Babe Ruth’s 1931 salary was $80,000.  Government statistics show a consumer price index of 15.2 for 1931 and 214.5 for 2009.  Ruth’s 1931 salary was equivalent to a 2009 salary of about

The following data give the dates of successive turning points in U.S. economic activity and the corresponding levels of real GDP at their time:Which of the following periods is a recession?

What might cause a rightward shift of the supply curve? 

If the value of money equals 1/8, the price level equals:     

If the actual rate of unemployment equals the natural rate of unemployment, then:

If Country A and Country B have the same population, then the standard of living in Country A will be ______ the standard of living in country B. 

TABLE 13-01A large national bank charges local companies for using their services. A bank official reported the results of a regression analysis designed to predict the bank’s charges (Y) — measured in dollars per month — for services rendered to local companies. One independent variable used to predict service charge to a company is the company’s sales revenue (X) — measured in millions of dollars. Data for 21 companies who use the bank’s services were used to fit the model: Y = β0 + β1X+εThe results of the simple linear regression are provided below.  = -2,700 + 20X, SYX = 65, two-tailed p value = 0.034 (for testing  β1)Referring to Table 13-1, a 95% confidence interval for β1 is (15, 30). Interpret the interval.

A regression analysis between weight (y in pounds) and height (x in inches) resulted in the following least squares line:  = 120 + 5x. This implies that if the height is increased by 1 inch, the weight is expected to:

TABLE 13-6The following EXCEL tables are obtained when “Score received on an exam (measured in percentage points)” (Y) is regressed on “percentage attendance” (X) for 22 students in a Statistics for Business and Economics course.        Referring to Table 13-6, which of the following statements is true?

TABLE 13-2A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the company randomly chooses 6 small cities and offers the candy bar at different prices. Using candy bar sales as the dependent variable, the company will conduct a simple linear regression on the data below:   SUMMARY OUTPUT Regression Statistics Multiple R 0.885404 R Square 0.783941 Adjusted R Square 0.729926 Standard Error 16.29861 Observations 6 ANOVA   df SS MS F Significance F Regression 1 3855.422 3855.422 14.51346 0.018946 Residual 4 1062.578 265.6446 Total 5 4918         Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 161.3855 26.16069 6.16901 0.003506 88.75183 234.0193 88.75183 234.0193 price -48.1928 12.65017 -3.80965 0.018946 -83.3153 -13.0703 -83.3153 -13.0703 Referring to the above Table, to test whether a change in price will have any impact on average sales, what would be the critical values? Use α = 0.05.