3) Please answer the question and show your work in the space provided.The scatterplot below shows the expected longevity of an animal in years and the correspondinggestation time (time in the womb) in days. The residual for a lion is shown on the scatterplot.20.0The equation of the line of best fit is y=6.642+0.03974x. Calculateand explain the meaning of the residual for a bison, which has agestation time of 285 days and an expected longevity of 15 years.17.515.012.510.07.55.02.50.050100150200250300Gestation Time (days)Longevity (years)

The question is based on a residual Given reg. eq : y = 6.642 + 0.03974x where, y : expected…

Answered: 3) Please answer the question and show…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Find the regression equation, letting overhead width be the predictor (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 2.3 cm. Can the prediction be correct? What is wrong with predicting the weight in this case? Use a significance level of 0.05. Overhead Width (cm) Weight (kg) 7.8 175 7.3 9.5 274 7.4 156 9.9 294 9.2 183 256 Click the icon to view the critical values of the Pearson correlation coefficient r. ..... The regression equation is y =+x. (Round to one decimal place as needed.)
Listed below are the overhead widths (cm) of seals measured from photographs and weights (kg) of the seals. Find the regression equation, letting the overhead width be the predictor (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 1.8 cm, using the regression equation. Can the prediction be correct? If not, what is wrong? Use a significance level of 0.05. Overhead Width (cm) 7.3 7.4 9.8 9.5 8.8 8.5 Weight (kg) 152 187 286 247 237 231 The regression equation is y =+ (x. (Round the y-intercept to the nearest integer as needed. Round the slope to one decimal place as needed.)
a. Estimate the regression line and also write the prediction equation. y = 83.4578-5.8795 x y = 5.8795 + 83.4578 x ŷ ŷ= = -5.8795 + 83.4578 x = 83.4578 + 5.8795 x
Find the regression equation, letting the diameter be the predictor (x) variable. Find the best predicted circumference of a beachball with a diameter of 44.4 cm. How does the result compare to the actual circumference of 139.5 cm? Use a significance level of 0.05. Baseball Basketball Golf Soccer Tennis Ping-Pong Volleyball Diameter 7.3 23.8 4.2 22.3 7.1 4.0 21.2 Circumference 22.9 74.8 13.2 70.1 22.3 12.6 66.6 LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r.
Use the estimate yest=3.3x2 - 9.4x - 0.1 to calculate a set of residuals, using a formula or a calculator. Explain your steps, then create a residual plot using this new model and assess its validity
Find the regression equation, letting the diameter be the predictor (x) variable. Find the best predicted circumference of a marble with a diameter of 1.9 cm. How does the result compare to the actual circumference of 6.0 cm? Use a significance level of 0.05. Baseball Basketball Golf Soccer Tennis Ping-Pong Volleyball 5 Diameter 7.4 23.6 4.3 21.7 7.1 3.9 21.5 Circumference 23.2 74.1 13.5 68.2 22.3 12.3 67.5
2
Find the regression equation, letting overhead width be the predictor (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 2.5 cm. Can the prediction be correct? What is wrong with predicting the weight in this case? Use a significance level of 0.05. Overhead Width (cm) 7.6 7.4 9.8 8.8 9.3 7.3 Weight (kg) 142 163 256 188 231 156 The regression equation is y= + x. (Round to one decimal place as needed.) The best predicted weight for an overhead width of 2.5 cm is kg? (Round to one decimal place as needed.) Can the prediction be correct? What is wrong with predicting the weight in this case? A. The prediction cannot be correct because a negative weight does not make sense. The width in this case is beyond the scope of the available sample data. B. The prediction cannot be correct because a negative weight does not make sense and because there is…
Write the linear model to test the hypothesis that there is no treatment effect. Clearly describe each term in the model, and the range of the subscripts. Write the null hypothesis that you are testing. Call: lm(formula = score ~ list, data = hearing) Residuals: Min 1Q Median 3Q Max -14.7500 -5.5833 -0.2083 6.3333 16.4167 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 32.750 1.612 20.315 < 2e-16 *** listList2 -3.083 2.280 -1.352 0.17955 listList3 -7.500 2.280 -3.290 0.00142 ** listList4 -7.167 2.280 -3.144 0.00225 ** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 7.898 on 92 degrees of freedom Multiple R-squared: 0.1382, Adjusted R-squared: 0.1101 F-statistic: 4.919 on 3 and 92 DF, p-value: 0.00325
The following equation describes the relationship between output and labor input at a sample of work stations in a manufacturing plant ŷ = 2.35+2.20X. Suppose, for a selected workstation, the labor input is 5, the predicted output is?
Construct and interpret a 95% prediction interval for the proceeds when the number of issues is 658.
Construct and interpret a 95% prediction interval for the proceeds when the number of issues is 602.

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