MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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- The line of best fit through a set of data is y = – 27.749 + 1.474x According to this equation, what is the predicted value of the dependent variable when the independent variable has value 30? y = Round to 1 decimal place.arrow_forwardThe following estimated regression equation is based on 10 observations was presented. ŷ = 29.1270 + 0.5906x1 + 0.4980x2 Here SST = 6,871.500, SSR = 6,526.625 , si, = 0.0762, and Si, = 0.0612. a. Compute MSR and MSE (to 3 decimals). MSR MSE = b. Compute F and perform the appropriate F test (to 2 decimals). Use a = 0.05. Use the F table. F The p-value is between 0.025 and 0.05 At a = 0.05, the overall model is not significant c. Perform at test for the significance of B1 (to 2 decimals). Use a = 0.05. Use the t table. The p-value is between 0.02 and 0.05 v At a = 0.05, there is not a significant relationship between y and 01. d. Perform a t test for the significance of B2 (to 2 decimals). Use a = 0.05. Use the t table. The p-value is between 0.01 and 0.02 v At a = 0.05, there is not a significant v relationship between y and x2.arrow_forwardConsider a linear regression model for the decrease in blood pressure (mmHg) over a four-week period with muy=2.8+0.8x and standard deviation chi=3.2. The explanatory variable x is the number of servings fruits and vegetables in a calorie-controlled diet. What is the subpopulation mean when x = 7 servings per day?arrow_forward
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- The table below lists measured amounts of redshift and the distances (billions of light-years) to randomly selected astronomical objects. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. For the prediction interval, use a 90% confidence level with a redshift of 0.0126. Find the explained variation. Redshift Distance OA, 0.157904 OB. 0.444904 OC. 0.000582 OD. 0.219582 0.0231 0.34 0.0536 0.76 0.0715 0.99 0.0391 0.56 0.0438 0.63 0.0109 0.15arrow_forwardA regression was run to determine if there is a relationship between hours of study per week (x) and the final exam scores (y).The results of the regression were: y=ax+b a=5.088 b=26.56 r2=0.913936 r=0.956 Use this to predict the final exam score of a student who studies 4.5 hours per week, and please round your answer to a whole number.arrow_forwardIt is known that the linear regression equation: y= -2.88+1.77x, with a coefficient of determination of 0.81. Based on the two information, the correlation coefficient isarrow_forward
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