For the
Linear,
Quadratic,
Quadratic
Polynomial, neither quadratic nor linear
Exponential,
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- National Debt The size of the total debt owed by the UnitedStates federal government continues to grow. In fact,according to the Department of the Treasury, the debt perperson living in the United States is approximately $53,000(or over $140,000 per U.S. household). The following datarepresent the U.S. debt for the years 2001–2014. Since thedebt D depends on the year y, and each input correspondsto exactly one output, the debt is a function of the year. SoD1y2 represents the debt for each year y. Source: www.treasurydirect.govDebt (billions Debt (billionsYear of dollars) Year of dollars)2001 5807 2008 10,0252002 6228 2009 11,9102003 6783 2010 13,5622004 7379 2011 14,7902005 7933 2012 16,0662006 8507 2013 16,7382007 9008 2014 17,824 (a) Plot the points 12001, 58072, 12002, 62282, and so on ina Cartesian plane.(b) Draw a line segment from the point 12001, 58072 to12006, 85072. What does the slope of this line segmentrepresent?(c) Find the average rate of change of the debt from 2002…arrow_forwardBecause of high tuition costs at state and private universities, enrollments atcommunity colleges have increased dramatically in recent years. The following data show theenrollment (in thousands) for Jefferson Community College from 2001–2009:Year Period (t) Enrollment (1000s)2001 1 6.52002 2 8.12003 3 8.42004 4 10.22005 5 12.52006 6 13.32007 7 13.72008 8 17.22009 9 18.1Compute F10: the Forecast for 2010. Compute Pearson’s Correlation Coefficient Use the Method of Least Squares to obtain the Best-Fit-Line for this data. Use the line to compute the forecast.arrow_forwardUsing the data in Table 6–11, calculate a 3-month moving average forecast for month 12.arrow_forward
- Large companies typically collect volumes of data before designing a product, not only to gain information as to whether the product should be released, but also to pinpoint which markets would be the best targets for the product. Several months ago, I was interviewed by such a company while shopping at a mall. I was asked about my exercise habits and whether or not I'd be interested in buying a video/DVD designed to teach stretching exercises. I fall into the male, 18 – 35-years-old category, and I guessed that, like me, many males in that category would not be interested in a stretching video. My friend Diane falls in the female, older-than-35 category, and I was thinking that she might like the stretching video. After being interviewed, I looked at the interviewer's results. Of the 93 people in my market category who had been interviewed, 17 said they would buy the product, and of the 113 people in Diane's market category, 34 said they would buy it. Assuming that these data came…arrow_forwardLarge companies typically collect volumes of data before designing a product, not only to gain information as to whether the product should be released, but also to pinpoint which markets would be the best targets for the product. Several months ago, I was interviewed by such a company while shopping at a mall. I was asked about my exercise habits and whether or not I'd be interested in buying a video/DVD designed to teach stretching exercises. I fall into the male, 18 – 35-years-old category, and I guessed that, like me, many males in that category would not be interested in a stretching video. My friend Amanda falls in the female, older-than-35 category, and I was thinking that she might like the stretching video. After being interviewed, I looked at the interviewer's results. Of the 97 people in my market category who had been interviewed, 16 said they would buy the product, and of the 101 people in Amanda's market category, 31 said they would buy it. Assuming that these data came…arrow_forwardQ1. The table provided gives data on indexes of output per hour (X) and real compensation per hour (Y) for the business and nonfarm business sectors of the U.S. economy for 1960–2005. The base year of the indexes is 1992 = 100 and the indexes are seasonally adjusted. a. Plot Y against X for the two sectors separately. b. What is the economic theory behind the relationship between the two variables? Does the scattergram support the theory? c. Estimate the OLS regression of Y on X. Note: on the table ( 1. Output refers to real gross domestic product in the sector. 2. Wages and salaries of employees plus employers’ contributions for social insurance and private benefit plans. 3. Hourly compensation divided by the consumer price index for all urban consumers for recent quarters.) Thank you!arrow_forward
