Suppose that based on a sample of high schools, a researcher estimatesvia OLS the regression modelYi = 30,1 + 2,0,2 + x3,130,3 + x4,iß0,4 + Uiwhere y, denotes the percentage of students passing the grade 10 mathtest in high school i, x2, denotes average annual teacher compensation inhigh school i, 3, denotes 1000 * (staff to student ratio) in high school i and4,i denotes student enrollment in high school i. Part of the Stata output isgiven on the following page. Using this output, test whether the data areconsistent with the belief that an increase in the staff to student ratio leadsto an increase in the percentage of students that pass the grade 10 mathtest. Be sure to justify your conclusion clearly.Stata output for Question 2(c):Source ITotal ISSModel | 2422.934343Residual | 42394.2462 404y Idf44817.1805 407Coef.x_2 I. 0004586x_31.0479199-.0001976x_4 |_cons | 2.274021807.644779104.936253MS110.115923Std. Err..0001004.039814.00021526.113794t P>|t|4.57 0.0001.20 0.229-0.92 0.3590.37 0.710Number of obs =F( 3, 404) =Prob > FR-squaredAdj R-squaredRoot MSE4087.700.0001= 0.05410.0470= 10.244.0002613-.0303487-.0006207-9.744801=[95% Conf. Interval].0006559.1261884.000225514.29284

Given information:k= 3 independent variablesn= 408 observation

Answered: Suppose that based on a sample of high…

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

3. Solve for B. The accompanying data are from a football league for one season. Use the regression tool to develop a model for predicting points/game as a function of yards/game. Explain the statistical significance of the model and the r^2 value. Solve for B Develop a mod for predicting points/game as a function of yards/game. Points/game= -20.892 + (.131) x yards/game. To Explain the statistical significance of the model first state the appropriate null and alternative hypotheses. H0 : H1: SEE PICTURE
I have modeled adult worker's salaries based upon their work experience. After surveying 200 adults about their salary and years in the workforce, I have found the following model: y=12000+5000*x where y is the predicted salary and x is the years in the labor force. R^2 = 0.63. What is the correlation for this model? (correlation between salary and years in the labor force)? a. 0 b. 0.79 c. 0.63 d. 0.50 e. 1
A researcher collects data between the age in years, (x), of a movie theater's popcorn popper and the cost of its monthly maintenance,(y).Find the regression equation. Round b to three decimal places.ˆyy^ = + CorrectxxFill in the table to find the residuals. Round table entries to three decimal places. xx yy ˆyy^ y−ˆyy-y^ 8 58 9 98 15 102 4 32 7 60 3 31 2 25 What is the correlation coefficient? Round to three decimal places. Graph the data and find the outlier. Give the ordered pair here:(, )If your ordered pair is actually the outlier, then the correlation coefficient would increase. Delete the ordered pair you chose and find the correlation coefficient again. Type the new correlation coefficient rounded to three decimal places here: Put the outlier back into your data and then find the test statistic, p-value, df, and critical value(s) for a test to find if there is a positive correlation with α=0.01α=0.01. Round to 3 decimal placestt…
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^=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. Find the estimated value of y when x=52. Round your answer to three decimal places. age 35 41 52 56 66 bone density 358 350 348 332 321
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+b1xy^=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 00 0.50.5 11 1.51.5 22 3.53.5 44 Overall Grades 8989 8181 7373 7272 6969 6767 6363 Table Copy Data Step 6 of 6: Find the value of the coefficient of determination. 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+b1xy^=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 1.51.5 2.52.5 33 44 4.54.5 55 66 Overall Grades 9494 9292 8282 7979 7171 7070 6262 Find the value of the coefficient of determination. Round your answer to three decimal places.
A researcher found a linear correlation between course grades and the average number of hours spent on a mobile phone each day. The line of best fit has equation y ^ = 3.7 − 0.786 x with correlation coefficient r = − 0.84. a. Does this prove that spending too much time on a phone causes students to get lower grades? b. What does the regression line predict your final grade in a course will be if you spend an average of 150 minutes per day on your phone?
A study in the univeristy of massachusetts amherst published in the may 2007 journal of marriage and family found that married women do about one fewer hour of housework a week for every $7500 they earn as a full time workers outside of the home, regardless of their husband's income A) what would be the numerical value of the slope coefficient in the regression model that predicts womens housework hours from their income? what does the sign of the slope (positive or negative) tell us about the relationship between these variables B) Suppose Lynette's salary is $30,000 greater than Gabriells. what would you predict the difference in hours of housework they each do.
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�^=�0+�1�, 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 00 11 1.51.5 22 2.52.5 44 4.54.5 Overall Grades 9797 9393 8585 7474 7272 7171 6666 Table Copy Data Step 1 of 6 : Find the estimated slope. Round your answer to three decimal places.
Consider the following population model for household consumption: cons = a + b1 * inc+ b2 * educ+ b3 * hhsize + u where cons is consumption, inc is income, educ is the education level of household head, hhsize is the size of a household. Suppose a researcher estimates the model and gets the predicted value, cons_hat, and then runs a regression of cons_hat on educ, inc, and hhsize. Which of the following choice is correct and please explain why. A) be certain that R^2 = 1 B) be certain that R^2 = 0 C) be certain that R^2 is less than 1 but greater than 0. D) not be certain
The table below gives the number of hours seven randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=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 2 2.5 3 3.5 4 4.5 5 Midterm Grades 72 74 80 82 87 88 93 Determine if the statement "Not all points predicted by the linear model fall on the same line" is true or false.
7

SEE MORE QUESTIONS

Recommended textbooks for you

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

Elementary Statistics: Picturing the World (7th E…

Statistics

ISBN:

9780134683416

Author:

Ron Larson, Betsy Farber

Publisher:

PEARSON

The Basic Practice of Statistics

Statistics

ISBN:

9781319042578

Author:

David S. Moore, William I. Notz, Michael A. Fligner

Publisher:

W. H. Freeman

Introduction to the Practice of Statistics

Statistics

ISBN:

9781319013387

Author:

David S. Moore, George P. McCabe, Bruce A. Craig

Publisher:

W. H. Freeman

SEE MORE TEXTBOOKS