The following data is to be used to construct a regression model: X 5 7 4 15 12 9 Y 8 9 12 26 16 13 The regression equation is. O y = 2.16+ 1.37x O y = 0.69 +0.57x Oy=0.57-0.69x O y 1.37 +2.16x O y = 0.57 +0.69x
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![The following data is to be used to construct a regression model:
X 5 7
4 15 12 9
Y 8 9 12 26 16 13
The regression equation is
O y = 2.16+ 1.37x
y = 0.69 +0.57x
O y = 0.57 -0.69x
O y = 1.37 +2.16x
O y = 0.57 +0.69x](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F2c6eeb93-4c54-4557-9f53-f8191d35892c%2F60d3ce1b-997a-4b75-aa1d-298c7fa81c07%2F1pwugl_processed.jpeg&w=3840&q=75)
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- The table below shows the average weekly wages (in dollars) for state government employees and federal government employees for 10 years. Construct and interpret a 99% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $814. The equation of the regression line is y = 1.431x - 17.649. Wages (state), x Wages (federal), y 700 752 790 823 853 877 912 921 949 969 1,027 1,040 1,095 1,143 1,184 1,246 1,270 1,304 1,338 1,402 Construct and interpret a 99% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $814. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) O A. We can be 99% confident that when the average weekly wages of state government employees is $814, the average weekly wages of federal government employees will be between $ and…Seventy-six Starbucks food items were analyzed for the calorie and carbohydrate content. We used linear regression to explore the relationship between the number of calories and amount of carbohydrates (in grams) Starbucks food menu items contain. The estimated regression equation with carbohydrates as the response variable and the calories as the explanatory variable is ŷ = 8.94 + 0.11x, and summary statistics of the two variables is provided below. variable min Q1 median Q3 max mean sd n missing calories 80 300 350 420 500 338.8 105.4 77 carbohydrates 16 31 45 59 80 44.9 16.6 77Used cars 2010 Vehix.com offered several used ToyotaCorollas for sale. The following table displays the ages ofthe cars and the advertised prices. a) Make a scatterplot for these data.b) Do you think a linear model is appropriate? Explain.c) Find the equation of the regression line. d) Check the residuals to see if the conditions for infer-ence are met. Age (yr) Price ($) Age (yr) Price ($)1 15988 6 99951 13988 6 119882 14488 7 89903 10995 8 94883 13998 8 89954 13622 9 59904 12810 10 41005 9988 12 2995
- Process the data in excel and present the results. A researcher is interested in knowing how well he can predict blood pressure from sodium intake. Formulate the regression equation for the data. What would be a likely blood pressure reading for a patient with a sodium intake of 6.0? Of 8.5? Patients Sodium BP 1 6.5 151 2 7.3 170 3 6.6 165 4 7.5 172 5 7.6 187 6 6.7 161 7 6.7 169 8 7.8 192 9 7 185 10 7.4 190 11 6.2 145 12 6.7 143The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. x 11.3 8.5 y 13.4 7 3.6 2.6 2.2 2.6 0.8 11 10.2 7.4 6 5.7 6.3 4.9 * = thousands of automatic weapons y = murders per 100,000 residents Determine the regression equation in y = ax + b form and write it below. (Round to 2 decimal places) A) How many murders per 100,000 residents can be expected in a state with 10.1 thousand automatic weapons? Answer = Round to 3 decimal places. B) How many murders per 100,000 residents can be expected in a state with 9.9 thousand automatic weapons? Answer = Round to 3 decimal places.The following data shows memory scores collected from adults of different ages. Age (X) Memory Score (Y) 25 10 32 10 39 9 48 9 56 7 Use the data to find the regression equation for predicting memory scores from age. The regression equation is: Ŷ = 4.33X + 0.11 Ŷ = -0.11X + 4.33 Ŷ = -0.11X + 13.26 Ŷ = -0.09X + 5.4 Ŷ = -0.09X + 12.6 Use the regression equation you found in question 6 to find the predicted memory scores for the following age: 28 For the calculations, leave two places after the decimal point and do not round: Use the regression equation you found in question 6 to find the predicted memory scores for the following age: 43 For the calculations, leave two places after the decimal point and do not round: Use the regression equation you found in question 6 to find the predicted memory scores for the following age: 50 For the calculations, leave two places after the decimal point and do not round:
