The following table shows the average annual income in a certain country, adjusted for inflation, for the given year. t = years since 1980 I = annual income 0 $23,109 5 $23,216 10 $25,384 15 $26,694 20 $30,719 25 $30,450 30 $28,738 (a) Find the equation of the regression line. (Round regression line parameters to two decimal places.) I(t) =        (b) Plot the data along with the regression line.               (c) Explain in practical terms the meaning of the slope of the regression equation. (Round your answers to two decimal places.) The slope of the regression line is  dollars per year. The slope means that, from 1980 on, the average annual income (adjusted for inflation) grew by $  each year.

Table 2 shows a recent graduate’s credit card balance each month after graduation. a. Use exponential regression to fit a model to these data. b. If spending continues at this rate, what will the graduate’s credit card debt be one year after graduating?

Demand for Candy Bars In this problem you will determine a linear demand equation that describes the demand for candy bars in your class. Survey your classmates to determine what price they would be willing to pay for a candy bar. Your survey form might look like the sample to the left. a Make a table of the number of respondents who answered yes at each price level. b Make a scatter plot of your data. c Find and graph the regression line y=mp+b, which gives the number of respondents y who would buy a candy bar if the price were p cents. This is the demand equation. Why is the slope m negative? d What is the p-intercept of the demand equation? What does this intercept tell you about pricing candy bars? Would you buy a candy bar from the vending machine in the hallway if the price is as indicated. Price Yes or No 50 75 1.00 1.25 1.50 1.75 2.00

A Dubious Model of Oil Prices The following table shows the prices of oil in U.S. dollars per barrel, t years since 1990, One analysis involving additional data used a cubic equation to model this data. t Years since 1990 0 2 5 7 10 12 15 17 20 21 P Price, dollars per barrel 18.91 16.22 16.63 18.20 27.04 23.47 49.63 69.04 77.46 106.92 a. Use cubic regression to model these data. Round the regression parameters to four decimal places. b. Plot the data along with the cubic model. c. In the analysis mentioned above, the graph is expanded through 2020. Expand the viewing window to show the model from 1990 to 2020. d. What estimate does the model give for oil prices in 2015? e. The actual price of oil in December of 2015 was about 35 per barrel. What basic principle in the use of models would be violated in relying on the estimate in part d?

Special Rounding Instructions For this exercise set, round all regression parameters to three decimal places, but round all other answers to two decimal places unless otherwise indicated. Postal RatesThe table below shows the cost s, in cents, of a domestic first-class postage stamp in the United States tyears after 1900. t=time,inyearssince1900 s=costofstamp 19 2 32 3 58 4 71 8 78 15 85 22 95 32 102 37 109 44 116 47 a.Use exponential regression to model s as an exponential function of t. b.What cost does your model give for a 1988 stamp? Report your answer to the nearest cent. The actual cost was 25cents. c.Plot the data and the exponential model.

The US. import of wine (in hectoliters) for several years is given in Table 5. Determine whether the trend appearslinear. Ifso, and assuming the trend continues, in what year will imports exceed 12,000 hectoliters?

B. The best predicted age of the Best Actor winner given that the age of the Best Actress winner that year is 42 years is____ years old.   C. Is the result within 5 years of the actual Best Actor​ winner, whose age was 43 ​years? (Yes/ No) the predicted age is (more than 5 years greater than/more than 5 years less than/5 years or less from) the actual​ winner's age.

For nine months, Joan observes the average daily gas consumption for her house and the corresponding average temperature that month. She gets the following scatterplot (with regression line equation presented and drawn in):             Interpreting the regression line (formula above the graph), in general, about how much is gas consumption reduced for each degree increase in average temperature in any given month?          AC 43, 20, 83, 800, 1438                  ["", "", "", ""]            Over the nine months Joan took measurements, approximately what was the range of gas consumptions?    AC   20,80,38,1438                     ["", "", "", ""]            For a month in which the average temperature is 40, predict the daily amount of gas consumed for that month.          AC 309, 630,425,800            ["", "", "", ""]            After collecting the data, Joan had insulation installed in her home. The next month, the average temperature was 30 and her home (with insulation) consumed…