PART 1. Directions: Use 100 to 250 words to come up with an essay containing your answers to thefollowing guide questions. Provide your own title.1.What are other real-life applications of correlation and regression? Give at least 3.2. The 3rd environmental principle states that "everything is connected to everything else", howare human actions correlated with our environmental issues today?3. Using the principle of linear regression, predict the future of our environment for another 20years if we humans will work hand in hand to care for our planet.

Since you have asked multiple questions, we will solve the first question for you. If you want any…

Answered: PART 1. Directions: Use 100 to 250…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

Refer to the Baseball 2018 data, which reports information on the 2018 Major League Baseball season. Let attendance be the dependent variable and total team salary be the independent variable. Determine the regression equation and answer the following questions. Click here for the Excel Data Filea-1. Draw a scatter diagram.1. On the graph below, use the point tool to plot the point corresponding to the Attendance and its team salary (Salary 1).2. Repeat the process for the remainder of the sample Salary 2, Salary 3, … ).3. To enter exact coordinates, double-click on the point and enter the exact coordinates of x and y. a-2. From the diagram, does there seem to be a direct relationship between the two variables?multiple choice 1 Yes No b. What is the expected attendance for a team with a salary of $100.0 million? (Round your answer to 4 decimal places.) c. If the owners pay an additional $30 million, how many more people could they expect to attend? (Round your answer to 3…
6, 5. Kathy painted a picture and posted it on a social media site. The table shows the number of people who responded that they liked the picture since Kathy posted it. Time Since Picture Was Posted 5. 7. (days) Number of Likes 11 21 38 Write the regression equation that best models the data. a. y = 0.96(1. 55)* b. y = 2.07(1. 38)* c. y = 0.536x – 0.857x + 1.81 d. y = 1.38x´ + 0.30x + 0. 43
A researcher is investigating possible explanations for deaths in traffic accidents. He examined data from 2000 for each of the 52 cities randomly selected in the US. The variables were death and income. Deaths: The number of deaths in traffic accidents per cityIncome: The median income per city The researcher ran a simple linear regression model: Deaths = Bo+B1(Income). Results shown in photo below. Question: Please help me better understand how to use results from photo to find value of R-squared of this simple linear regression model.
Provide an example of a research project in your hometown where you would choose to use linear regression. What variable would be your Y-score, and what variable would be your X-score? What does a regression line represent? What is the standard error of estimate?
Hello tutor, please help me to understand this 2 part MCQ question. Thank you. Part A) Based on Image 1, A researcher examined the relationship between weight (y axis) and height (x axis) among 475 male subjects. He graphed the relationship in the scatter diagram below. Weight is measured in pounds, and height in inches. The equation of the regression line is y = 3.86*x – 110.42. Is it reasonable to presume that if a male is 107 inches tall, his weight will be 302.6 pounds? a) Yesb) No Part B) Based on Image 2, A researcher examined the relationship between Variables X and Y among 150 male subjects, and he graphed a scatter plot as seen below. The correlation coefficient for all the 150 data points is about 0.5. Let K be the correlation coefficient for the data points with X values lying between 130 to 150. Which of the following statements is correct?a) K is less than 0.50.b) K is more than 0.50.c) None of the other options.
Which of the following is true of a linear regression line? a. Located as close as possible to all the points of a scatter chart. B. Is defined by an equation having 2 parameters: the slope and the intercept c. Provides an approximate relationship between the values of two parameters d. All of the above
The following joint frequency distribution table shows responses from a sample of 210 unionized employees on how their union president handled a recent labour action. Employees were categorized by age group and by their level of approval. Age Group Approve Disapprove Indifferent Total under 25 12 31 30 73 25 to 40 26 20 8 54 over 40 38 21 24 83 Total 76 72 62 210 Report answers accurate to at least 4 decimal places. What is the probability that a randomly selected employee:a) did not disapprove? b) was in the 25 to 40 age group and approved? c) was not in the 25 to 40 age group and approved? d) was in the under 25 age group or disapproved? e) was not in the under 25 age group or disapproved? f) was not under 25 and did not disapprove? Given that an employee was in the 25 to 40 age group, what is the probability that the employeea) approved? b) did not disapprove? What is the probability of selecting an employee that was in the under 25 age group from…
Suppose that a simple linear regression model is appropriate for describing the relationship between y = house price (in dollars) and x = house size (in square feet) for houses in a large city. The population regression line is y = 22,500 + 43x and ?e = 4,000. b) Approximately what proportion of 2,000 sq ft homes would be priced over $110,000? (You may need to use a table. Round your answer to four decimal places.) Approximately what proportion of 2,000 sq ft homes would be priced under $100,000? (You may need to use a table. Round your answer to four decimal places.)
The accompanying data are the number of wins and the earned run averages (mean number of earned runs allowed per nine innings pitched) for eight baseball pitchers in a recent season. 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 = 5 wins Click the icon to view the table of numbers of wins and earned run average. (b) x= 10 wins (c) x=21 wins (d) x= 15 wins The equation of the regression line is y = x+ | (Round to two decimal places as needed.) !!
The value of a sports franchise is directly related to the amount of revenue that a franchise can generate. The accompanying data table gives the value and the annual revenue for 15 major sport teams. Suppose you want to develop a simple linear regression model to predict franchise value based on annual revenue generated.
Which of the following statements best describes linear regression? A measure of the degree of dependence between two variables. A statistical technique using pairs of data and identifying a line which ‘best fits’ all of the pairs of observations. A measure of the proportion of changes in the dependent variable which can be explained by a change in the independent variable. Shows individual costs against their associated activity levels but makes no attempt to identify a linear relationship between them.
A social scientist collects information about counties in California and finds that the correlation between average income of the county and a rating of healthcare quality in the county is 0.78. A scatterplot of the two variables is football shaped. A particular county has an average income that is 0.4 SDs above the average of all counties. Using regression, we would predict that its healthcare quality is _________ SDs above the average healthcare quality for all counties, and that it is therefore at the _________ percentile of healthcare quality among all counties. Choose the answer below to fill in the two blanks. Group of answer choices 0.31; 24th 0.78; 58th 0.78; 79th 0.31; 62nd PreviousNext

Recommended textbooks for you

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

Elementary Statistics: Picturing the World (7th E…

Statistics

ISBN:

9780134683416

Author:

Ron Larson, Betsy Farber

Publisher:

PEARSON

The Basic Practice of Statistics

Statistics

ISBN:

9781319042578

Author:

David S. Moore, William I. Notz, Michael A. Fligner

Publisher:

W. H. Freeman

Introduction to the Practice of Statistics

Statistics

ISBN:

9781319013387

Author:

David S. Moore, George P. McCabe, Bruce A. Craig

Publisher:

W. H. Freeman

SEE MORE TEXTBOOKS