3. A biologist was recording various temperatures (in degrees Celsius) and predicting theamount of glucose produced by a plant (in milligrams). Suppose the linear equation wasthe following:ŷ = 2.7 +0.0123x R²a) Based on the coefficient of determination, how would you classify the predictivepower of the model?b) Suppose that a residual plot was the following:25201510J50-5-10-15Residual-20-250510Fitted Values vs. Residuals1520Fitted Value25= 2%303540Is a linear regression model appropriate for this kind of data? Why or why not?

Coefficient of determination : It is stastical measurement that examines how much difference in one…

Answered: 3. A biologist was recording various…

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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Compare the linear regression data for two students walking in front of a motion sensor: Bob’s walk d = 0.75t + 2 r = 0.70 Tracey’s walk d = 0.75t + 2 r = 0.95 a) How are the movements of these walkers similar? different? b) Sketch possible distance versus time graphs for Bob and Tracey.
Which of the slopes matches best with the slope of the data in the scatter plot? would it be m = 3/8?, m = 8/3?, m = - 3/8? or would it be m = - 8/3???
A business analyst found a linear relationship between the predicted profit (in thousands of dollars) with the amount of employees hired (think of the units as per person). The resulting regression equation and coefficient of determination were found to be: ŷ = 10 + 4.5x R² = 72% a) Interpret the slope and y-intercept using the guidelines learned in class. b) Find the predicted profit when the you hire 5 employees. c) Suppose that the true profit when 5 employees are hired is $42 thousand dollars. Find the residual. d) What is the correlation coefficient? Round to three decimal places. e) What is the strength of the correlation coefficient?
Consider the following regression equation: y = -3.9 + 7.2x What does 7.2 depict in the regression equation above? a) The direction of the line. b) The y-intercept. c) The point where x = 0. d) The y when x = 7.2.
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. Xx Y 11.8 14.1 11.5 9.8 7.1 6.2 6.5 x = thousands of automatic weapons y = murders per 100,000 residents 8.6 7 3.3 2.5 2.5 2.6 6 This data can be modeled by the equation y = 0.85x +4.07. Use this equation to answer the following; Answer decimal places. = A) How many murders per 100,000 residents can be expected in a state with 1.2 thousand automatic weapons? Answer = decimal places. Round to 3 0.9 4.7 B) How many murders per 100,000 residents can be expected in a state with 8.5 thousand automatic weapons? Round to 3
Using the weights (Ib) and highway fuel consumption amounts (mi/gal) of the 48 cars listed in the accompanying data set, one gets this regression equation: y = 58 9-0.00749x, where x represents weight Complete parts (a) through (d). Click the icon to view the car data. 東 b. What are the specific values of the slope and y-intercept of the regression line? O A. The slope is 58.9 and the y-intercept is 0.007499. B. The slope is -0.00749 and the y-intercept is 58.9. O C. The slope is 58.9 and the y-intercept is -0.00749. O D. The slope is 0.00749 and the y-intercept is 58.9. c. What is the predictor variable? O A. The predictor variable is highway fuel consumption, which is represented by x. B. The predictor variable is weight, which is represented by x. O C. The predictor variable is weight, which is represented by y O D. The predictor variable is highway fuel consumption, which is represented by y. d. Assuming that there is a significant linear correlation between weight and highway fuel…
What is the plot of 2/3
If the regression line showing the effect of education on income has a slope of 1000. a) the variables are not related b) the Y intercept would be 1.00 c) every change in education increases income d) every year of education increases income by 1000
Below is the output from regression. Use the p-value and decide if the equation is good to use for forecasting. Group of answer choices A.) p-value = 82 - equation is good to use B.) p-value = 0.15 - equation is not good to use C.) p-value = 0.18 - equation is not good to use D.) p-value = -16 - equation is good to use
The accompanying data are the length (in centimeters) and girths (in centimeters) of 12 harbor seals. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x=140 cm (b) x=172 cm (c) x=164 cm (d) x=158 cm Length, x Girth, y138 106168 130153 116144 105159 126158 119124 103137 103154 121148 111147 106145 110 The equation of the regression line is y=____x + ___
The following data refers to the amount of caffeine (in mg) consumed by ten university students and their time to complete a practice quiz (in minutes) for a Econominc Exam. Time Caffeine 75 180 83 150 65 195 60 240 82 120 58 280 52 270 66 190 55 300 60 250 Calculate the slope and y-intercept for the data above, provide the equation for the line of best fit and interprt the slope and y intercept for the data Let y = time and x = caffeine amount.

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