Calculate Pearson's correlation coefficient r. Then explain the direction and strength of the relationship based on the r. 12345678ABCCollege ID Accept rate (%) Grad rate (%)159659769589810961094158515931584169218891896209020862485257625868078849101112131415161718192072222122233424568LOSA EN234791011121314151617181920282829 (Round calculated results to the hundredth (2nd place to the right of the decimal) when result extendsbeyond that unless otherwise noted).It is generally believed that there is a relationship between a college's acceptance rate and itsgraduation rate. I wanted to know how strong this relationship is within the top universities in thecountry, so I collected the graduation rate and acceptance rate data of a randomly selected sample ofuniversities from all the top U.S. universities (with an acceptance rate at or below 30%). The data set isin Tab Q2 of the Excel data file.Ola Create a scatter plot between the two variables using Excel. Paste the plot here and format it into

Obtain the value of the correlation. The value of the correlation is obtained below as follows:

Answered: Calculate Pearson's correlation…

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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#2 and #3
Match the correlation coefficients with their scatterplots. Select the letter of the scatterplot below which corresponds to the correlation coefficient. (Click on image for a larger view.) B v 1. r = -0.74 с A ✓ 2. r = -0.49 3. r = -0.97 4. r = 0.76 A B D
An educator wants to see the number of absences(X) a student in her class has affects the Student’s final GPA(Y)a) Find Correlation coefficient b) Draw a Scatter plot c) Find the Regression equation of Y on X d) Predict the student’s GPA when X = 6 x 4 5 2 8 3 10 7 y 2.5 2.3 4 2.1 3.3 1.7 2.3
A study is conducted to determine the relationship between a driver’s age and the number of accidents he or she has over a 1-year period. The data are presented in table below. c. Test the significance of the correlation coefficient at  = 0.05. d. Is it significant to construct a regression equation?
Find the equation of the regression that model the relationship between the weight of mail and number of order using HYPERBOLIC EQUATION. Compute for the correlation coefficient using PEARSON PRODUCT MOMENT CORRELATION COEFFICIENT (PPMCC).
Need help answering A, B and C. B) Perform the linear regression calculation and provide the linear regression equation that describes the relationship between Y (number of air conditioning units sold) and X (outside temperature in degrees Fahrenheit. Calculate: Coefficient of determination (r2) and the coefficient of correlation (r).  SST, SSE and SSR for this linear regression.  Estimate for the variance (σ2) and the standard deviation for the linear regression model you have developed. C) Using the linear regression equation that you developed in topic (b), calculate the estimated sales for a day that will reach 72 degrees F and for a day that will reach 94 F and for both temperature levels calculate the error “e” when comparing the estimated value against the actual data provided. At which of the two temperatures, is your model more accurate? Justify.
A random sample of college students was surveyed about how they spend their time each week. The scatterplot below displays the relationship between the number of hours each student typically works per week at a part- or full-time job and the number of hours of television each student typically watches per week. The correlation between these variables is r = –0.63, and the equation we would use to predict hours spent watching TV based on hours spent working is as follows: Predicted hours spent watching TV = 17.21 – 0.23(hours spent working) Since we are using hours spent working to help us predict hours spent watching TV, we’d call hours spent working a(n) __________________ variable and hours spent watching TV a(n) __________________ variable. The correlation coefficient, along with what we see in the scatterplot, tells us that the relationship between the variables has a direction that is _________________ and a strength that is ______________________. According to the…
How does multiplying each score by a (positive) constant affect the value of the correlation? The correlation changes sign. The correlation does not change. The correlation decreases. The correlation increases.
The ages (in years) of five men and their systolic pressures. (You can use technology) Age, x 16 25 39 45 49 Systolic blood pressure, y 109 122 143 132 199 a. calculate the correlation coefficient, r b. calculate the critical r c. Is there a significant linear relationship between x and y? d. find the equation of regression line e Interpret the slope and the y-intercept f. Predict the systolic blood pressure for a man who is 40 years old.
Which of the following denotes the slope or the regression coefficient for X? A) The term a B) The term b C) The error term D) The correlation coefficient, r
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The number of hours 6 students spent for a test and their scores on that test are shown below. Hours spent studying, x Test score, y 4 (a) x = 2 hours (c) x = 13 hours (b) x= 2.5 hours (d) x = 4.5 hours 2 3 5 40 45 52 49 63 70 Find the regression equation. ý =x+ (O (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) Choose the correct graph below. O A. OB. OC. OD. 80- 80- Hours studying Hours studying Hours studying Hours studying (a) Predict the value of y for x= 2. Choose the correct answer below. O A. 52.2 О В. 49.2 ОС. 64.2 O D. not meaningful (b) Predict the value of y for x = 2.5. Choose the correct answer below. O A. 115.4 О В. 52.2…
The following table shows students’ number of absences, x, and the student’s final grade,, y.# of absences x 6 2 15 9 12 5 8 Final grade y 82 86 43 74 58 90 78a) Calculate r, the correlation coefficient ________________b) Find the equation of the regression line __________________________________c) If a student is absent 4 times,, what grade does your regression line predict?__________________

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