Consider the simple linear regression model given by E(y) = 1.5 + 0.23*x where y is measured in litres and x is measured in dollars. What must be the value of the slope coefficient if x is measured in thousands of dollars while the unit of measurement of y is unchanged (i.e., x is divided by 1000)? Answer:

Consider the simple linear regression model given by E(y) = 1.5 + 0.23*x where y is measured in litres and x is measured in dollars. What must be the value of the slope coefficient if x is measured in thousands of dollars while the unit of measurement of y is unchanged (i.e., x is divided by 1000)? Answer:

Survey Of Economics

10th Edition

ISBN:9781337111522

Author:Tucker, Irvin B.

Publisher:Tucker, Irvin B.

Chapter1: Introducing The Economic Way Of Thinking

Section1.A: Applying Graphs To Economics

Problem 7SQ

See similar textbooks

Similar questions

How do you interpret the R-squared obtained from running this regression?
As an auto insurance risk analyst, it is your job to research risk profiles for various types of drivers. One common area of concern for auto insurance companies is the risk involved when offering policies to younger, less experienced drivers. The U.S. Department of Transportation recently conducted a study in which it analyzed the relationship between 1) the number of fatal accidents per 1000 licenses, and 2) the percentage of licensed drivers under the age of 21 in a sample of 42 cities. Your first step in the analysis is to construct a scatterplot of the data. FIGURE. SCATTERPLOT FOR U.S. DEPARTMENT OF TRANSPORATION PROBLEM U.S. Department of Transportation The Relationship Between Fatal Accident Frequency and Driver Age 4.5 3.5 3 2.5 1.5 1 0.5 6. 10 12 14 16 18 Percentage of drivers under age 21 Upon visual inspection, you determine that the variables do have a linear relationship. After a linear pattern has been established visually, you now proceed with performing linear…
Numerical Answer Only Type Question Enter the numerical value only for the correct answer in the blank box. If a decimal point appears, round it to two decimal places. Assume that the number of visits by a particular customer to a mall located in downtown Toronto is related to the distance from the customer's home. The following regression analysis shows the relationship between the number of times a customer visits(Y)per month and the distance(X, measured in km) from the customer's home to the mall. \[ Y=15-0.5 X \] A customer who lives30 kmaway from the mall will visi______ who lives10 km away. less times than a customer
How should I interpret the coefficients on a regression with a naural log of a dependent variable? Ex: Ln(wage)=B1+B2Experience+B3Male...+Ui
A scatter plot shows data for the cost of a vintage car from a dealership (y in dollars) in the year a years since 1990. The least squares regression line is given by y-25,000 + 500z. Interpret the y intercept of the least squares regression line. Select the correct answer below O The predicted cost of a vintage car from a dealership in the year is 820.000 O The predicted cost of a vintage car from a dealershpin the year 1090 is 85,000. O The predicted cost of a vintage car from a dealershp in the year 1990 is sse. The yintercept should not be interpreted.
Consider the following data regarding students' college GPAs and high school GPAs. The estimated regression equation is GPA). Estimated College GPA = 2.56 + 0.1582 High School GPA GPAs College GPA High School GPA 3.96 4.42 2.81 3.91 3.53 4.21 3.27 2.76 3.58 4.95 2.07 4.24 Copy Data Step 2 of 3: Compute the mean square error (s2) for the model. Round your answer to four decimal places.
26) Consider the following regression line: i= -7.29 + 1.93 x YearsEducation. You are told that the t-statistic on the slope coefficient was 24.125. What is the standard error of the slope coefficient? (assume 5% level of significance) A. -0.08 B. 0.30 C. 1.64 D. 0.08
1. Consider a linear regression model y = XB + € with E(e) = 0. The bias of the ridge estimator of 3 obtained by minimizing Q(B) = (y — Xß)¹ (y — Xß) + r(BTB), for some r > 0, is ——(X²X + r1)-¹8 1 (X¹X +rI)-¹3 r -r(XTX+rI) ¹8 r(X¹X+r1) ¹3
5. The following estimated equation was obtained by OLS regression using quarterly data for 1978 to 1996 inclusive. Yt = 2.20+ 0.104Xt₁ - 3.48 Xt₂ + 0.34Xt3 (3.4) (0.005) (2.2) (0.15) Standard errors are in parentheses, the explained sum of squares was 109.6, and the residual sum of squares 18.48. a. Test at the 5% level for the statistical significance of the parameter estimates. b. Calculate the coefficient of determination.
Time left U:18:05 CLEAR MY CHOICE Finish a Question Consider the following model Y=B1+B2 X2 +e. Assume you change the scale of the y and X variables in such a way that Not yet Y*=aY and X2*=bX2. and you run the regression Y*=B1*+B2* X". What effect this scaling will have on answered the slope Marked out of 1.00 Select one: P Flag O a. B2=a+b (B2) question O b. B2*=a/b^2 (B2) O c. B2*-ab (B2) O d. B2*=a/b (B2) NEXT PAGE PREVIOUS PAGE
The table to the right contains price-demand and total cost data for the production of projectors, where p is the wholesale price (in dollars) of a projector for an annual demand of x projectors and C is the total cost (in dollars) of producing x projectors. Answer the following questions (A) - (D). (A) Find a quadratic regression equation for the price-demand data, using x as the independent variable. X 270 360 520 780 The fixed costs are $. (Round to the nearest dollar as needed.) ITTI y = (Type an expression using x as the variable. Use integers or decimals for any numbers in the expression. Round to two decimal places as needed.) Use the linear regression equation found in the previous step to estimate the fixed costs and variable costs per projector. The variable costs are $ per projector. (Round to the nearest dollar as needed.) (C) Find the break even points. The break even points are (Type ordered pairs. Use a comma to separate answers as needed. Round to the nearest integer as…
You estimated the following regression. What value would you predict for Y, if X = 46? (Round your final answer to zero decimal places.) Source | SS df MS Number of obs = 452 -------------+---------------------------------- F(1, 450) > 99999.00 Model | 451909533 1 451909533 Prob > F = 0.0000 Residual | 1435457.34 450 3189.9052 R-squared = 0.9968 -------------+---------------------------------- Adj R-squared = 0.9968 Total | 453344990 451 1005199.53 Root MSE = 56.479 ------------------------------------------------------------------------------ Y | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- X | 12.27466 .0326116 376.39 0.000 12.21057 12.33875 _cons | 69.67934 3.949949 17.64 0.000…