- (a) For United States, provide data for the variables below over the years 1993 –2007:(i) Net migration rate (per 1,000 population)(ii) Total fertility rate (live births per woman)(iii)Unemployment, general level (Thousands)(iv) Wages(v) Life expectancy at birth for both sexes combined (years)Data can be obtained from the UN database http://data.un.org/Explorer.aspxUsing R-Studio, estimate a regression equation to determine the effect of unemployment,general level, wages and life expectancy at birth for both sexes on the net migration rate.(All codes and regression output should be provided).(i) Write down the regression equation. (ii) Interpret the coefficients and determine which of the individual coefficients in theregression model are statistically significant. In responding, construct and test anyappropriate hypothesis. (iii) Interpret the coefficient of determination.arrow_forwardThe table gives the average heights of children for ages 1 – 10, where x = the age (in years) and y = the height (in cm). Part a: Make a scatter plot and determine which type of model best fits the data.Part b: Find the regression equation.Part c: Can your equation be used to find the average height of a 20 year old? Explain.arrow_forwardWorld Military Expenditure The following chart shows total military and arms trade expenditure from 2011–2020 (t = 1 represents 2011). †A bar graph titled "World military expenditure" has a horizontal t-axis labeled "Year since 2010" and a vertical axis labeled "$ (billions)". The bar graph has 10 bars. Each bar is associated with a label and an approximate value as listed below. 1: 1,800 billion dollars 2: 1,775 billion dollars 3: 1,750 billion dollars 4: 1,730 billion dollars 5: 1,760 billion dollars 6: 1,760 billion dollars 7: 1,850 billion dollars 8: 1,900 billion dollars 9: 1,950 billion dollars 10: 1,980 billion dollars (a) If you want to model the expenditure figures with a function of the form f(t) = at2 + bt + c, would you expect the coefficient a to be positive or negative? Why? HINT [See "Features of a Parabola" in this section.] We would expect the coefficient to be positive because the curve is concave up. We would expect the coefficient to be negative because the…arrow_forward
- (a) For United States, provide data for the variables below over the years 1993 – 2007: (i) Net migration rate (per 1,000 population) (ii) Total fertility rate (live births per woman) (iii)Unemployment, general level (Thousands) (iv) Wages (v) Life expectancy at birth for both sexes combined (years) Data can be obtained from the UN database http://data.un.org/Explorer.aspx Using R-Studio, estimate a regression equation to determine the effect of unemployment, general level, wages and life expectancy at birth for both sexes on the net migration rate. (All codes and regression output should be provided). (iv) Using the 10% level of significance, determine and discuss whether the overall regression equation is statistically significant. In responding, construct and test any appropriate hypothesis. (v) Determine and interpret the confidence interval for the independent variable(s).arrow_forward(a) For United States, provide data for the variables below over the years 1993 – 2007: (i) Net migration rate (per 1,000 population) (ii) Total fertility rate (live births per woman) (iii)Unemployment, general level (Thousands) (iv) Wages (v) Life expectancy at birth for both sexes combined (years) Data can be obtained from the UN database http://data.un.org/Explorer.aspx Using R-Studio, estimate a regression equation to determine the effect of unemployment, general level, wages and life expectancy at birth for both sexes on the net migration rate. (All codes and regression output should be provided).(b) Using R-Studio redo the regression analysis with the total fertility rate as an additionalindependent variable. (All codes and regression output should be provided).(i) Write down the regression equation. (ii) Use the 5% level of significance, determine and discuss whether the total fertilityrate has a significant impact on the net migration rate in your assigned country.…arrow_forward21–23. Language enrollments. The line graph in Figure 2.28 shows total course enrollments in languages other than English in U.S. institutions of higher education from 1960 to 2009. (Enrollments in ancient Greek and Latin are not included.) Exercises 21 through 23 refer to this figure. 1,800,000 1,629,326 1.522.770 1,600,000 - 1,400,000 - 1347.036 1,200,000- 1,073,097 1,067,217 1,000.000 - 975.7m 963,930 883.222 1.06.603 922,439 960.588 B00,000 - 97.077 877.91 600,000 - 608,749 400.000 - 200,000 - 1960 1965 1968 | 1972 1977 1980 1983 1986 1990 1995 199 2002 2006 2009 1970 1974 Figure 2.28 Crauder, et al., Quantitative Literacy, 3e, © 2019 W. H. Freeman and Company FIGURE 2.28 Enrollments in languages other than English in U.S. institutions of higher education (2009). 21. During which time periods did the enrollments decrease? 22. Calculate the average growth rate per year in enrollments over the two periods 1960–1965 and 2006– 2009. Note that the time periods are not of the same…arrow_forward
- Algebra & Trigonometry with Analytic GeometryAlgebraISBN:9781133382119Author:SwokowskiPublisher:Cengage