001b Residual 11479.107 4531 2.533 Total 12238.311 4532 a. Dependent Variable: Delinquency b. Predictors: (Constant), Family support…
The options for part b are: head circumference or height
The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting a woman's bone density based on her age. 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. Age 47 48 56 60 67 Bone Density 359 350 334 314 313 Find the estimated slope. Round your answer to three decimal places.
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 0.5 2 3 4.5 5 6 Overall Grades 99 98 96 92 89 88 80 Table Step 6 of 6 : Find the value of the coefficient of determination. Round your answer to three decimal places.