P(Getting a 3 and a 5 when a fair die is thrown once) =Which correlation coefficient, r, and which regression line equation, would mostlikely correspond to the scatter plot below?6.Scatter Plot for Question 6r valuesRegression Line12Equations(J). r= 410(A).Ý = 1.9 + 1.7x8(K). r = -1.9Ý = 0 – 126(B).(L). r = 0.964(C).Ý = 1.9 – 0.96 x2(M). r = 0(D).Ý = 4 + 5x – 6x1(N). r =- 0.9623X46Please write your name on each sheet of PaperPage 3 of 4

Here given scatter plot and identifying regression line

Answered: Which correlation coefficient, r, and…

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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A regression between foot length (response variable in cm) and height (explanatory variable in inches) for 42 students resulted in the following regression equation: y = 10.4 + 0.21x If a student happened to be extraordinarily tall (say, 10ft, just for the fun of it) and had a foot size of 25 cm, how might this affect the slope of the regression line?
Please no written by hand solutions 3. A researcher is interested in the correlation between a person’s age and the amount of sleep they get. He uses a poll to collect representative data for 2,000 people. The researcher performs a regression, with a dependent variable of minutes per week spent sleeping, and an independent variable of age in years. The regression results are as follows: - (Intercept): 150 - age: -5 Answer the following: - What is the regression line? - What is the predicted number of minutes sleeping for someone who is 20 years old? - The researcher is also interested in the relationship between age, sleep, and politics. Each person who responds to the poll chooses a value for liberal between 0 (very conservative) and 100 (very liberal) to describe their politics. The researcher performs a regression with the same independent variable of minutes per week sleeping, and dependent variables of age and liberal. The regression results are as follows: - (Intercept):…
(New Question) Which of the following is true about panel data regression? In panel data, there is a possibility of autocorrelation because of the correlation between u and u, where ujt and u are error terms for entity i and j. O Fixed effect model imposes the same intercept across the entities but allows for different slopes in estimation. O Panel data can be more useful than cross-sectional data because with panel data it is possible to estimate the regression coefficients even if X is fixed over time within entities. O The time-demeaned OLS regression transforms the data by deviating X and Y by the average across entities at each time t.
I’m taking a statistics and probability class. Please get this correct because I want to learn. I have gotten wrong answers on here before
Data from the United Nations on individual countries Obesity rates and vegetable consumption by country were organized into the scatter plot below. Linear Regression Equation for this data: y = -0.8449x + 50.328 Correlation Coefficient: 0.5 --- The data on this table can be simplified into a single statement. Which of the following statements would be the most accurate based on the chart, equation, and correlation coefficient? Question 10 options: As vegetable consumption goes up, obesity rates would tend to decrease. As vegetable consumption goes down, obesity rates would tend to increase. As vegetable consumption goes up, obesity rates would tend to increase. As vegetable consumption goes down, obesity rates would tend to decrease.
You are given below the following information about advertising and sales. Adv. Exp. (X) (S Lakhs) Sales (Y) Lakhs) Мean 10 90 S.D. 3 12 Correlation Coefficient 0.8 (a) Calculate the two regression lines. (b) Find the likely sales when advertisement expenditure is (c) What should be the advertisement expenditure if the company wants to attain a sales target of 15 lakhs. 120 lakhs ?
Question 6, 3.3.30
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.
Question 6, 3.3.30
The following data shows memory scores collected from adults of different ages. Age (X) Memory Score (Y) 25 10 32 10 39 9 48 9 56 7 Use the data to find the regression equation for predicting memory scores from age. The regression equation is: Ŷ = 4.33X + 0.11 Ŷ = -0.11X + 4.33 Ŷ = -0.11X + 13.26 Ŷ = -0.09X + 5.4 Ŷ = -0.09X + 12.6 Use the regression equation you found in question 6 to find the predicted memory scores for the following age: 28 For the calculations, leave two places after the decimal point and do not round: Use the regression equation you found in question 6 to find the predicted memory scores for the following age: 43 For the calculations, leave two places after the decimal point and do not round: Use the regression equation you found in question 6 to find the predicted memory scores for the following age: 50 For the calculations, leave two places after the decimal point and do not round:
Find Karl person's coefficient of correlation using regression coefficient byr=-0.56, bry=-0.83 Answer:

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