1:28 PM Wed Apr 21* 76%88 QStats Exam•..Untitled Notebook (1)Stats ExamSTA 2023 EC Regression1. A doctor wanted to determine whether there is a relationbetween a males age and his HDL cholesterol. He randomlyselected 17 of his patients and determined their HDL levels. Heobtained the following data.Age, x HDL, y38574254463432565535524061426138264738446662305351362745523849553928a) Calculate rb) Calculate the least regression linec) Test whether there is a linear relationship between age andHDL. Let a=0.05d) Construct a 95% Confidence Interval for the slope of theregression line| 1:28 PM Wed Apr 21* 75%88 QStats Exam•..Untitled Notebook (1)Stats Exame) Construct a 95% Confidence Interval for the predicted meanage for a 75 year old male. Let x*=75f) Construct a 95% Prediction Interval for the predicted age for a75 old male. Let x*=75.year2. As concrete cures it gains strength. The following datarepresents the 7 day and 28 day strength (in pounds per squareinch) of a certain type of concrete.7 Day Strength, x 28 Day Strength, y23004070339052202430464028904620333048502480412033805020266048902620419033404630a) Calculate rb) Calculate the least regression linec) Test whether there is a linear relationship between 7-daystrength and 28-day strength. Let a=0.05d) Construct a 95% Confidence Interval for the slope of the

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Description: 1:28 PM Wed Apr 21* 76%88 QStats Exam•..Untitled Notebook (1)Stats ExamSTA 2023 EC Regression1. A doctor wanted to determine whether there is a relationbetween a males age and his HDL cholesterol. He randomlyselected 17 of his patients and determine

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STA 2023 EC Regression 1. A doctor wanted to determine whether there is a relation between a males age and his HDL cholesterol. He randomly selected 17 of his patients and determined their HDL levels. He obtained the following data. Age, x HDL, y 38 57 42 54 46 34 32 56 55 35 52 40 61 42 61 38 26 47 38 44 66 62 30 53 51 36 27 45 52 38 49 55 39 28 a) Calculate r b) Calculate the least regression line c) Test whether there is a linear relationship between age and HDL. Let a=0.05

STA 2023 EC Regression 1. A doctor wanted to determine whether there is a relation between a males age and his HDL cholesterol. He randomly selected 17 of his patients and determined their HDL levels. He obtained the following data. Age, x HDL, y 38 57 42 54 46 34 32 56 55 35 52 40 61 42 61 38 26 47 38 44 66 62 30 53 51 36 27 45 52 38 49 55 39 28 a) Calculate r b) Calculate the least regression line c) Test whether there is a linear relationship between age and HDL. Let a=0.05

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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A movie studio wishes to determine the relationship between the revenue generated from the streaming of comedies and the revenue generated from the theatrical release of such movies. The studio has the following bivariate data from a sample of fifteen comedies released over the past five years. These data give the revenue x from theatrical release (in millions of dollars) and the revenue y from streaming (in millions of dollars) for each of the fifteen movies. The data are displayed in the Figure 1 scatter plot. (The 2nd picture contains the rest of the data as it would not fit in the first pic and it includes the question as well.)
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c. Which of the following is the correct graph of the given data? -ОА. 10 1012 12 10 O C. 12- 81012 1012 Using the graph, explain the dramatic difference between the answers to parts (a) and (b). Choose the correct answer below. OA. The point (10,10) is not an outier, but it does have a strong effect on the least squares line and the correlation coefficient. OB. The point (10,10) does not have any effect on the least squares line and the correlation coefficient. OC. The point (10,10) is an outler that has a weak effect on the least squares line and the correlation coefficient. OD. The point (10,10) is an outlier that has a strong effect on the least squares line and the correlation coefficient.
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A movie studio wishes to determine the relationship between the revenue from the streaming rental of comedies and the revenue generated from the theatrical release of such comedies. The studio has the following bivariate data from a sample of fifteen comedies released over the past five years. These data give the revenue x from theatrical release (in millions of dollars) and the revenue y from streaming rentals (in millions of dollars) for each of the fifteen movies. The data are displayed in the Figure 1 scatter plot. Also given is the product of the theater revenue and the rental revenue for each of the fifteen movies. (These products, written in the column labelled "xy", may aid in calculations.) Theater Rental revenue, y revenue, x xy (in millions of (in millions of dollars) dollars) 61.7 9.7 598.49 15.1 1.7 25.67 45.3 6.3 285.39 28.1 12.1 340.01 49.1 16.1 790.51 xx 12.9 10.2 131.58 28.1 2.4 67.44 66.0 9.7 640.2 20.6 5.8 119.48 7.5 2.8 21 25.8 6.9 178.02 Theater revenue 36.2 12.8…
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A study of emergency service facilities investigated the relationship between the number of facilities and the average distance traveled to provide the emergency service. The following table gives the data collected. Number of Facilities Average Distance (miles) 9 1.67 11 1.11 16 0.84 21 0.61 27 0.51 30 0.48 (a) Develop a scatter diagram for these data, treating average distance traveled as the dependent variable. CELL 0.2 0.4 0.6 0.8 1.2 1.4 1.6 1.8 Number Number Number Distance @ (b) Does a simple linear regression model appear to be appropriate? Explain. O Yes, the scatter diagram suggests that there is a linear relationship. O No, the scatter diagram suggests that there is no relationship. O No, the scatter diagram suggests that there is a curvilinear relationship. (c) Develop an estimated regression equation for the data of the form ý = b + b₁x + b₂x²: a second-order model with one predictor variable. (Round your numerical values to four decimal places.) ŷ =
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