The accompanying data gives the high and low temperatures in January for a random sample of 50cities.a. Decide whether use of the linear correlation coefficient as a descriptive measure for the data isappropriate.b. If appropriate, obtain the linear correlation coefficient.c. If appropriate, interpret the value of r in terms of the linear relationship between the two variables.Click the icon to view the High and Low data values.a. The linear correlation coefficient as a descriptive measure for the databecauseb. Select the correct choice and, if necessary, fill in the answer box to complete your choice.O A. The linear correlation coefficient isappropriate(Round to three decimal places as needed.)OB. The linear correlation coefficient as a descriptive measure for the data is not appropriate.c. Choose the correct answer below.O A. There appears to be a strong negative linear association between the two variables.B. There appears to be a weak negative linear association between the two variables.OC. There appears to be a weak positive linear association between the two variables.O D. There appears to be a strong positive linear association between the two variables.O E. The linear correlation coefficient as a descriptive measure for the data is not appropriate. High and Low dataHigh(x)31349487696062584031235445397382795082Low(y)NNNNS 422227471554545413321184536334573763871High(x)34606361863383385069314958338227464682Low(y)284146517923683441482442522578153439640I

Given data indicates the high and low temperatures in January for a random sample of 50 cities.

Answered: The accompanying data gives the high…

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 data presented below are observed groundwater levels, and model calculated groundwater levels. a. Compute the Pearson correlation coefficient for the relationship between Observed Head and Computed Head. Discuss the result. b. Draw a scatter diagram with Observed Head on the Ordinate and Computed Head on the Abscissa. Discuss the plot.
The ages (in years) of 10 men and their systolic blood pressures (in millimeters of mercury) are shown in the attached data table with a sample correlation coefficient r of 0.900. Remove the data entry for the man who is 50 years old and has a systolic blood pressure of 201 millimeters of mercury from the data set and find the new correlation coefficient. Describe how this affects the correlation coefficient r. Use technology. Click the icon to view the data set. Data Table 1. The new correlation coefficient r going from 0.900 to | (Round to three decimal places as needed.) Systolic blood Age, x pressure, y this cyc 16 109 12/24/1 24 122 145 39 stion 131 46 201 50 182 64 stions 199 70 29 130 ng Quest 58 177 118 22 ered Que cted Quest Done Print Enter your answer in the answer box. ch tv DEC MacBook Pro DII F11 F10 F9 F8 F7 ...
Based on the data below, answer the following question: Draw a scatter diagram that highlights the relationship between Local tuition and Starting Salary in Excel. Based on the scatter diagram, the direction of the correlation indicates that students' salaries tend to be _______ if the school charges higher local tuition. Select one: a. higher b. lower Business School Full-Time Enrollment Students per Faculty Local Tuition ($) Foreign Tuitiion ($) English Test Work Experience Starting Salary ($) 1 Melbourne Business School 200 5 24,420 29,600 No Yes 71,400 2 University of New South Wales (Sydney) 228 4 19,993 32,582 No Yes 65,200 3 Indian Institute of Management (Ahmedabad) 392 5 4,300 4,300 No No 7,100 4 Chinese University of Hong Kong 90 5 11,140 11,140 No No 31,000 5 International University of Japan (Niigata) 126 4 33,060 33,060 Yes No 87,000 6 Asian Institute of Management (Manila) 389 5 7,562 9,000 No Yes 22,800 7 Indian Institute of Management…
For the data below, draw a scatter plot on each graph provided. Then use your graphing calculator to find the line of best fit and the correlation coefficient. Round all numbers to three decimal places. Line of Best Fit:Correlation Coefficient:What conclusions can you draw about the relationship between calories and fat?Line of Best Fit:Correlation Coefficient: What conclusions can you draw about the relationship between calories and sodium? If you are asked to report your opinion on which relationship is stronger: calories and fat, or calories and sodium, what would your opinion be? Why?
Which of the following values of the correlation r indicates the strongest correlation between the two variables? Select one: a. r = 1.22 b.r = 1.22 C.r = 0.75 d. r = -0.81 e.r = -1.90
The ages (in years) of 10 men and their systolic blood pressures (in millimeters of mercury) are shown in the attached data table with a sample correlation coefficient r of 0.910. Remove the data entry for the man who is 49 years old and has a systolic blood pressure of 199 millimeters of mercury from the data set and find the new correlation coefficient. Describe how this affects the correlation coefficient r. Use technology. Age, x Systolic blood pressure, y 16 110 26 122 39 142 44 132 49 199 64 185 72 199 31 130 56 174 23 117 Click the icon to view the data set. The new correlation coefficient r ▼ A. gets stronger, b.gets weaker, C.stays the same, going from 0.910 to= . (Round to three decimal places as needed.)
Assume that you have paired values consisting of heights (in inches) and weights (in Ib) from 40 randomly selected men. The linear correlation coefficient r is 0.587. Find the value of the coefficient of determination. What practical information does the coefficient of determination provide? Choose the correct answer below. O A. The coefficient of determination is 0.655. 65.5% of the variation is explained by the linear correlation, and 34.5% is explained by other factors. O B. The coefficient of determination is 0.345. 65.5% of the variation is explained by the linear correlation, and 34.5% is explained by other factors. O C. The coefficient of determination is 0.655. 34.5% of the variation is explained by the linear correlation, and 65.5% is explained by other factors. O D. The coefficient of determination is 0.345. 34.5% of the variation is explained by the linear correlation, and 65.5% is explained by other factors. Click to select your answer. 3:54 PM e Type here to search…
Decide whether the variables represented by the scatter plots below are positively or negatively correlated. Use P for positively and N for Negatively.
10. Please answer
Y 2. Describe the direction and strength of the correlations from the following scatterplots. (Are they weak, moderate, strong, or no correlation? Positive, negative, or no correlation?) X X X Y
7. Given the situation, determine what type of correlation: Positive Negative No Correlation a. Speed of a car and amount of speeding tickets Positive Negative No Correlation b. Size of your shoe and size of dog Positive Negative No Correlation c. Size of your shoe and your height Positive Negative No Correlation d. Amount of points scored and your jersey number Positive Negative No Correlation e. Paycheck size and water bill amount Positive Negative No Correlation f. Number of calories eaten and the number of bags of Takis eaten Positive Negative No Correlation g. The temperature outside and the amount of air conditioning used 12
Given the following data, do the tasks stated below. a) Identify the independent variable and the dependent variable. b) Construct a scatter plot. c) Determine the direction of the straight line that the data points seem to follow. d) Determine the strength of the correlation between the two variables.

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