1.Given the data below, compute the following:a.Correlation coefficienti. r=ii. Is the relationship (select one).Strongly correlatedModerately correlated• Weakly correlated• No correlationiii. In what direction is the correlation, interpret in the context of the data.Calculate the SlopeC.Calculate the Interceptd. Use parts b. and c. to write down the regression equation.Hours xTestScoresnHoursScoreHours^2Score ^2Studying040251464569735756937909795SUMSe.Use the regression equation to predict the test scores (y's) for the given hours of stui. X=3 hoursii. X=6.5 hoursb.123456785

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Answered: 1. Given the data below, compute the…

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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Dr. Wabld Hamdy given by the following table: y X-4 -2 2 4 --2 0 0.25 0 0 -100 0.25 1 0.25 00 0 2 0.25 0 Find the correlation coefficient between X and Y llu mad and imported automobiles sold
3. The speed (in miles per hour) of 8 vehicles and their braking distance (in feet) when stopping on a dry surface speed, x braking distance, y 20 30 40 50 50 60 65 70 55 72 75 110 138 162 193 225 type of correlation: Conclusion
OA. The scatterplot indicates there is a negative, strong, linear relationship between Median Salary and Annual Sales. OB. The scatterplot indicates there is a negative, weak, linear relationship between Median Salary and Annual Sales. OC. The scatterplot indicates there is a positive, strong, linear relationship between Median Salary and Annual Sales. OD. The scatterplot indicates there is a positive, weak, linear relationship between Median Salary and Annual Sales. OE. The scatterplot indicates there is no relationship between Median Salary and Annual Sales.
Which of the following correlation coefficients indicate the strongest relationship between two variables? A .20 B .87 C .80 D -.95
Use the data in the table, which shows the average annual salaries (both in thousands of dollars) for public school principals and teachers in the U.S. for 11 years. Apply what you have learned in the previous tab to complete this graded lab questions. 1. Repeat the steps from tab #1 using this data to construct a scatter plot graph and calculate the correlation coefficient R. (Recall the corelation coefficient is R and not R Teachers y Principalsx 77.8 43.7 78.4 43.8 80.8 45.0 R= 80.5 45.6, 2. Does the R value represent a positive, negative or no correlation between the salaries ol the teachers and principals? As teacher salaries increase, what happens to prinicipal salaries? 10 11 81.5 45.9 84.8 48.2 12 13 87.7 49,3 3. Write the equation of the regression line for the data below. The equation is y= 14 91.6 51.3 52.9 Teachers y 15 16 95.7 54.4 COD 54.2 =D0.5873x-2.0s07o R=0.995, 17 95.7 4. Use the regression equation that you found in exercise #3 to predict the average annual salary…
L3Q8.Find the type of relationship that exists between the two variables x and y in the scatter plot. A.Zero correlation B.Negative correlation C.Positive correlation D.None of the choices
Answer 21-24 thank you
the number of rubber bands used and the distance, incentimeters, of her jump. When they created a scatterplotthe relationship appeared to be linear, and the correlationwas r = 0.996. After discussing these results, the teacherinstructed the students to convert the distances to inches.What effect will this have on the correlation between thetwo variables?a) Because 1 cm = 0.393701 inches, the correlationwill become .392126.b) Because 1 cm = 0.393701 inches, the correlationwill become 2.5298.c) Because only the length measurements have changed,the correlation will decrease substantially.d) Because changing from centimeters to inches doesnot affect the value of the correlation, the correlationwill remain 0.996. e) Because inches is a much more common measure-ment for distance in the United States, the relation-ship between the data will be stronger and thus the correlation will increase.
Consider the bivariate data set with n = 7 observations X -4 1 -6 9. -8 -4 -4 Y 20 60 -10 99 -3 16 18 where a linear relationship between X and Y is investigated. The equation relating Y to X is formulated by Y = Bo + B1X + e and is called the simple linear regression equation. Use your calculator to answer the following questions. Give the values of the least squares estimates Bo Round your answer to the nearest integer. Round your answer to 3 decimal places.
Write a report using Word. Cover the following topics. This file contains some information about different cars. Car Weight (pounds), x Miles per Gallon, y A 2750 31.5 B 3120 27.9 C 3385 23.7 D 3740 23.3 E 4225 21 Create a scatterplot for the data in the Weight and Braking columns. Paste it here. a) Using StatCrunch or TI 83/84 to calculate the linear correlation between the data in the Weight and MPG columns. b) Explain the mathematical relationship between Weight and MPG based on the linear correlation coefficient. Be certain to include comments about the magnitude and the direction of the correlation. c) Write the equation for the least-squares regression line if there is one. d) Predict the miles per gallon of car C and compute the residual.
The following table shows the values of the age and the job satisfaction of ice cream shop employees Employee Age Job Satisfaction16 918 920 722 824 426 528 626 524 722 8 d. Sketch a scatterplot of this data by hand (do NOT use/submit any plots created by a program).e. Does there appear to be a linear relationship between the two variables? f. Calculate the slope for this data.

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