« 10. For 50 students of a class the regression equation of marks in Statistics(X) ön the marks in Accountancy (Y) is 3 Y-5 X+180 = 0. The mean marks in Account-ancy is 44 and variance of marks in Statistics is 9/16th of the variance of marks in Ac-countancy. Find the mean marks in Statistics and the coefficient of correlation betweenmarks in the two subjects.3X 10 8S

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Answered: 10. For 50 students of a class 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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IQ scores were obtained randomly from selected twins at birth. For 20 such twins the linear correlation coefficient was 0.896 and equation of regression line is y= -3.02 + 1x, where x represents the iq score of the twin that was first born. Also the 20 x values has a mean of 103.2 and the 20 y values has a mean of 105.2. What is the best predicted IQ of the twin born second, given the first born twin has an IQ of 105?
Suppose IQ scores were obtained from randomly selected twins. For 20 such pairs of people, the linear correlation coefficient is 0.930 and the equation of the regression line is y=−10.69+1.11x, where x represents the IQ score of the twin born first. Also, the 20 x values have a mean of 98.28 and the 20 y values have a mean of 98.5. What is the best predicted IQ of the twin born second, given that the twin born first has an IQ of 92? Use a significance level of 0.05.LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r.Question content area bottomPart 1The best predicted IQ of the twin born second is enter your response here.(Round to two decimal places as needed.)
Suppose IQ scores were obtained from randomly selected twins. For 20 such pairs of people, the linear correlation coefficient is 0.892 and the equation of the regression line is Modifying Above y= -1.91 + 1.01 x, where x represents the IQ score of the twin born the second. Also, the 20 x values have a mean of 100.07 and the 20 y values have a mean of 98.8 What is the best predicted IQ of the twin born first twin born first,given that the twin born second twin born secondhas an IQ of 96?Use a significance level of 0.05. Click the icon to view the critical values of the Pearson correlation coefficient r. Critical Values of the Pearson Correlation Coefficient r NOTE: To test H0: rhoρequals=0 against H1: rhoρnot equals≠0, reject H0 if the absolute value of r is greater than the critical value in the table. n a=0.05 a=0.01 4 0.950 0.990 5 0.878 0.959 6 0.811 0.917 7 0.754 0.875 8 0.707 0.834 9 0.666 0.798 10…
One difference between ANOVA and regression is: a) ANOVA is for statistical inference, whereas regression is not b) a regression line accounts for variability, whereas variability is not a concept in ANOVA c) in regression, we estimate a slope, whereas in ANOVA, we estimate mean differences d) ANOVA bases its inferences on samples, whereas regression bases its inferences on populations e) ANOVA and regression are not different at all, they are exactly the same f) ANOVA features p-values, whereas regression does not
Suppose IQ scores were obtained from randomly selected twins. For 20 such pairs of people, the linear correlation coefficient is r = 0.914 and the equation of the regression line is y = 9.87+0.9x, where x represents the IQ score of the twin born first and y represents the IQ score of the twin born second. What is the bestpredicted IQ of the twin born second, given that the twin born first has an IQ of 107?What does the r value tell you about the relationship between the IQ scores of twins?What is the Value for r squared? What does the r squared statiscic mean in this scenario?
One difference between ANOVA and regression is: a) ANOVA is for statistical inference, whereas regression is not b) a regression line accounts for variability, whereas variability is not a concept in ANOVA c) in regression, we estimate a slope, whereas in ANOVA, we estimate mean differences d) ANOVA bases its inferences on samples, whereas regression bases its inferences on populations e) ANOVA and regression are not different atall,they are exactly the same f) ANOVA features p-values, whereas regression does not
True or False 1) The correlation coefficient of 0.6 has a stronger association than a correlation coefficient of -0.8 2) The slope is the y value when x equals intercept. 3) The standard error describes the differences b
The least-squares regression equation is y=728.0x+14,705 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.8165. For every dollar increase in median income, the percent of adults having at least a bachelor's degree is ___%, on average. For a median income of $0, the percent of adults with a bachelor's degree is ____%.
IQ scores were obtained from randomly selected adopted children living together. For 20 such pairs of children, the linear correlation coefficient is 0.027 and the equation of the regression line is y=-3.22+1.02x, where x represents the IQ score of the older child. Also, the 20 x values have a mean of 104.2 and the 20 y values have a mean of 103.1. What is the best predicted IQ of a younger adopted child, given that the older adopted child in the same family has an IQ of 110
If you have a b of 0.56 in a regression equation, what does this mean? For every one-unit increase in x, you get an increase of 0.56 in y r = .31 On average, the variability of real scores around the regression line is 0.56 For every 1 standard deviation increase in x, you get an increase of 0.56 standard deviations in y
You conducted a regression analysis between the number of absences and number of tasks missed by your 5 classmates in Statistics and Probability. It resulted that the regression line is y = 0.65x + 1.18. What is the predicted number of tasks missed of a learner who is always present? a. The learner has 1 task missed. b. The learner has less than 2 tasks missed. c. The learner has more than 2 tasks missed. d. The learner has no task missed.
-Suppose that there are two independent variables, and to explain . -Write down the population regression line. -Consider changing X2 while holding X1 constant. Write down the population regression line after the change. -What is the partial effect of X2 on Y?

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