b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables?There appears to be a - Select your answer -linear relationship between a and y.c. Try to approximate the relationship between æ and y by drawing a straight line through the data.|to provide a linear approximation of the relationship between æ and y.d. Develop the estimated regression equation by computing the values of bo and bị using equations: (Enter negative values as negative figure)Select your answer -E(z; – 7)(y: – T)bịbo = j – bịax (to 2 decimals)e. Use the estimated regression equation to predict the value of y when a = 6.(to 2 decimals)+ Given are five observations for two variables, a and y.410923145649521028

As per our guidelines we can solve first three subpart and rest can be reposted. Solution-: Given…

Answered: b. What does the scatter diagram…

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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Give the equation of the regression line: -913.2969+0.4808years(y) a) Plug an actual x value into the equation and discuss the difference between the real y and the predicted yb) Discuss the domain of your datac) Include the scatterplot with line of best fit
To what part of the equation of the straight line < Y = MX + C > does the OLS regression coefficient correspond? - This question is based on Data Analysis A. YB. MC. XD. D
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?
Data from 147 colleges from 1995 to 2005 (Lee,2008) were tested to predict the endowments (in billions) to a college from the average SAT score of students attending the college. The resulting regression equation was Y = -20.46 + 4.06 (X). This regression indicates that: a. for every one-point increase in SAT scores, a college can expect 4.06 billion more in endowments. b. most colleges have very high endowments. c. for every one-point increase in SAT scores, a college can expect 20.46 billion fewer in endowments. d. for every one-dollar increase in endowments, the college can expect a half-point increase in SAT scores.
The ages (in years) of five men and their systolic pressures. (You can use technology) Age, x 16 25 39 45 49 Systolic blood pressure, y 109 122 143 132 199 a. calculate the correlation coefficient, r b. calculate the critical r c. Is there a significant linear relationship between x and y? d. find the equation of regression line e Interpret the slope and the y-intercept f. Predict the systolic blood pressure for a man who is 40 years old.
An individual wants to determine how much money a boy scout earns from selling popcorn (Y-variable) based on the length of time (in days) that they went out selling (X-variable). Using the following linear regression equation Ŷ = 5 + 20X: a. State the value of the intercept AND the value of the slope (2 points) b. Based on the given regression equation, what can you determine about the direction of the relationship between X and Y (i.e. is it positive or negative)? (2 points) c. If a boy scout sells popcorn for 4 days, how much money is he predicted to earn? (2 points)
Use the computer output to estimate the intercept BO and the slope B1.The regression equation is Y=795 - 3.25X Predictor Coef SE Coef T P Constant 795.449 86.46 9.20 0.000 X -3.252 1.066 -3.05 0.006 Intercept B 0:Slope B 1:
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The number of hours 6 students spent for a test and their scores on that test are shown below. Hours spent studying, x 1 Test score, y 39 A. Test score 80- Find the regression equation. y = 5.5 x + (35.5) (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) Choose the correct graph below. 0- 1 3 45 52 0 8 Hours studying B. Test score A 80- 3 5 5 48 61 67 0- 0 8 Hours studying N Test score 80- (a) x = 2 hours (c) x = 15 hours 0- 0 8 Hours studying ✔ (b) x = 2.5 hours (d) x = 3.5 hours Test score A 80- 8 0 Hours studying
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 E Click the icon to view the table of lengths and girths. (b) x= 172 cm (c) x= 164 cm (d) x= 158 cm - X The equation of the regression line is y =x+ (Round to two decimal places as needed.) Lengths and Girth Construct a scatter plot of the data and draw the regression line. Plot length on the horizontal axis and girth on the vertical axis. Choose the correct graph below. O A. Length, x Girth, y O B. Oc. 137 106 168 130 153 117 144 105 158 125 159 118 180 120 125 102 137 104 (a) Predict the girth for a length of 140 cm, if it is meaningful. Select the correct choice below and, if…
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…
Suppose Ms. Carr is interested in the y relationship between her students' 9th grade 120 math final exam scores and the number of hours they spent studying during the year. She 100 collects information for 15 ninth grade 80 students and uses it to obtain the regression 60 equation, where x is the number of hours 40 spent studying during the year and ŷ is the predicted final exam score. 20 ŷ = 1.48x + 75.64 10 15 20 25 30 35 The scatter plot displays her results. Study time in hours What is the predicted ŷ-value when a student spends 13 hours studying? Round your answer to one decimal place. Select the correct interpretation. The above predicted value of ŷ is the predicted score of 13 out of 15 students. the predicted final math test score if a student studies 13 hours during the year. what any student will score on the final exam if they study at least 13 hours. the math final test score that 13 students beat. Math test score in points
The table shows the number of goals allowed and the total points earned (2 points for a win, and 1 point for an overtime or shootout loss) by 14 ice hockey teams over the course of a season. The equation of the regression line is y= - 0.558x + 216.186. Use the data to answer the following questions. (a) Find the coefficient of determination, r, and interpret the result. (b) Find the standard error of the estimate, s,, and interpret the result. Goals Allowed, x Points, y 218 212 216 220 257 266 274 200 211 206 216 204 264 244 O 111 106 99 90 86 83 45 105 100 101 94 83 67 68 (a) ? =O (Round to three decimal places as needed.)

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