Identify the estimated simple linear regression equation.AnswerO y = Bo+B1x1 + ẞ2x2 + €Oy Bo+B1x + €Oy bob₁x + ε○ ŷ = bo+b₁x

The estimated simple linear regression equation is typically represented as:y^=b0+b1xWhere:y^…

Answered: Identify the estimated simple linear…

Managerial Economics: Applications, Strategies and Tactics (MindTap Course List)

14th Edition

ISBN:9781305506381

Author:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Publisher:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Chapter4A: Problems In Applying The Linear Regression Model

Section: Chapter Questions

Problem 1E

See similar textbooks

Similar questions

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…
Consider the output here from a regression in R. What is 3₂? Coefficients: Estimate (Intercept) 1.708 5.404 -1.478 9.531 X1 X2 X3 Std. Error 0.555 2.792 0.6 2.758
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
You estimated a regression with the following output. Source | SS df MS Number of obs = 289 -------------+---------------------------------- F(1, 287) = 41986.64 Model | 664544048 1 664544048 Prob > F = 0.0000 Residual | 4542496.25 287 15827.5131 R-squared = 0.9932 -------------+---------------------------------- Adj R-squared = 0.9932 Total | 669086544 288 2323217.17 Root MSE = 125.81 ------------------------------------------------------------------------------ Y | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- X | 43.81013 .2138056 204.91 0.000 43.38931 44.23096 _cons | 49.31707 16.96222 2.91 0.004 15.93094 82.70319…
Q4. The Omantel firm has estimate the Sales of fibre internet connections in Oman with the related to advertising expenditure made by the company over the past 26 months. Following is the firm estimated results of the regression equation. DEPENDENT VARIABLE: Y R-SQUARE F-RATIO P-VALUE ON F OBSERVATIONS: 26 0.85121212 8.747 0.0187 PARAMETER STANDARD VARIABLE ESTIMATE ERROR T-RATIO P-VALUE INTERCEPT 7.6 6.33232 1.200 0.2643969 3.53 0.52228 ? 0.0001428 a. What is the dependent and independent variables in the above regression equation of Omantel firm? b. Calculate the estimated t-ratio. Test the slope estimates for statistical significance at the 10 percent significance level. d. Interpret the coefficient of determination.
The following information regarding a dependent variable y and an independent variable x is provided. Find the slope of the regression equation. Ex = 90 Ey = 340 n = 4 SSR = 103 E(y - )(x - x) E(x – x)2 = 236 E(y - y)2 = 1,978 = -153 %3D %3D Select an answer and submit. For keyboard navigation, use the up/down arrow keys to select an answer. a -0.648 b -0.265 0.265
A forecaster used the regression equation Qt= a + bt+q₁D₁ + C2D2 + c3D3 and quarterly sales data for 2004/-2021/V (t = 1, ..., 64) for an appliance manufacturer to obtain the results shown below. Q is quarterly sales, and D1, D₂ and D3 are dummy variables for quarters I, II, and III. DEPENDENT VARIABLE: QT R-SQUARE OBSERVATIONS: 64 0.8768 VARIABLE INTERCEPT T D1 D2 D3 F-RATIO P-VALUE ON F 107.982 0.0001 PARAMETER STANDARD ESTIMATE 30.0 1.5 10.0 25.0 40.0 ERROR T-RATIO P-VALUE 2.34 0.0224 2.14 0.0362 3.33 0.0015 3.47 0.0010 2.53 0.0140 12.80 0.70 3.00 7.20 15.80 In any given year, quarterly sales tend to vary as follows:
1. For a regression model y = XB + u where u is N(0, o?1), y is nx1 matrix, X is nxp matrix, B is px1 matrix and u is nx1 matrix, a. derive the estimators B using the method of least squares
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.
Water is being poured into a large, cone-shaped cistern. The volume of water, measured in cm³, is reported at different time intervals, measured in seconds. A regression analysis was completed and is displayed in the computer output. Regression Analysis: cuberoot (Volume) versus Time Predictor Coef SE Coef Constant -0.006 0.00017 -35.294 0.000 Time 0.640 0.000018 35512.6 0.000 s=0.030 R-Sq=1.000 R-sq (adj)=1.000 What is the equation of the least-squares regression line? Volume = 0.640 - 0.006(Time) Volume = 0.640 - 0.006(Time) Volume = -0.006 + 0.640(Time) Volume = - 0.006 + 0.640(Time?)
Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed actress/actor ages in various years, find the best predicted age of the Best Actor winner given that the age of the Best Actress winner that year is 43 years. Is the result within 5 years of the actual Best Actor winner, whose age was 45 years? Best Actress 27 30 30 61 30 32 46 28 61 22 43 56 D Best Actor 42 39 38 45 51 49 59 51 38 57 45 34 Find the equation of the regression line. y = + (Round the constant to one decimal place as needed. Round the coefficient to three decimal places as needed.) The best predicted age of the Best Actor winner given that the age of the Best Actress winner that year is 43 years is years old. (Round to the nearest whole number as needed.) Is the result within 5 years of the actual Best Actor winner, whose age was 45 years? the predicted age is the actual winner's age.
Refer to the following computer output from estimating the parameters of the nonlinear model Y=aRbsc7d The computer output from the regression analysis is: DEPENDENT VARIABLE: LNY R-SQUARE 32 0.7766 OBSERVATIONS: VARIABLE INTERCEPT LNR P-VALUE ON F 0.0001 PARAMETER ESTIMATE STANDARD ERROR T-RATIO -0.6931 F-RATIO 4.66 -0.44 8.28 32.44 0.32 1.36 -2.17 3.43 -1.83 P-VALUE 1.80 0.0390 LNS 0.24 LNT 4.60 Based on the information in the table, the nonlinear relation can be transformed into the following linear regression model: Multiple Choice in Y= 1n a.ln R.1n S.1n T in Y= 1na + b1nR+ cins + din T 1n Y = 1n(aRb SC7d) Y = 1n(aRb Sc7d) 0.0019 0.0774 0.0826

SEE MORE QUESTIONS

Recommended textbooks for you

Managerial Economics: Applications, Strategies an…

Economics

ISBN:

9781305506381

Author:

James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Publisher:

Cengage Learning