Results of Regressions of Average Houry Earning Education Binary Variables and Other Characteristics Using Data from the Current Population Survey Dependent variable: average hourly earnings (AHE). Regressor (1) (2) (3) 5.57 5.59 5.55 College (X,) Female (X2) -2.69 -2.67 -2.67 0.30 0.30 Age (X) 0.70 Northeast (X,) 0.61 Midwest (Xs) South (X) -0.28 12.94 4.49 3.83 Intercept Summary Statistics SER 6.40 6.34 6.33 0.180 0.194 0.198 0.180 0.193 O 97 4100 4100 4100 Using the regression results in column (2) On average, a worker eams $ per hour V for each year that he or she ages.

In the regression equation, what is B0? Group of answer choices the population slope the sample y-intercept the sample slope the population y-intercept

INSUR A life insurance company wishes to examine the relationship between the amount of life insurance held by a family and family income. From a random sample of households, the company collected the accompanying data. The data are in units of thousands of dollars. INCOME 97 38 141 29 y = x = Let INSUR 280 75 INCOME 303 81 453 137 The numerator of the slope coefficient formula for the estimated regression equation is: 357 77 a 400,201.10 199 43 b 392,354.02 251 53 384,660.80 807 184 d 377,118.44 147 45 272 70 537 128 527 117 245 55 483 116 673 204 194 46 154 51 163 48 280 69 507 140 464 136 321 71 873 206 476 144 574 111 251 65 497 130 826 171 133 32 259 82 281 73 446 146 332 77 219 48 208 55 180 48 169 42 273 69 502 127 547 126 281 80 428 143 370 77 221 49 214 51

QUESTION 39 A researcher reports an independent-measures t-statistic with degrees of freedom = 38 . How many participants were in the entire study?     20     40     39     76

A finance manager employed by an automobile dealership believes that the number of cars sold in his local market can be predicted by the interest rate charged for a loan. Interest Rate (%) Number of Cars Sold (100s) 3 5 10 7 8 2 The finance manager performed a regression analysis of the number of cars sold and interest rates using the sample of data above. Shown below is a portion of the regression output. Regression Statistics Multiple R0.998868 R2 0.997738 Coefficient |14.88462 Interest Rate -1.61538 Intercept 1. Are there factors other than interest rate charged for a loan that the finance manager should consider in predicting future car sales? 2. Is interest rate charged for a loan the most important factor to be considered in predicting future car sales? Explain your reasoning.The dealership's vice- president of marketing has requested a sales forecast at the prevailing interest rate of 7%. 3. As finance manager, what reasons would you convey to the vice-president in recommending…

T or F  A household is frequently used in analyses because more consistent data are usually collected at that level.

determine the regression line equation plot the line on a graph and summarize the results( reject or do not) is there enough evidence?

the unemployment rate for 18- to 34-year-olds was reported to be 10.8% (the Cincinnati Enquirer, november 6, 2012). assume that this report was based on a random sample of four hundred 18- to 34-year-olds. a. a political campaign manager wants to know if the sample results can be used to conclude that the unemployment rate for 18- to 34-years-olds is significantly higher than the unemployment rate for all adults. according to the bureau of labor Statistics, the unemployment rate for all adults was 7.9%. develop a hypothesis test that can be used to see if the conclusion that the unemployment rate is higher for 18- to 34-year-olds can be supported.b. use the sample data collected for the 18- to 34-year-olds to compute the p-value for the hypothesis test in part (a). using a 5 .05, what is your conclusion?c. explain to the campaign manager what can be said about the observed level of significance for the hypothesis testing results using the p-value

The OLS estimation of the relationship between GRADE and HOURS of studying gives the following fitted equation (standard errors in parentheses): GRADEA = 38.15+0.048*HOURS (6.85) (0.01) Calculate the corresponding t statistic to test the slope coefficient for significance (Use two decimal places without rounding)

QUESTION 7 Which is NOT true about the coefficient of determination? As you add more variables, the R-square generally rises. As you add more variables, the adjusted R-square can fall. If the R-square is above 50%, the regression is considered significant. The R-square gives the percent of the variation in the dependent variable that is explained by the independent variables. The higher is the R-square, the better is the fit.