18. Median Income The data in the table show the median incomes y (in thousands of dollars) for samples of householders of various ages z in the United States in 2017. (Adapted from U.S. Census Bureau) 20 30 40 50 60 70 40.1 62.3 78.4 80.7 68.6 41.1 a. Use the regression capabilities of a graphing utility to find a quadratic model for the data. b. Use a graphing utility to plot the data and graph the model. c. Use the model to approximate the median incomes for a sample of 27-year-old householders and a sample of 56-year-old householders.

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70. College Costs The table lists the average tuition and fees (in constant 2014 dollars) at public colleges and universi- ties for selected years. Year 1984 1994 2004 2014 Tuition and Fees (in 2014 dollars) 12,179 16,188 7626 9386 Source: National Center for Education Statistics. (a) Find the equation of the least-squares regression line that models the data. (b) Graph the data and the regression line in the same viewing window. (c) Estimate the cost in 2009. (d) Use the model to predict the cost in 2019.

Average Age and Length of Service Is the average age of armed services personnel related to the average amount of length of service in months? The data are shown. Age Time Send data to Excel Part: 0 / 5 25.1 25.2 25.8 27 27.1 66.5 70.1 74 89 82 Part 1 of 5 (a) Draw the scatter plot for the variables.

Help with: Determine the​ least-squares regression line. Test whether there is a linear relation between height and weight at the α=0.05 level of significance. What is the P Value Remove the values listed for Player 4 from the data table. Test whether there is a linear relation between height and weight. Do you think that Player 4 is​ influential? What is the P Value

ea surface temperature26.726.726.626.626.626.626.526.526.326.326.126.1Growth0.850.850.850.850.790.790.860.860.890.890.920.92    Make a scatterplot. Which is the explanatory variable? The plot shows a negative linear pattern. Explanatory Variable:

Using 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…

a) Determine the least squares regression equation for the population in years since 2005.  Round the slope and y-intercept to the nearest tenth.  b) Find the correlation coefficient, r-value, of the line. Round your answer to the nearest thousandth. c) Predict the population for the 2020. ____ thousand people

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Life expectancy in the United States has been rising since the nineteenth century. The table shows the U.S. life expectancy in selected years. Year 1950 1960 1970 1980 1990 2000 Life expectancy at birth 68.2 69.7 70.8 73.7 75.4 77 a. Let t represent the number of years after 1950, and plot the data. Draw a line a best fit for the data points. 80+ 76- 5 10 15 20 25 30 35 40 45 50 Draw: 72+ 64- 60+ 56 52 48- 44 Clear All