A highway department is studying the relationship between traffic flow and speed. The following model has been hypothesized: y = Bot Box + where y = traffic flow in vehicles per hour x = vehicle speed in miles per hour. The following data were collected during rush hour for six highways leading out of the city. Traffic Flow (y) Vehicle Speed (x) 1,245 35 1,318 40 1,215 30 1,324 45 1,338 50 1,112 25 (a) Develop an estimated regression equation for the data. (Round bo to one decimal place and b₁ to two decimal places.) y =

A highway department is studying the relationship between traffic flow and speed. The following model has been hypothesized: y = Bot Box + where y = traffic flow in vehicles per hour x = vehicle speed in miles per hour. The following data were collected during rush hour for six highways leading out of the city. Traffic Flow (y) Vehicle Speed (x) 1,245 35 1,318 40 1,215 30 1,324 45 1,338 50 1,112 25 (a) Develop an estimated regression equation for the data. (Round bo to one decimal place and b₁ to two decimal places.) y =

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

You have noticed that paying higher wages attracts more productive employees. However, you are concerned that there may be a limit to this relationship. Some experimentation has convinced you that the relationship between wages paid (x) and profits can be modelled by the equation Profit = 25x − 0.1x2 + 200. Use a Nonlinear Solver tool to determine the level of wages that will maximize profits.
1. A study published in 1993 used US state panel data to investigate the relationshipbetween minimum wage and the employment of teenagers. The sample period was1977 to 1989 for all 50 states. The author estimated a model of the following type:ln(Eit) = β0 + β1ln(Mit/Wit) + γ2D2i + ... + γnD50i + δ2B2t + ... + δTB13t + uitwhere E is the employment to population ratio of teenagers, M is the nominalminimum wage, and W is average hourly earnings in manufacturing. In addition,other explanatory variables, such as the adult unemployment rate, the teenagepopulation share, and the teenage enrollment rate in school, were included.(a) Name some of the factors that might be picked up by time and state fixedeffects(b) The author decided to use eight regional dummy variables instead of the 49state dummy variables. What is the implicit assumption made by the author?Could you test for its validity? How?(c) The results, using time and region fixed effects only, were as follows:ˆ ln(EIT ) =…
Let ŷ represent the profit (or loss) for a certain company z years after 1965. Based on the data shown below, a statistician calculates a linear model ŷ = - 2.76x + 54.33. 2 50.05 3 46.3 4 42.25 5 41.4 6 36.35 7 34.5 31.85 30.5 10 26.45 11 23.1 12 20.85 13 19.9 Use the model to estimate the profit in 1978. Round to the nearest cent. The estimated profit in 1978 is $
A marketing analyst wants to examine the relationship between sales (in $1,000s) and advertising (in $100s) for firms in the food and beverage industry and collects monthly data for 25 firms. He estimates the modet: Sales- Bo + B1 Advertising +t. The following table shows a portion of the regression results. Coefficients Standard Error t-stat p-value Intercept 40.10 14.08 2.848 0.0052 Advertising 2.88 1.52 -1.895 0.0608 Which of the following are the competing hypotheses used to test whether the slope coefficient differs from 3? Multiple Choice Ho i bị 3; HAtbi3 Họ ib - 2.88; HAibi 2.88
Water is being poured into a large, cone-shaped cistern. The volume of water, measured in cm³, is reported at different time intervals, measured in seconds. A regression analysis was completed and is displayed in the computer output. Regression Analysis: cuberoot (Volume) versus Time Predictor Coef SE Coef Constant -0.006 0.00017 -35.294 0.000 Time 0.640 0.000018 35512.6 0.000 s=0.030 R-Sq=1.000 R-sq (adj)=1.000 What is the equation of the least-squares regression line? Volume = 0.640 - 0.006(Time) Volume = 0.640 - 0.006(Time) Volume = -0.006 + 0.640(Time) Volume = - 0.006 + 0.640(Time?)
The Australian Government has developed a survey to enable it to gauge the views of the Australian public regarding "Climate Change". The survey consists of a sample of 400 Australian Citizens and Permanent Residents regarding their views on a wide range of Climate Change topics. The Government intends to use the results of the survey to assist in the formulation of government policy for the next 30 years. The variables used in the dataset are as follows: Variable Name Explanation Options Cars Number of motor vehicles in your household Income Your income in Dollars ($) Support Belief that Australia should financially support developing countries in their efforts to address Climate Change (Yes, No) Cause Who/what you think is most responsible for Climate Change (Mostly Human, Mostly Natural, There is no Climate Change, Unsure/Undecided} Solar_Panels Willingness to Install Solar Panels For each of the scenarios outlined below, describe a type of Visualisation (i.e. a Chart/Table/Graph)…
Suppose you have the following data: X Y 3 9 7 45 5 25 2 8 Using OLS methods: estimate the following regression model: Sq root of Yi = Beta0 + Beta1(Xi) + error
The following data gives the experience of the machine operators and their performance ratings as given by the number of good parts turned out per 100 pieces.Experience(X) 16 12 18 4 3 10 5 12Performance Ratings (Y) 88 87 89 68 78 80 75 83Obtain the regression line of performance ratings on experience and estimate the probable performance if the operator has 7 years of experience.
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
The following table was generated from the sample data of 10 college students regarding the number of parking tickets the student receives in a semester, the student's age, and the student's GPA. The dependent variable is the student's GPA, the first independent variable (x1) is the number of parking tickets, and the second independent variable (x2) is the student's age. Coefficients Standard Error 1-Stat p-value Intercept Number of Parking Tickets Student's Age 15.034003 -0.026275 -0.638331 1.302739 11.540305 0.000025 0.030254 0.062922 -0.868470 0.418515 -10.144838 0.000053 Copy Data Step 2 of 2: Indicate if any of the independent variables could be eliminated at the 0.05 level of significance. Answer x1 x2 Keep all variables Tables Keypad Keyboard Shortcu
We have estimated the impact of gross domestic product (GDP), energy consumption (ENERGY) and population (POP) on CO2 emiisions (CO2) in Cyprus. The results are as follows;Dependent Variable: CO2Method: Least SquaresDate: 04/20/17 Time: 09:46Sample: 1990 2013Included observations: 24 Write down the economic function for the above estimation by using the information obtained from above table b- Write down the economic model for the above estimation by using the information obtained from above table . c- Write down the econometric model for the above estimation by using the information obtained from above table d- Write down the least squares line by using the information obtained from above tablee- Explain what each coefficient of the least squares line indicates
A website that rents movies online recorded the age and the number of movies rented during the past month for some of their customers. The data are shown below for a random sample of 25 of their customers.The regression line for the data, with number of movie rentals as the response variable, provides an intercept = 18.87, and slope = -0.228. The standard error of the slope SE(b1) = 0.0827. Margin of error ME for a 99% Confidence Interval for the slope of the Population regression line is: 0.1161 0.2322 0.4644 0.3483