9. The (incomplete) table below shows the x and y values for three data points. It also showsthe estimated coefficients, predicted y values and residuals for two potential regression lines(A and B). Fill in the missing values in the table below.obs1W23231009080706050403020100y602001X328Using the values you just calculated, plot the three data points and the two estimatedregression equations in the graph below. Be sure to label everything clearlyVA40503aAABARegression AUA4-30-15510YB64060BRegression BAВв7UB25-2015820910

Here for the given data on x & y variables. We have derived 2 estimated lines A & B which…

9. The (incomplete) table below shows the x and y values for three data points. It also shows the estimated coefficients, predicted y values and residuals for two potential regression lines (A and B). Fill in the missing values in the table below. obs 123 100 90 80 y 60 20 70 X 3 8 VA 40 50 UA aA A ВА -30 -15 Regression A 10 VB Using the values you just calculated, plot the three data points and the two estimated regression equations in the graph below. Be sure to label everything clearly 40 60 UB 25 -20 15 Regression B αB 20 A Вв

9. The (incomplete) table below shows the x and y values for three data points. It also shows the estimated coefficients, predicted y values and residuals for two potential regression lines (A and B). Fill in the missing values in the table below. obs 123 100 90 80 y 60 20 70 X 3 8 VA 40 50 UA aA A ВА -30 -15 Regression A 10 VB Using the values you just calculated, plot the three data points and the two estimated regression equations in the graph below. Be sure to label everything clearly 40 60 UB 25 -20 15 Regression B αB 20 A Вв

ENGR.ECONOMIC ANALYSIS

14th Edition

ISBN:9780190931919

Author:NEWNAN

Publisher:NEWNAN

Chapter1: Making Economics Decisions

Section: Chapter Questions

Problem 1QTC

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You are given information on the use of public transportation in the data set within the image. Number of weekly riders y -variable Price per week (of using public transportation) x-variable Population of city x-variable Monthly income of riders x variable Average parking rates per month x-variable (a) Run a regression of the Number of weekly riders on Price per week, Population of city, Monthly income of riders, Average parking rates per month. Please copy and paste your regression results and do not submit your EXCEL worksheet. (b) If the average parking rates increase by $1, what will be the change in the number of weekly riders? Will this change be a statistically significant change? Please explain. (c) If the price per week (of using public transportation) increases by $1, what will be the change in the number of weekly riders? Will this change be…
4.
b. The following model is a simplified version of the multiple regression model used by BEST Econometrics Group to study the trade off between time spent sleeping and working to look at other factors affecting sleep: sleep Bo + B₁totwrk + B₂educ + Page + μ₁ where sleep and totwork (total work) are measure in minutes per week and educ and age are measured in years. (i) If adults trade sleep for work, what is the sign of B₁? (ii) What signs do you think ₂ and 3 will have? (iii) Using the data in SLEEP75.RAW, the estimated equation is sleep = 3,638.25-.148totwrk-11.13educ - 2.20age, n = 706, R² = .113 If someone works five hours per week, by how many minutes is sleep predicted to fall? Is this a large tradeoff? (iv) Discuss the sign and magnitude of the estimated coefficient on educ (v) Would you say totwrk, educ, and age explain much of the variation in sleep? (vi) What other factors might affect the time spent sleeping? (vii) Are these likely to be correlated with totwrk?
7. The Stata data set "college_gpa" has data on students' college GPAS, high school GPAS, ACT scores, lectures skipped during the academic year, and other characteristics. We wish to examine the predictors of college GPAS. You must submit your do-file (commands). a) Regress college GPA on high school GPA and write the estimated regression line. b) Interpret the intercept of your regression in a sentence. Does this coefficient make sense?n Explain c) Interpret the coefficient on high school GPA in a sentence. Does this coefficient make sense? Explain. reg colGPA hsGPA Source df MS Number of obs 141 %3D F(1, 139) 33.80 Model 5.58478164 1 5.58478164 Prob > F e.0000 Residual 22.9668501 139 .165229138 R-squared Adj R-squared 0.1956 %3D 0.1898 %3D Total 28.5516318 140 .203940227 Root MSE .40648 colGPA Coef. Std. Err. t P>|t| [95% Conf. Interval] hsGPA .6242948 .1073816 5.81 0.000 .4119822 .8366073 _cons 890254 3669263 2.43 0.017 647755
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What are the measures of fit that are commonly used for multiple regressions? How can an adjusted R2 take on negative values?
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1. Suppose output (Q) is related to labor (L) and capital (K) in the following nonlinear way: Q = albKc When taking log to this equation, it is transformed into a linear LnQ = Ina + b In(L) + c Ln (K) One hundred twenty-three observations are used to obtain the following regression results: Dependant Variable: Observations: Variable Intercept L K Q 123 5.5215 Parameter Standard Estimate error 0.650 R-square 0.350 0.7547 0.9750 0.2950 0.1450 F-ratio 184.56 t-ratio 5.66 2.20 2.41 p-value on F 0.00001 p-value 0.0001 0.0295 0.0173 a. Write the regression equation based on the output either in the transformed linear form or the original non-linear form.
SSE SST X₂ The estimated regression equation for these data is ŷ = 7.6 +0.9x. Compute SSE, SST, and SSR (to 1 decimal). SSR 2 7 6 18 9 13 20 9 26 23 What percentage of the total sum of squares can be accounted for by the estimated regression equation (to 1 decimal)? % What is the value of the sample correlation coefficient (to 3 decimals)?
number 1 please
Question 2 A Full explain this question and text typing work only We should answer our question within 2 hours takes more time then we will reduce Rating Dont ignore this line