STRUCTURED QUESTIONGRAPH SHEET REQUIRED FOR THIS QUESTIONThe following table shows, for a sample of towns in Great Britain, the number ofsolicitors, x, and the number of cars stolen last week, y.12711192134171518y1432128643112302529(i)Using the data in the table, plot a scatter graph and state the relationship betweenx and y.(ii)Determine the equation to the regression line and estimate the number of carsstolen when the number of solicitors was:(a) 13(b) 20(iii)Using relevant information from part (ii) above, draw the line of best fit.(iv)On your graph, highlight the points (0, a), (x,ỹ) and explain what each represent.(v)Calculate the value of the product moment correlation coefficient r for the data.(vi)Comment on the suggestion that most car thieves are solicitors.

As per our guidelines, we are allowed to answer first three sub-parts. Thanks Given Data : X Y…

Answered: The following table shows, for a sample…

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 table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age Bone Density34 35745 34148 33160 32965 325 Step 2 of 6: Find the estimated y-intercept. Round your answer to three decimal places.
Let x be the weight of a car (in hundreds of pounds), and let y be the miles per gallon (mpg). Suppose a car weighs 3800 pounds. What does the data forecast for the miles per gallon expected? x= 27 44 32 47 23 40 34 52 y= 30 19 24 13 29 17 21 14 State the correlation coefficient and state the regression lin equation.
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. X Y 11.4 8.6 7.2 3.6 13.5 11.3 10.1 x = thousands of automatic weapons y = murders per 100,000 residents 2.4 2.8 2.3 0.9 7 6.1 6.6 5.9 4.7 This data can be modeled by the equation y = 0.83x +4.06. Use this equation to answer the following; Special Note: I suggest you verify this equation by performing linear regression on your calculator. Answer = A) How many murders per 100,000 residents can be expected in a state with 2.7 thousand automatic weapons? Answer = Round to 3 decimal places. B) How many murders per 100,000 residents can be expected in a state with 11 thousand automatic weapons? Round to 3 decimal places.
9. Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in milligrams) for 6 beef hot dogs are shown in the table below. Calories, x Sodium, y 160 130 330 120 70 190 (a) x = 170 calories (c) x = 150 calories 180 (b) x = 80 calories 420 470 360 250 530 (d) x = 210 calories Find the regression equation. x+( (Round to three decimal places as needed.) y = Choose the correct graph below. OA. О В. OC. OD. 560- 560 560 560- 200 G 0IN T> 200 200 Calories Calories Calories Calories (a) Predict the value of y for x = 170. Choose the correct answer below. O A. 411.632 O B. 543.752 O C. 455.672 O D. not meaningful (b) Predict the value of y for x = 80. Choose the correct answer below. O A. 411.632 О В. 257.492 O C.…
The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age 39 43 46 61 64 Bone Density 352 346 321 314 312 Table Step 1 of 6 : Find the estimated slope. Round your answer to three decimal places
The following data represent the number of flash drives sold per day at a localcomputer shop and their prices.Price Units Sold34 336 432 635 530 938 240 1a. Develop the estimated regression equation that could be used to predict thequantity sold given the price. Interpret the slope.b. Did the estimated regression equation provide a good fit? Explain.c. Compute the sample correlation coefficient between the price and the number offlash drives sold. Use a= 0.01 to test the relationship between price and units sold.d. How many units can be sold per day if the price of flash drive is set to $28.
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
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 ŷ₁

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