A paper gives data on x = change in Body Mass Index (BMI, in kilograms/meter2) and y = change in a measure of depression for patients suffering from depression who participated in a pulmonary rehabilitation program. The table below contains a subset of the datagiven in the paper and are approximate values read from a scatterplot in the paper.BMI Change (kg/m²)0.5 -0.5 00.1 0.7 0.811.51.210.4 0.4Depression Score Change -1944581314 17 181214The accompanying computer output is from Minitab.Fitted Line PlotDepression score change = 6.512 + 5.472 BMI change20S5.26270R-Sq27.16%R-Sq (adj) 19.88%15-:10--0.5 0.01.5ⓇS5.26270CoefficientsTermCoefVIFSE Coef2.26T-Value2.88P-Value0.0164Constant6.512BMI change5.4722.831.930.0823 1.00Regression EquationDepression score change = 6.512 + 5.472 BMI change(a) What percentage of observed variation in depression score change can be explained by the simple linear regression model? (Round your answer to two decimal places.)%(b) Give a point estimate of o. (Round your answer to five decimal places.)S =Interpret this estimate.s is the typical amount by which the depression score change value differs fromwhat is predicted using the least squares regression line.(c) Give an estimate of the average change in depression score change associated with a 1 kg/m² increase in BMI change. (Round your answer to three decimal places.)Depression score change品と0.5BMI changeR-sq27.16 %1.0

From given output, the regression equation is given by Depression score change = 6.512 + 5.472 BMI…

Answered: a) what percentage of observed…

A First Course in Probability (10th Edition)

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Chapter1: Combinatorial Analysis

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Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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An economist is interested to see how consumption for an economy (in $ billions) is influenced by gross domestic product ($ billions) and aggregate price (consumer price index). The Minitab output of this regression is reproduced below. Coefficients Term Constant GDP Price Model Summary S 0.299 Error Total Coef Analysis of Variance Source Regression -0.0861 0.7654 -0.0006 R-sq 0.98% DF • 2 7 9 SE Coef 0.5644 0.0574 0.0028 R-sq(adj) 0.98% Adj SS 33.4163 0.6277 34.0440 T-Value O a. 7 O b. 9 O c. 10 O d. Cannot be determined from the information given. -0.1520 13.3400 -0.1290 Adj MS 16.7082 0.0897 P-Value 0.8837 0.0001 0.8330 F-Value P-Value 186.325 0.049 Referring to the table above, how many observations were there in this study?
What is a residual? Explain when a residual is positive, negative, and zero. OA. A residual is the sum of the observed y-value of a data point and the predicted y-value on a regression line for the x-coordinate of the data point. A residual is positive when the point is below the line, negative when it is above the line, and zero when the observed y-value equals the predicted y-value. OB. A residual is the difference between the observed y-value of a data point and the predicted y-value on a regression line for the x-coordinate of the data point. A residual is positive when the point is above the line, negative when it is below the line, and zero when the observed y-value equals the predicted y-value. OC. A residual is the difference between the observed y-value of a data point and the predicted y-value on a regression line for the x-coordinate of the data point. A residual is positive when the point is below the line, negative when it is above the line, and zero when the observed…
A vocational counselor uses the number of days without employment to predict her clients' feelings of self efficacy, measured on a scale of 1 to 5, with higher numbers meaning that clients feel more secure in their job related abilities. The slope of the regression line is –1.02. Which statement is the best interpretation for this finding? a. For every 1-point increase in self-efficacy, there is an associated decrease in the number of days of unemployment. b. For every additional day of unemployment, there is an associated decrease in self-efficacy of 1.02 points. c. The least number of days a person can be unemployed and still feel self-efficacious is 3.98 points d. The decrease in self-efficacy of 1.02 points is caused by each additional day of unemployment
The following is the simple regression results based on the data from Madrigal Corporation: Dependent variable – Machine maintenance costs Independent variable – Machine hours Computed values Intercept P 3,500 Coefficient on independent variable P 3.50 Coefficient of correlation 0.856 R2 0.733 What percentage of the variation in maintenance costs is explained by the independent variable? (use two decimal places, e.g. 82.20%, 55.31% or 0.82, 0.55, these will be counted as correct answers)
Would you please assist in answering this question with working out?Thank you. Q. Using a sample of recent university graduates, you estimate a simple linear regression using initial annual salary as the dependent variable and the graduate's weighted average mark (WAM) as the explanatory variable. If the regression model has an estimated intercept of 2200 and an estimated slope coefficient of 550, what is the predicted starting salary of a student with a WAM of 82?
The table below shows (lifetime) peptic ulcer rates (per 100 population), UU, for various family incomes, xx, as reported by the 1989 National Health Interview Survey. Income 4000 6000 8000 12000 16000 20000 30000 45000 60000 Ulcer rate 14.1 13.1 13.8 12.6 11.8 11.7 11.5 9.3 7.6 (a) Find the equation of the regression line. Ulcer rate, U(x)= . (b) Estimate the peptic ulcer rate for an income level of x0= 25000 according to the linear model in part (a). Ulcer rate, U(x0)= .
Please assist second part? Thank you!
3. Regression analysis breaks scores on the DV into... (explain and give equations)
please answer for what is the p value

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