Two variables have a positive linear correlation. Is the slope of the regression line for the variables positiveor negative?OA. The slope is negative. As the independent variable increases the dependent variable tends to decrease.OB. The slope is negative. As the independent variable increases the dependent variable also tends to increase.OC. The slope is positive. As the independent variable increases the dependent variable also tends to increase.OD. The slope is positive. As the independent variable increases the dependent variable tends to decrease20

Correlation is positive (Given)

Answered: Two variables have a positive linear…

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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10:56 AA www-awn.aleks.com O REGRESSION AND CORRELATION Predictions from the least-squares regressio. OC OO D The managers of an electric utility wish to examine the relationship between temperature and electricity use in the utility's service region during the summer months. In particular, the managers wish to be able to predict total electricity use for a day from the maximum temperature that day. The bivariate data below give the maximum temperature (in degrees Fahrenheit) and the electricity use (in thousands of kilowatt hours) of electricity generated and sold for a random sample of sixteen summer days. A best-fitting line for the data, obtained from least- squares regression, is given by =53.28 + 3.07.x, in which x denotes the maximum temperature and y denotes the electricity use. This line is shown in the Figure 1 scatter plot. Temperature, x Electricity use, y (in degrees Fahrenheit) (in thousands of kilowatt hours) 78.4 295.4 72.5 232.1 00- 72.7 276.8 94.5 363.4 375 94.8 335.6…
Do you observe a linear relationship between the two variables?
Q5. Find the equation of Regression line for the given data. X: 15 3 4 7 Y: 5 6 10 20 2 Find the value of Y when X = 6.
You intend to estimate a population mean u with the following sample 26.9 34.2 20.2 29.7 69 You believe they population is normally distributed. Find 90% confidence interval. Enter your answer as an open interval(I.e.,parentheses) accurate two top decimals places(because the sample data are reported accurate to one decimal place). 90% C.I =__________Answer should be obtained without any preliminary rounding. However, the critical value may be rounded to 3 decimal places
Use the given data to find the equation of the regression line. Examine the scatterplot and identify a characteristic of the data that is ignored by the regression line. x 9 9 13 10 10 13 5 4 12 7 6 y 7.09 6.48 12.69 7.16 7.46 9.16 6.36 5.12 8.19 6.44 5.55 Create a scatterplot of the data. Choose the correct graph below. A. 05101520250510152025xy A scatterplot has a horizontal x-scale from 0 to 25 in intervals of 1 and a vertical y-scale from 0 to 25 in intervals of 1. Eleven points are plotted with approximate coordinates as follows: (9, 8); (9, 7); (13, 6); (10, 7); (10, 5); (13, 7); (5, 7); (4, 13); (12, 7); (7, 8); (6, 9). B. 05101520250510152025xy A scatterplot has a horizontal x-scale from 0 to 25 in intervals of 1 and a vertical y-scale from 0 to 25 in intervals of 1. Eleven points are plotted with approximate coordinates as follows: (7,…
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 1 2 2 4 5 5 Test score, y 39 45 50 49 63 73 (a) x=2hours (b) x=2.5hours (c) x=14hours (d) x=3.5hours Find the regression equation. y=______ x+__________ (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.)
Use the given data to find the equation of the regression line. Examine the scatterplot and identify a characteristic of the data that is ignored by the regression line. A. Find the equation of the regression line. y=+ x (Round the y-intercept two decimal places as needed. Round the slope to three decimal places as needed.)
Describe the unexplained variation about a regression line in words and in symbols. y X (xi, Yj) • (,,)) (x, y) y = y Choose the correct answer below. O A. The unexplained variation is the sum of the squares of the differences between the y-values of each ordered pair and the mean of the y-values of the ordered pairs. B. The unexplained variation is the sum of the squares of the differences between the observed y-values and the predicted y-values. OC. The unexplained variation is the sum of the squares of the differences between the predicted y-values and the mean of the y-values of the ordered pairs.
The correlation for the data is r=1 and a=0.05 should regression analysis be done Find the equation of the regression line y = a+bx A= B= Find y when x=40
The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 40inches. Is the result close to the actual weight of 352pounds? Use a significance level of 0.05.a. Chest size (inches) 41 54 44 55 39 51 Weight (pounds) 328 528 418 580 296 503 a.What is the regression equation? b. The best predicted weight for a bear with a chest size of 39 inches is _______pounds.
Describe the explained variation about a regression line in words and in symbols. y x (xi, Yj). (,))) (x₁, y) y = y D Choose the correct answer below. O A. The explained variation is the sum of the squares of the differences between the predicted y-values and the mean of the y-values of the ordered pairs. B. The explained variation is the sum of the squares of the differences between the y-values of each ordered pair and the mean of the y-values of the ordered pairs. C. The explained variation is the sum of the squares of the differences between the observed y-values and the predicted y-values.
The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 58 inches. Is the result close to the actual weight of 572 pounds? Use a significance level of 0.05. Chest size (inches) 46 57 53 41 40 40 Weight (pounds) 384 580 542 358 306 320 LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y=nothing+nothingx (Round to one decimal place as needed.)

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