Using data from 50 workers, a researcher estimates Wage = β0 + β1Education + β2Experience + β3Age + ε, where Wage is the hourly wage rate and Education, Experience, and Age are the years of higher education, the years of experience, and the age of the worker, respectively. The regression results are shown in the following table. Coefficients Standard Error t Stat p-Value Intercept 8.93 3.96 2.26 0.0289 Education 1.34 0.38 3.53 0.0010 Experience 0.48 0.20 2.40 0.0205 Age −0.04 0.05 −0.80 0.4278 a-1. Interpret the point estimate for β1. multiple choice 1 As Education increases by 1 year, Wage is predicted to increase by 1.34/hour. As Education increases by 1 year, Wage is predicted to increase by 0.48/hour. As Education increases by 1 year, Wage is predicted to increase by 1.34/hour, holding Age and Experience constant. As Education increases by 1 year, Wage is predicted to increase by 0.48/hour, holding Age and Experience constant. a-2. Interpret the point estimate for β2. multiple choice 2 As Experience increases by 1 year, Wage is predicted to increase by 1.34/hour. As Experience increases by 1 year, Wage is predicted to increase by 0.48/hour. As Experience increases by 1 year, Wage is predicted to increase by 1.34/hour, holding Age and Education constant. As Experience increases by 1 year, Wage is predicted to increase by 0.48/hour, holding Age and Education constant. b. What is the sample regression equation? (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.) c. Predict the hourly wage rate for a 23-year-old worker with 3 years of higher education and 5 years of experience. (Round final answer to 2 decimal places.)
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- A student is interested in the relation between ?,the number of job changes and ?, the annual salary(in thousands of dollars) for people living in the Columbus area. A random sample of 10 peopleemployed in Columbus provided the followinginformation:? 4 7 5 6 1 5 9 10 10 3? 33 37 34 32 32 38 43 37 40 33a) The regression equation is: _____b) Graph the data and the regression equation on thesame graph. Label the graph.c) Describe the apparent relationship between thenumber of job changes and annual salary.d) What does the slope of the regression equationrepresent in terms of the annual salary?e) Identify any outliers or potential influentialobservations. Explain your reasoning.f) Identify the predictor and response variables.g) r2= _____h) r= _____i) Interpret the meaning of r2 and how useful theregression equation is for making predictions.j) Interpret the meaning of r in terms of the linearrelationship between the number of job changesand annual salary.k) Use the regression equation to…arrow_forwardUsing a sample of 46 college students, we want to determine if there is a significant correlation between weight (in lbs.) and weekly exercise (in minutes). The results of a correlation and regression analysis are indicated in the Excel output below. The mean weight (the independent variable) was 166.80 lbs., and the mean weekly exercise time (the dependent variable) was 158.83 minutes. SUMMARY OUTPUT Regression Statistics Multiple R 0.027082077 R Square 0.000733439 Adjusted R Square -0.021977165 Standard Error 79.41761298 Observations 46 ANOVA df SS MS F Significance F Regression 1 203.6896 203.6896 0.032295 0.858207 Residual 44 277514.9 6307.157 Total 45 277718.6 Coefficients Standard Error t Stat P-value Lower 95%…arrow_forwardWe expect a car's highway gas mileage to be related to its city gas mileage (in miles per gallon, mpg). Data for all 1259 vehicles in the government's 2019 Fuel Economy Guide give the regression line highway mpg = 8.720 + (0.914x city mpg) for predicting highway mileage from city mileage. 1 O Macmillan Learning (b) What is the intercept? Give your answer to three decimal places. intercept: Why is the value of the intercept not statistically meaningful? The value of the intercept is an average value calculated from a sample. The value of the intercept represents the predicted highway mileage for city gas mileage of 0 mpg, and such a prediction would be invalid since 0 is outside the range of the data. The value of the intercept represents the predicted highway mileage for slope 0. O The value of the intercept represents the predicted city mileage for highway gas mileage of 0 mpg, and such a car does not exist. mpgarrow_forward
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- I need help on B,C,Darrow_forwardUsing data from 50 workers, a researcher estimates Wage Be + B₁Education + B2Experience + B3Age +, where Wage is the hourly wage rate and Education, Experience, and Age are the years of higher education, the years of experience, and the age of the worker, respectively. A portion of the regression results is shown in the following table. Coefficients Standard Error t Stat p-Value Intercept 7.45 3.79 1.97 0.0554 Education 1.06 0.37 2.86 0.0063 Experience 0.37 0.18 2.06 0.0455 Age -0.02 0.06 -0.33 0.7404 a-1. Interpret the point estimate for ẞ1. As Education increases by 1 year, Wage is predicted to increase by 1.06/hour. As Education increases by 1 year, Wage is predicted to increase by 0.37/hour. As Education increases by 1 year, Wage is predicted to increase by 1.06/hour, holding Age and Experience constant. As Education increases by 1 year, Wage is predicted to increase by 0.37/hour, holding Age and Experience constant. a-2. Interpret the point estimate for ẞ2. ○ As Experience…arrow_forwardWe conduct a regression of size on hhinc, owner, hhsize1, hhsize2, and hhsize3. Wedo not include the constant. The regression output is reported in Table 3. Would youconclude that the home size increases with the household size? Interpret the signand magnitude of the estimated coefficients of hhsize1, hhsize2, and hhsize3arrow_forward
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