Suppose the simple linear regression model, Y; = Bo + B1 a; + Ej, is used to explain the relationship between x and y.A random sample of n10 values for the explanatory variable (x) was selected and the corresponding values of theresponse variable (y) were observed. The summary statistics were:Σ.8, Συ- 10 , Σα,y 9.5,Σ-7.4, Σ-20 5. What is the value of the coefficient of determination, R2 ?0.745O 0.563O 0.2560.225

Answered: Image /qna-images/answer/3e47ef67-0565-4c22-86c4-6ed3cd815f05.jpg

Answered: Suppose the simple linear regression…

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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Here are the scatter plots for two sets of bivariate data with the same response variable. The first compares the variables x & y. The second compares the variables w & y 00⁰0 889 Which explanatory variable has a stronger relationship with the response variable y? The first variable (x) has a stronger relationship with the response variable y. The second variable (w) has a stronger relationship with the response variable y.
o pis pe Suppose a doctor measures the height, x, and head circumference, y. of 11 children and obtains the data below. The correlation coefficient is 0.899 and the least squares regression line is y = 0.185x+ 12.276. Complete parts (a) and (b) below. Height, x Head Circumference, y 17.4 17.1 17.2 16.9 17.4 17.1 17.1 17.3 17.3 17.3 17.4 27.75 25.75 26.75 25.75 28 26.5 25.75 26.75 27 27.25 27.25 (a) Compute the coefficient of determination, R?. R2 = % (Round to one decimal place as needed) (b) Interpret the coefficient of determination k Approximately % of the variation in (Round to one decimal place as needed.) is explained by the least-squares regression model. Enter your answer in each of the answer boxes. Save for Later DUE RTTT:DY PIVT Score: o:5SYO Tor Tv attempts 3:35 PA- a 2/22/202 Type here to search insert prt sc 4+ backsp %23 6. 8.
The weights (in pounds) of 6 vehicles and the variability of their braking distances (in feet) when stopping on a dry surface are shown in the table. Can you conclude that there is a significant linear correlation between vehicle weight and variability in braking distance on a dry surface? Use α=0.01. Weight, x 5920 5370 6500 5100 5890 4800 Variability in 1.76 1.91 1.50 braking distance, y EEE Click here to view a table of critical values for Student's t-distribution. Setup the hypothesis for the test. Ho: P Ha: P 0 0 1.86 1.62 1.67 M
The given quantities below were calculated from a sample data set. Στο 338 I Lu=308 Ση2 = 4678 2 y = 4236 Determine the least squares regression line. Round values to four decimal places, if necessary. Σry = 3595 n = 30 Determine the correlation coefficient. Round the solution to four decimal places, if necessary.
The following output is from a multiple regression analysis that was run on the variables FEARDTH (fear of death) IMPORTRE (importance of religion), AVOIDDTH (avoidance of death), LAS (meaning in life), and MATRLSM (materialistic attitudes). In the regression analysis, FEARDTH is the criterion variable (Y) and IMPORTRE,AVOIDDTH, LAS, and MATRLSM are the predictors (Xs). The SPSS output is provided below, followed by a number of questions. Descriptive Statistics Mean Std. Deviation N feardth 27.0798 8.08365 163 importre 5.8282 2.46104 163 avoiddth 18.5460 6.97633 163 Las 70.1288 9.89460 163 matrlsm 53.5552 10.21860 163 Model Variables Entered Variables Removed Method 1 matrlsm, avoiddth, importre, lasa . Enter a. All requested variables entered. b. Dependent Variable: feardth Model Summary Model R R Square Adjusted R Square…
A sample of 548 ethnically diverse students from Massachusetts were followed over a 19-month period from 1995 and 1997 in a study of the relationship between TV viewing and eating habits. For each additional hour of television viewed per day, the number of fruit and vegetable servings per day was found to decrease on average by 0.14 serving. (a) For this study, what is the dependent variable? O location of students O number of fruit and vegetable servings per day O number of non fruit or vegetable servings per day O number of hours of television viewed per day year What is the independent variable? O location of students O number of fruit and vegetable servings per day O number of non fruit or vegetable servings per day O number of hours of television viewed per day O year (b) Would the least-squares line for predicting number of servings of fruits and vegetables using number of hours spent watching TV as a predictor have a positive or negative slope? Explain. O The slope of the least…
Suppose a doctor measures the height, x, and head circumference, y, of 8 children and obtains the data below. The correlation coefficient is 0.858 and the least squares regression line is y = 0.228x +11.187. Complete parts (a) and (b) below. Height, x 27.5 25.75 26.5 25.5 27.25 26.25 25.75 27.25 27 27.25 27 Head Circumference, y 17.4 17.2 17.2 16.9 17.6 17.1 17.1 17.4 17.4 17.3 17.3 (a) Compute the coefficient of determination, R². R² =% (Round to one decimal place as needed.) (b) Interpret the coefficient of determination and comment on the adequacy of the linear model. Approximately % of the variation in (Round to one decimal place as needed.) is explained by the least-squares regression model. According to the residual plot, the linear model appears to be
2. A researcher had rats engage in a lever-press task for either a small, medium, or larger reward. The number of lever presses was the dependent variable. The data were as follows: Reward Size Small Medium Large 1 4 6 4 3 5 1 4 4 2 5 T = 13 SS = 2.75 T= 6 T= 20 SS = 9 SS = 2 EX2 = 165 a. Do the data indicate that reward size had a significant impact on lever-pressing? Use the hypothesis testing steps & p = .05. Compute any necessary post-hoc tests. b. Compute eta-squared to measure the effect size.
Here are the scatter plots for two sets of bivariate data with the same response variable. The first compares the variables x & y. The second compares the variables w & y 098 Which explanatory variable has a stronger relationship with the response variable y? O The first variable (x) has a stronger relationship with the response variable y. O The second variable (w) has a stronger relationship with the response variable y.

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