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'sage, 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 independentvariable (x2) is the student's age.Coefficients Standard Error1-Statp-valueInterceptNumber of Parking TicketsStudent's Age15.034003-0.026275-0.6383311.30273911.540305 0.0000250.0302540.062922-0.868470 0.418515-10.144838 0.000053Copy DataStep 2 of 2: Indicate if any of the independent variables could be eliminated at the 0.05 level of significance.Answerx1x2Keep all variablesTablesKeypadKeyboard Shortcu

Given:Dependent variable = student's GPAIndependent variables:x1 = number of parking ticketsx2 =…

Answered: The following table was generated from…

ENGR.ECONOMIC ANALYSIS

14th Edition

ISBN:9780190931919

Author:NEWNAN

Publisher:NEWNAN

Chapter1: Making Economics Decisions

Section: Chapter Questions

Problem 1QTC

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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: CO2 Method: Least Squares Date: 04/20/17 Time: 09.46 Sample: 1990 2013 Included observations: 24 Variable Coefficient Std. Error t-Statistic Prob. GDP ENERGY POP 2.002813 0.022114 -0.734352 0.203927 6.458672 0.011872 0.328388 0.293686 0,310097 1.862670 -2.236233 0.694371 0.7597 0.0773 0,0369 0.4954 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.825079 Mean dependentyar 0.798841 0.048515 Akaike info criterion 0.047074 Schwarz criterion 40.75460 Hannan-Quinn.criter. 31.44583 Durbin-Wats on stat 0.000000 3.625982 0.108170 -3.062883 -2.866541 -3.010793 1.410912 S.D. dependent yar a Write down the economie function for the above estimation by using the information obtained from above table| b- Write down the economic model for the above…
The following data was collected to explore how a student's age and GPA affect the number of parking tickets they receive in a given year. The dependent variable is the number of parking tickets, the first independent variable (1) is the student's age, and the second independent variable (x2) is the student's GPA. Effects on Number of Parking Tickets Age GPA Number of Tickets 17 2 1 17 2 2 18 2 4 20 2 5 20 3 5 22 3 6 233 22 3 6 3 7 25 4 7 Copy Data Step 2 of 2: Determine if a statistically significant linear relationship exists between the independent and dependent variables at the 0.01 level of significance. If the relationship is statistically significant, identify the multiple regression equation that best fits the data, rounding the answers to three decimal places. Otherwise, indicate that there is not enough evidence to show that the relationship is statistically significant. Answer How to enter your answer (opens in new window) Selecting a checkbox will replace the entered answer…
The following table was generated from the sample data of 10 junior high students regarding the average number of hours they are unsupervised per night, the average number of hours they play video games per night, and their final grades in their math class. The dependent variable is the final grade, the first independent variable (x1) is the number of hours unsupervised each night, and the second independent variable (2) is the number of hours of video games each night. Intercept Coefficients Standard Error 99.492882 t-Stat 6.492044 Hours Unsupervised Hours Playing Video Games -1.878497 -5.596653 1.368043 1.178139 p-value 15.325355 0.000005 -1.373127 0.218817 -4.750418 0.003157 Step 1 of 2: Write the multiple regression equation for the computer output given. Round your answers to three decimal places. How to enter your answer (opens in new window) Answer y = + x1 + x2 Copy Data Tables Keypad Keyboard Shortcuts
The following table was generated from the sample data of 10 junior high students regarding the average number of hours they are unsupervised per night, the average number of hours they play video games per night, and their final grades in their math class. The dependent variable is the final grade, the first independent variable (x1) is the number of hours unsupervised each night, and the second independent variable (2) is the number of hours of video games each night. Coefficients Standard Error 1-Stat p-value Intercept Hours Unsupervised 60.829438 3.861884 15.751235 0.000001 3.451483 0.826485 4.176100 0.004157 Hours Playing Video Games 4.918683 0.867336 5.671022 0.000758 Step 2 of 2: Indicate if any of the independent variables could be eliminated at the 0.05 level of significance. Answer O Keep all variables Copy Data Tables Keypad Keyboard Shortcuts
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
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
For each of the following variables, determine whether the variable is categorical or numerical. If the variable is numerical, determine whether the variable is discrete or continuous. In addition, determine the measurement scale. a. Time, in hours, spent working per month b. Name of a household's cable television provider c. Number of online purchases made in a month d. Satisfaction rating of a cable television provider (from low to high) e. Time, in hours, spent surfing the Internet per month a. Time, in hours, spent working per month is what kind of variable? O A. This variable is a continuous numerical variable that is ratio-scaled. O B. This variable is a discrete numerical variable that is ratio-scaled. OC. This variable is a discrete numerical variable that is interval-scaled. O D. This variable is a categorical variable that is ordinal-scaled. O E. This variable is a categorical variable that is nominal-scaled. O F. This variable is a continuous numerical variable that is…
Test Design: Suppose I want to test the impact of soccer coaches on soccer teams. How would you test this? Include a few (3 or 4) independent variables to explain the dependent variable. Describe the data and write the regression equation.
QUESTION 1 Suppose a researcher collects data on houses that have been sold in a particular neighbourhood over the past year, and obtains the regressions results in the table shown below. This table is used for Questions 1-6. Dependent variable: In(Price) Regressor (1) (2) (3) (4) (5) 0.00042 (0.000038) Size In(Size) 0.57 (2.03) 0.69 0.68 0.69 (0.055) (0.054) (0.087) In(Size)² 0.0078 (0.14) Bedrooms 0.0036 (0.037) Рol 0.082 0.071 0.071 0.071 0.071 (0.032) (0.034) (0.034) (0.036) (0.035) 0.037 0.027 0.026 0.027 0.027 (0.030) View (0.029) (0.028) (0.026) (0.029) Pool x View 0.0022 (0.10) 0.12 (0.035) Condition 0.13 0.12 0.12 (0.035) 0.12 (0.045) (0.035) (0.036) 6.63 (0.53) Intercept 10.97 6.60 7.02 6.60 (0.069) (0.39) (7.50) (0.40) Summary Statistics SER 0.102 0.098 0.099 0.099 0.099 R? 0.72 0.74 0.73 0.73 0.73 Variable definitions: Price = sale price ($); Size = house size (in square feet); Bedrooms = number of bedrooms; Pool = binary variable (1 if house has a swimming pool, 0…
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.
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
The table lists weights (pounds) and highway mileage amounts (mpg) for seven automobiles. Use the sample data to construct a scatterplot. Use the first variable for the x-axis. Based on the scatterplot, what do you conclude about a linear correlation? Weight (lb) Highway (mpg) Which scatterplot below shows the data? O A. 40- 20+ 2000 5000 2855 3050 3810 3985 4250 2275 3525 33 32 27 24 22 39 28 Weight (lb) Q Q O B. 40 20+ 2000 AHH 5000 Weight (lb) Q Q Is there a linear relationship between weight and highway mileage? O A. No, there appears to be a relationship, but it is not linear. O B. Yes, as the weight increases the highway mileage decreases. O C. Yes, as the weight increases the highway mileage increases. OD. No there appears to be no relationshin C O C. Q 40- M Q 20++ 2000 5000 Weight (lb) Highway ( O D. Highway (mpg) 40- 20+ 2000 5000 Weight (lb) Q

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