a) State the estimated OLS regression and interpret the slope coefficients.b) Test at 5% significance level whether or not the coefficient on GNP is significantlyless than one.c) Test at 5% significance level whether or not the coefficient on military sales/assistanceis significant. In order to explain the U.S. defense budget, the following variables are considered. Data from1962-1981 is collected.VariableDefinitionYDefense budget-outlay for year t, $ billionsX2GNP for year t, $ billionsX3U.S. military sales/assistance in year t, $ billionsX4Aerospace industry sales, $ billionsDependent Variable: YMethod: Least SquaresDate: 11/22/21 Time: 11:20Sample: 1962 1981Included observations: 20VariableCoefficientStd. Errort-StatisticProb.X20.0167030.0070172.3802610.0301X3-0.6961740.453978-1.5334970.1447X41.4677290.2776085.2870470.000122.775143.3116956.8771860.0000R-squared0.971088Mean dependent var83.86000Adjusted R-squared0.965667S.D. dependent var28.97771S.E. of regressionSum squared resid5.369339Akaike info criterion6.376143461.2769Schwarz criterion6.575290Log likelihood-59.76143Hannan-Quinn criter.6.415019F-statistic179.1337Durbin-Watson stat0.676777Prob(F-statistic)0.000000

The result of OLS regression model for dependent variable Defense budget - outlay for year and…

Answered: a) State the estimated OLS regression…

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

Show that an interaction term of a dummy variable and a regressor changes the slope of a regression line..
Use the summary statistics to calculate the regression line for this data. Explain each coefficient. What is the total amount of weight would you expect a weightlifter with a body weight of 84kg to lift? At the 5% significance level, is there evidence that the body weight of the athlete is a useful predictor for the total amount an athlete can lift? Assume the assumptions can be verified.
Define the term Sample Correlation? why it is used in linear equation?
1. Which one can describe the regression estimation? A) Predict the mean value of the dependent variable bascd on valucs of the cxplanatory variables. B) Predict the mcdian valuc of the dependent variable based on valucs of the explanatory variables. C) Predict the mcan valuc of the independent variables on the basis of the dependent variable. D) Predict the median value of the independent variables on the basis of the dependent variable.
A regression model to predict Y, the state burglary rate per 100,000 people, used the following four state predictors: X1 = median age, X2 = number of bankruptcies per 1,000 population, X3 = federal expenditures per capita (a leading predictor), and X4 = high school graduation percentage. Click here for the Excel Data File (a) Using the sample size of 45 people, calculate the tcalc and p-value in the table given below. (Negative values should be indicated by a minus sign. Leave no cells blank - be certain to enter "0" wherever required. Round your t-values to 3 decimal places and p- values to 4 decimal places.) Predictor Intercept AgeMed Coefficient SE tcalc p-value 4,641.0430 798.0634 -28.8630 12.4684 Bankrupt 20.1604 12.1079 FedSpend HSGrad% -0.0181 0.0181 -30.3196 7.1136 (b-1) What is the critical value of Student's tin Appendix D for a two-tailed test at a = .01? (Round your answer to 3 decimal places.) -value =
It was proposed that a study be conducted on the number of start- ups and annual number of business bankruptcies. Data collected was six year period. Develop regression equation and forecast the bankruptcy numbers given the start ups for the forthcoming year to be 60. Interpret the significance of predictor through R Square Business Bankruptcies Start ups (in 1000) 34.3 58.1 35 55.4 38.5 57 40.1 58.5 35.5 57.4 37.9 58
What mean physical health score would you expect in a group of 28-year-old women with a graduate degree?
Hypertension The investigators for a study collected standardized data on timed 24-hour urinary excretion for 10,079 men and women from 52 population samples in 32 countries. One of the goals of the study was to quantify the relationship between 24-hour urinary Na (y) and estimated 24-hour urinary Na (x) obtained from casual urine specimens at one point in time. The investigators presented a simple linear regression of y on x, separately for men and women. The regression equation for men was: Y = 1.09x - 7.11, with R² = 0.26, n = 1,369 Hint: Assume that a t distribution with > 200 df is the same as a N(0, 1) distribution. You can use the Distribution Calculators page in SALT to find critical values and/or p-values to answer parts of this question. (a) What does the R² of 0.26 mean in words? R²: = 0.26 means that about 74% of the time the estimated 24-hour urinary Na matches the 24-hour urinary Na obtain from casual urine specimens at one point in time. R² = 0.26 means that about 26% of…
Consider a linear regression model that relates school expenditures and family background to student performance in Massachusetts using 224 school districts. The response variable is the mean score on the MCAS (Massachusetts Comprehensive Assessment System) exam given in May 1998 to 10th-graders. Four explanatory variables are used: (1) STR is the student-to-teacher ratio, (2) TSAL is the average teacher’s salary, (3) INC is the median household income, and (4) SGL is the percentage of single family households. The Excel Regression output for the sample regression equation is given below. (a) What proportion of the variation in MCAS score is explained by the explanatory variables? (b) At the 5% level, are the explanatory variables jointly significant in explaining MCAS score? Explain briefly. (c) At the 5% level, which variables are individually significant at predicting MCAS score? Explain briefly. (d) Suppose a second regression model (Model 2) was generated using only…
A nonprofit analyst considered two independent variables as a predictor for the dependent variable Commitment, the percent of total expenses that are allocated to charitable services. The independent variables are Revenue, total revenue in billions of dollars, andEfficiency, the percent of private donations remaining after fundraising expenses. The regression analysis resulted in this ANOVA table. Determine whether there is a significant relationship between commitment and the two independent variables at the 0.01 level of significance. Source Degrees of Freedom Sum of Squares Mean Square F p-value Regression 2 3640.0416 1820.02 51.0429 <.0001 Error 87 3102.1301 35.66 Total 89 6742.1717 Determine the p-value. The p-value is ________ (Round to three decimal places as needed.)
. Is the male–female earnings difference estimated from this regressionstatistically significant at the 5% level? Construct a 95% confidenceinterval for the difference.
Last ride Consider the roller coasters described inExercise 26 again. The regression analysis gives themodel Duration = 64.232 + 0.180 Drop.a) Explain what the slope of the line says about howlong a roller coaster ride may last and the height of thecoaster.b) A new roller coaster advertises an initial drop of200 feet. How long would you predict the rides last?c) Another coaster with a 150-foot initial drop advertisesa 2-minute ride. Is this longer or shorter than you’dexpect? By how much? What’s that called?

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

a) State the estimated OLS regression and interpret the slope coefficients. b) Test at 5% significance level whether or not the coefficient on GNP is significantly less than one. c) Test at 5% significance level whether or not the coefficient on military sales/assistance is significant.