- A social scientist would like to analyze the relationship between educational attainment (in years of higher education) and annual salary (in $1,000s). He collects data on 20 individuals. A portion of the data is as follows: Salary 43 49 1 35 Education 7 7 Click here for the Excel Data File a. Find the sample regression equation for the model: Salary Be + B1Education + e. (Round answers to 2 decimal places.) Salary = 37.21 + 6.68 b. Interpret the coefficient for Education. Education As Education increases by 1 year, an individual's annual salary is predicted to increase by $8,590. As Education increases by 1 year, an individual's annual salary is predicted to decrease by $6,680. As Education increases by 1 year, an individual's annual salary is predicted to decrease by $8,590. As Education increases by 1 year, an individual's annual salary is predicted to increase by $6,680. c. What is the predicted salary for an individual who completed 7 years of higher education? (Round coefficient…H. Find the slope and y-intercept of each regression line. Then, determine if the correlation between the variables is positive or negative. (12 points) Regression Line Equation 1. Y = 1.751X – 21.722 Slope y-intercept Kind of Correlation 2. Y = -221.943X+65.434 3. Y = -82.455X –314.986 4. Y = 0.997X + 0.168The table below shows the average weekly wages (in dollars) for state government employees and federal government employees for 10 years. Construct and interpret a 90% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $825. The equation of the regression line is y = 1.597x- 169.203. Wages (state), x Wages (federal), y 742 775 783 802 842 890 912 939 949 954 1,002 1,039 1,097 1,145 1,199 1,242 1,271 1,299 1,335 1,398 Construct and interpret a 90% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $825. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) O A. There is a 90% chance that the predicted average weekly wages of federal government employees is between S and S given a state average weekly wage of $825. O B. We can be 90%…
- The table below shows the average weekly wages (in dollars) for state government employees and federal government employees for 10 years. Construct and interpret a 95% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $895. The equation of the regression line is y = 1.454x- 36.984. Wages (state), x Wages (federal), y 712 778 789 801 843 878 927 937 939 958 1,014 1,054 1,116 1,146 1,191 1,248 1,270 1,302 1,335 1,401 Construct and interpret a 95% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $895. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) O A. We can be 95% confident that when the average weekly wages of state government employees is $895, the average weekly wages of federal government employees will be between $ and…When using population size as the explanatory variable, x, and broadband subscribers as the response variable, y, for data on the number of individuals in a country with broadband access and the population size for 36 nations, the regression equation is y = 4,975,098 +0.0342x. a. Interpret the slope of the regression equation. Is the association positive or negative? Explain what this means. b. Predict broadband subscribers at the (i) population size 7,014,655, (ii) population size 1,155,173,053. c. For one nation, y = 71,110,000, and x = 322,413,902. Find the predicted broadband use and the residual for this nation. Interpret the value of this residual. a. Since the association is positive, the slope means that as the (Type an integer or a decimal.) b. (i) The predicted broadband subscribers for population size 7,014,655 is (Round to the nearest whole number as needed.) population size increases by 1 unit, the number of broadband subscribers tends to increase by 0.0342.Seventy-six Starbucks food items were analyzed for the calorie and carbohydrate content. We used linear regression to explore the relationship between the number of calories and amount of carbohydrates (in grams) Starbucks food menu items contain. The estimated regression equation with carbohydrates as the response variable and the calories as the explanatory variable is ŷ = 8.94 + 0.11x, and summary statistics of the two variables is provided below. variable min Q1 median Q3 max mean sd n missing calories 80 300 350 420 500 338.8 105.4 77 carbohydrates 16 31 45 59 80 44.9 16.6 77
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