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.

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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

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The President of the Farmers Association wants to know how the amount of fertilizer and theamount of water given to plants affect their growth. The results were inputted into MINITABso as to fit the model. Regression Analysis: Growth versus Water, Fertilizer The regression equation isGrowth = ? + ? Water + ?Fertilizer Predictor Coef SE Coef T PConstant 42.085 ** 3.118 0.009Water 0.178 0.386 0.460 0.654Fertilizer 5.790 0.952 6.083 * S = 6.159 R-Sq = 77.1%% R-Sq(adj) = 73.3% Analysis of VarianceSource DF SS MS F PRegression 2 1532.603 766.301 *** ****Residual Error 12 455. 130 37.928Total 14 1987.733 iv Conduct a hypothesis test, at the 5% level of significance, to determine whether ? is…
Identify the correct statement concerning, r the correlation coefficie between X and Y and the linear regression, Y = aX+b. A. Both can be used to show cause and effect. B. Both quantify the strength of relationship between X and Y. C. X and Y are interchangeable in both relationships. D. Both can be used to make predictions.
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
answer 6
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
Needed to be solved part 36 and 37 correclty in 30 minutes and get the thumbs up. Please show neat and clean work
Many small companies buy advertising without considering its effect. The marketing manager is trying to make the case that "you have to spend money to make money." Spending on billboard advertise ments, in the manager's opinion, has a direct effect on sales. These are records for 7 months in 1000s: Monthly expenditure on 21 25 billboards 16 42 34 10 19 Monthly sales Develop a regression estimating equation. If the monthly expenditure on billboards is 20,000/- what is the monthly sale generated 34 14 48 32 26 29 20
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.)
In this section, we introduced a descriptive measure of the utility of the regression equation for making predictions. a. Identify the term and symbol for that descriptive measure. b. Provide an interpretation.
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.
Below table contains a data sample where X is the independent, and Y the dependent variable. Using the data, please conduct a regression analysis. Determine first the regression equation with the help of below graph and table, then answer all the questions. 1. The value of cell a is 2. The value of cell b is 3: The value of cell c is 4: The value of cell d is 5: The value of cell e is 6: The value of cell f is 7: The value of cell g is 8. The value of cell h is 9: The value of cell i is 10: The value of cell j is 11: The value of cell k is 12: The value of cell l is 13: The value of cell m is 14: The value of cell n is 15: The value of cell o is 16: The value of cell p is 17: The value of cell q is 18: The value of cell r is 19: The value of cell s is 20: The value of cell t is 21: The value of cell u is 22: The value of cell v is 23: The value of cell w is 24: The value of cell x is 25: The value of cell y is 26: The value of cell z is 27: The value of cell aa is 28: The value of cell…

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