The data below are the temperatures on randomly chosen days during a summer class and the number of absences on those days. Find the equation of the regression line for the given data.Temperature, x7285919088987510080Number of absences, y371010815415A. y= 30.27x+ 0.449%3DВ.y = 0.449x + 30.27C. y = 0.449x - 30.27D. y = 30.27x- 0.449

Given data is Temperature x 72 85 91 90 88 98 75 100 80 No. of absences y 3 7 10 10 8 15 4 15 5

Answered: The data below are the temperatures on…

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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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.
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
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 table below shows the heights (in feet) and the number of stories of six notable buildings in a city. 483 Height, x Stories, y 772 628 518 508 51 48 45 42 496 37 (a) x=499 feet (c) x=315 feet (b)x=639 feet (d) x = 732 feet 35 Find the regression equation. ŷ=x+ (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) Choose the correct graph below. O C. OB. O D. OA. Q Q ↓ 0 0 Height (feet) Height (feet) (a) Predict the value of y for x = 499. Choose the correct answer below. OA. 51 OB. 40 60+ 0- 800 60+ 0- 800 Q A 60- → 0 Height (feet) 800 60- 0- 800 0 Height (feet)
4
PLEASE ANSWER 4,5 AND 6
n order for applicants to work for the foreign-service department, they must take a test in the language of the country where they plan to work. The data below shows the relationship between the number of years that applicants have studied a particular language and the grades they received on the proficiency exam. Find the equation of the regression line for the data. given Number of years, x 4 5 3 6 2 7 3 Grades on test, y 61 68 75 82 73 90 58 93 72 O A. y 6.910x+46.261 O B. -46.261x +6.910 O C. =6.910x-46.261 O D. = 46.261x-6.910 Next Time Remaining: 01:02:25 74°F Mostly 五 TTL
The table below shows the age of 8 individuals and the packs of medicine they consume each year. Age 17 27 54 35 42 31 46 23 Medicine (in packs) 17 7 12 6 2 a. Determine the correlation coefficient r between the two variables. Answer rounded to at least 4 decimal places. b. Determine the slope coefficient B1 for the regression of medicine packs consumed on age. Answer rounded to at least 4 decimal places. c. Determine the y-intercept Bo for the regression of medicine packs consumed on age. Answer rounded to at least 4 decimal places. d. What will be the expected packs of medicines consumed per year by a person of age 33. Answer rounded to at least 4 decimal places. packs
If the regression equation is ỹ =1.3+0.20x, and r =0.81 then the correlation is equal to O -0.09 O -0.90 O none O 0.20 O -0.20 O 0.90
Bluereef real estate agent wants to form a relationship between the prices of houses, how many bedrooms, House size in sq ft and Lot Size in sq ft. The data pertaining to 100 houses were processed using MINITAB and the following is an extract of the output obtained: The regression equation is Price = B + ¢Bedroom + yHouse Size + ALot Size Predictor Coef SE Coef T P Constant 37718 14177 2.66 ** Bedrooms 2306 6994 0.33 0.742 House Size 74.3 52.98 0.164 Lot Size -4.36 17.02 -0.26 0.798 S= 25023 R-Sq=56.0% R-Sq (adj) =54.6% Source DF MS F P Regression Residual 76501718347 25500572782 *** **** Error 96 60109046053 626135896 Total 99 d) Is y significantly different from -0.5? e) Perform the F test at the 1% level, making sure to state the null and alternative hypotheses. f) Give an interpretation to the term “R-sq" and comment on its value.
Use the regression equation to predict the value of y for x = -1.6. Assume that the variables x and y have a significant correlation. -5-34 1 -1-2 X 0 2 3 -4 y - -10 8 9 1 -2-6 -1 3 6 -8 OA. 1.214 OB. -2.803 O C. 2.980 OD. -3.907

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