4. The residual for the first observation in the table is5. The average value of the residuals isY3148.3217

Answered: Image /qna-images/answer/14b2a1ae-e8e1-4103-ae22-3c89554efc2c.jpg

Answered: 4. The residual for the first…

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 correlation between X and Y is r = 0.35. If we doublw each X value, decrease each Y by 0.20, and interchange the variables (put X on the Y-axis and vice versa), the new correlation is?
Can you explain how I can find the variance for the data using the formula provided? I don’t understand what the numbers for E and X are.
Use the value of the linear correlation coefficient to calculate the coefficient of determination. What does this tell you about the explained variation of the data about the regression line? About the unexplained variation? r = -0.338 Calculate the coefficient of determination. (Round to three decimal places as needed.) % of the variation can be explained by the regression line (Round to one decimal place as needed.) % of the variation is unexplained and is due to other factors or to sampling error. (Round to one decimal place as needed.)
Variable A and Variable B are very highly correlated at r = -.89. Joe’s z-score on Variable A is -1.5. Which of the following would be the best guess for his z score on Variable B? a. 0 b. -1.335 c. 1.5 d. -1.5 e. -0.90
Suppose u1 and uz are true mean stopping distances at 50 mph for cars of a certain type equipped with two different types of braking systems. The data follows: m = 6, x = 115.6, s1 = 5.03, n = 6, y = 129.9, and s2 = 5.38. Calculate a 95% CI for the difference between true average stopping distances for cars equipped with system 1 and cars equipped with system 2. (Round your answers to two decimal places.) In USE SALT Does the interval suggest that precise information about the value of this difference is available? Because the interval is so narrow, it appears that precise information is available. Because the interval is so narrow, it appears that precise information is not available. o Because the interval is so wide, it appears that precise information is not available. o Because the interval is so wide, it appears that precise information is available.
Which of the following is not one of the uses of a scatter plot and regression line a. to estimate the average y at a specific value of x. b. All three are uses of the scatterplot and regression line c. to determine if a change in x causes a change in y d. to predict y at a specific value of x.
The table below gives the age and bone density for 5 women. Use the equation of the regression line, y= b0 + b1x, for predicting a women's bone density based on her age. The correlation coefficient may or may not be statically significant for the data given. Remember it wouldn't be appropiate to use regression line to make a prediction if the correlation coefficient isn;t statically significant. (y has a "hat" on the top) age 39 51 54 56 67 bone density 355 349 347 315 313 Find the estimated slope. Rund your answer to three decimal places. Find the estimated y-intercept. Round your answer to three decimal places. Determine the value of the dependent variable y at x+ 0 (y has a "hat" onthe top) Find the estimated value of y when x = 51. Round your answer to three decimal places. Substitute the values you found in steps 1 and 2 into the equation for the regression line to find the estimated linear model. According to this model, if the valueof the…
Here is a scatterplot. Give an estimate for the correlation coefficient r and explain how you made your choice.
COMPUTE BY HAND NOT EXCEL, GOOGLE SHEETS etc 5. Write a brief paragraph about whether the in-home counseling is equally effective as the out of home treatment for two separate groups. Here are the data. The out come variable is level of anxiety after treatment on a scale from 1-10 Total In-home treatment X Out of home treatment Y X2 Y2 XY 1 3 7 9 49 21 2 4 6 16 36 24 3 1 7 1 49 7 4 1 8 1 64 8 5 1 7 1 49 7 6 3 6 9 36 18 7 3 5 9 25 15 8 6 6 36 36 36 9 5 4 25 16 20 10 1 2 1 4 2 11 4 5 16 25 20 12 5 4 25 16…
21. Which of the following statements is true regarding the sources of variation present in an analysis of regression? SSy is partitioned into variation explained by the regression model and residual variation. If most of the variability in Y is associated with residual variation, then X predicts Y. There are three sources of variation in an analysis of regression: regression variance, residual variance, and error variance. Regression variation measures variability in X, whereas residual variation measures variability in Y.
A negative correlation means that decreases in the X variable tend to be accompanied by decreases in the Y variable. T or F
Suppose ₁ and ₂ are true mean stopping distances at 50 mph for cars of a certain type equipped with two different types of braking systems. The data follows: m = 9, x = 113.3, s₁=5.01, n = 9, y = 129.6, and s₂ = 5.34. Calculate a 95% CI for the difference between true average stopping distances for cars equipped with system 1 and cars equipped with system 2. (Round your answers to two decimal places.) USE SALT -21.57 1x ) Does the interval suggest that precise information about the value of this difference is available? Because the interval is so narrow, it appears that precise information is available. Because the interval is so narrow, it appears that precise information is not available. Because the interval is so wide, it appears that precise information is available. Because the interval is so wide, it appears that precise information is not available. x -11.06

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4. The residual for the first observation in the table is 5. The average value of the residuals is Y X 3 1 5 4 8 3 1 7