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- I need help to interpret the slope of the scatter plot and to do the linear regression equationPlease fill in empty box, thank you :)Listed below are the overhead widths (cm) of seals measured from photographs and the weights (kg) of the seals. Overhead width 7.2 7.4 9.8 9.4 8.8 8.4 Weight 116 154 245 202 200 191 The four pairs of values below were obtained from the regression equation. Which is an extrapolation? a) overhead width 7.5 cm, weight 144 kg b) overhead width 10 cm, weight 245 kg c) overhead width 7.2 cm, weight 132 kg d) overhead width 8.1 cm, weight 169 kg
- The following data are the monthly salaries and the grade point averages for students who obtained a bachelor's degree in mathematics. GPA: 2.6, 3.4, 3.6, 3.2, 3.5, and 2.9; Monthly Salary: 330o, 3600, 4000, 3500, 3900, and 3600. Plot the scatter diagram showing the deviations about the estimated regression line and the line y = y(bar).Which of the following is not one of the uses of a scatter plot and regression line a. to estimate the average y at a specific value of x. b. All three are uses of the scatterplot and regression line c. to determine if a change in x causes a change in y d. to predict y at a specific value of x.Measurements of the electrical resistivity of tungsten at specified temperatures are presented in the table below. The error in the determination of the temperature was negligible. The temperatures are stated as absolute temperatures in °K. The units of resistivity are u Ncm . Carry out a regression analysis for resistivity as a function of temperature. Temperature Resistivity 300 5.54 Include a scatterplot showing the residuals vs temperature. 400 7.95 Do the regression assumptions appear to be valid? 500 11.00 600 12.28 Include a scatterplot showing the raw data points as black circles as well as a continuous blue line representing the regression model. 700 15.95 800 18.46 Find the lower and upper limits for a 99% confidence interval for the slope of the regression model. Add a pair of red lines to the scatterplot: both passing through the centroid of the data, one having the slope corresponding to the lower bound of the confidence interval, and the other having the slope…
- Use the Stata output below. The data comes from students in an undergraduate economics course. The regression of interest is: final =B₁ + B₁ atndrte + ß₂hwrte + ¸priGPA+ ¹ ACT .reg final atndrte hwrte priGPA ACT Source Model 3094.70776 11929.9465 Residual Total final SS atndrte hwrte priGPA ACT _cons 15024.6543 df 773.676939 4 669 17.832506 MS 673 22.324895 Coef. Std. Err. .0138725 .0183476 .010863 1.906347 .3750236 .3990516 .0535332 9.225908 1.46863 Number of obs F(4, 669) Prob > F R-squared Adj R-squared Root MSE t P>|t| ||||||||||||| 674 [95% Conf. Interval] Approximate the p-value from the null hypothesis that all of the slope parameters are equal to zero.Interpret the following three sets of data (X versus Y) using scatter chart and regression analyze X: C16 (number of cars on the sales lot) versus Y: C17 (cars sold per day)The arm span and foot length were both measured (in centimeters) for each of 20 students in a biology class. The computer output displays the regression analysis. Predictor Coef SE Coef t-ratio Constant Arm span -7.611 2.567 2.965 0.046 0.186 0.035 5.377 0.000 S = 1.61 R-Sq = 63.0% R-Sq (Adj) = 64.9% Which of the following is the best interpretation of the standard deviation of the residuals? The typical arm span is 161 centimeters. The typical foot length is 16.1 centimeters. The typical distance between the observed and predicted arm spans is 1.61 centimeters. The typical distance between the observed and predicted foot lengths is 1.61 centimeters. Op
- The dataset below contains synthetic records of human heights and weights of 18 years old children. HEIGHT WEIGHT (Feet) (in kg) 5.48 51.36 5.96 62.04 5.78 69.56 5.69 64.70 5.65 65.59 5.73 56.05 5.82 64.31 5.83 62.03 а. Find the equation of the regression that model the relationship between the weight of mail and number of order using LINEAR EQUATION, EXPONENTIAL EQUATION, SIMPLE POWER EQUATION, and HYPERBOLIC| EQUATION. b. Compute for the correlation coefficient of each equation using PEARSON PRODUCT MOMENT CORRELATION COEFFICIENT (PPMCC).The following table contains ACT scores and the GPA for eight college students. Estimate the relationship between GPA (yi) and ACT (x;) using OLS regression by hand. Report the intercept and slope estimates: Student 1 2 3 4 5 6 7 8 GPA 2.8 3.4 3.0 3.5 3.6 3.0 2.7 3.7 ŷ₁ =B₁ + B₁x₁ ACT 21 24 26 27 29 25 25 30 y X ŷ₁Please do only the last three