Calories and protein: The following table presents the number of grams of protein and the number of caloriesper 100 grams for each of 18 fast-food products.Protein Calories Protein Calories17.252895.6236713.733763.5818812.96 31511.9727521.242685.8440822.5422112.2246016.233098.0518910.64 2265.153666.1634415.933343.69163 16.52241Source: United States Department of AgricultureThe following output was obtained after performing regression analysis in Excel:Regression StatisticsMultiple RR SquareAdjusted R SquareStandard ErrorObservationsRegression outputvariablesInterceptProtein0.03650.0013-0.061184.972118coefficients std error302.5212 45.1484-0.5082 3.4795Y-302.521-0.508xa. Give the value of the correlation coefficient and interpret its meaning.confidence intervalt (df=16) p-value 95% lower 95% upper6.701 5.10E-06 206.8108 398.2315-0.146 8857 -7.8845 6.8680b. Compute the least-squares regression line for predicting calories (y) from protein (x).Ac. Interpret the value of the slope.d. Predict the number of calories in a fast-food product containing 18 grams of protein. Round to the nearestwhole number.e. What is the 95% confidence interval for the slope. You do not have to interpret the results.

It is given that R square, R2 = 0.0013Intercept = 302.5212Slope (Protein) = -0.5082Note: According…

Answered: a. Give the value of the correlation…

MATLAB: An Introduction with Applications

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The General Aviation Manufacturers Association has reported annual flying hours and fuel consumption for airplanes with a single, piston-driven engine as listed in file XR15057. Data are in millions of flying hours and millions of gallons of fuel, respectively. Determine the linear regression equation describing fuel consumption as a function of flying hours, then identify and interpret the slope, the coefficient of correlation, and the coefficient of determination. At the 0.05 level of significance, could the population slope and the population coefficient of correlation be zero? Determine the 95% confidence interval for the population slope Year Hours Gallons 1992 18400000 199100000 1993 17000000 184200000 1994 16400000 177200000 1995 17800000 192600000 1996 17600000 188400000 1997 18300000 196300000
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The least-squares regression equation is y=784.6x+12,431 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7962. In a particular region, 26.5 percent of adults 25 years and older have at least a bachelor's degree. The median income in this region is $29,889. Is this income higher or lower than what you would expect? Why?
Do movies of different types have different rates of return on their budgets? Here's a regression of USGross (SM) on Budget for comedies and action movies with an indicator variable. Complete parts (a) through (d). Dependent variable is: USGross ($M) Coefficient SE(Coeff) - 6.78278 16.95 1.00523 Variable Constant Budget ($M) Comedy 24.0373 0.1613 11.73 t-ratio P-value -0.400 0.6907 6.23 <0.0001 2.05 0.0451 a) Write out the regression model. USGross = + ( Budget + (Comedy R-squared = 32.8% R-squared (adjusted) = 31.0% s = 47.51 55 degrees of freedom
The least-squares regression equation is y=620.6x+16,624 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7004. Predict the median income of a region in which 30% of adults 25 years and older have at least a bachelor's degree.
A regression was run to determine if there is a relationship between the happiness index (y) and life expectancy in years of a given country (x). The results of the regression were: ý=a+bx a=-1.692 b=0.117 (a) Write the equation of the Least Squares Regression line of the form (b) Which is a possible value for the correlation coefficient, r? O -0.649 O 1.32 O 0.649 O-1.32 (c) If a country increases its life expectancy, the happiness index will O increase O decrease (d) If the life expectancy is increased by 2.5 years in a certain country, how much will the happiness index change? Round to two decimal places. (e) Use the regression line to predict the happiness index of a country with a life expectancy of 75 years. Round to two decimal places.
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a. Give the value of the correlation coefficient and interpret its meaning. b. Compute the least-squares regression line for predicting calories (v) from protein (x). A Y-302.521-0.508x c. Interpret the value of the slope.