3.2. Consider a fictitious dataset of nTotalErrorCalculate the (unadjusted) coefficient of determination, R².C.Consider a fictitious dataset of n =100 observations with sy = 80. We runa regression with three explanatory variables to get s = 50. We also get%3D100 20 20 202090 30 40(X'X)"2030 80 502040 50 70a. Determine the standard error of b3, se(bz).b. Determine the estimated covariance between b2 and bz.c. Determine the estimated correlation between b2 and b3.d. Determine the estimated variance of 4b2 + 3b3.

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Answered: coefficient of determination, R?. 100…

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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I have asked this question twice and both times it has been wrong. Answer given F=.82 and .77 both these are incorrect. A bakery is considering buying one of two gas ovens. The bakery requires that the temperature remain constant during a baking operation. A study was conducted to measure the variance in temperature of the ovens during the baking process. The variance in temperature before the thermostat restarted the flame for the Monarch oven was 3.3 for 22 measurements. The variance for the Kraft oven was 4 for 25 measurements. Does this information provide sufficient reason to conclude that there is a difference in the variances for the two ovens? Assume measurements are normally distributed and use a 0.02 level of significance.
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
c) Show that the coefficient of determination, R², can also be obtained as the squared correlation between actual Y values and the Y values estimated from the regression model where Y is the dependent variable. Note that the coefficient of correlation between Y and X is Eyixi r = And also that ỹ = ŷ (18.75)
The calculation of the coefficient of determination r depends on the number of independent variables. An adjusted value of based on the number of degrees of freedom is calculated using the formula shown below, where n is the number of data pairs and k is the number of independent variables. =1-(1-7)(n-1)] adj n-k-1 Data were found on eight pre-owned sedans of a certain make. Suppose a multiple regression on these data has 6 independent variables. The coefficient of determination is found to be 0.972 based on a sample of 24 paired observations. After calculating rdi, determine the percentage of the variation in y that can be Compare this result with the one obtained using . adj explained by the relationships between variables according to r th %3D 12 adj (Round to three decimal places as needed.) % of the variation in y can be explained by the relationships between variables. About on (Round to one decimal place as needed.) The value of radi the value of 2. is adj uest Que Quest Enter…
5. Explain what the correlation coefficient tells you about the relationship between your variables. 7. Interpret the slope of the regression equation in terms of the variables in your data set.
The regression line for Y vs X is given by Y = 0.82X + 59.1. The standard deviations for X and Y are 1.5 and 2.2 respectively. Suppose now we construct a regression line that uses Y to predict X. The predicted average increase of X when Y is increased by 1 unit is ______________. (Give your answer correct to 2 decimal places.)
The correlation between two variables x and y is –0.6. If we used a regression line to predict y using x, what percent of the variation in y would be explained?
Prev The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, y = bo + b₁x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, In practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age Bone Density 61 62 68 69 40 357 350 343 340 315 Step 1 of 6: Find the estimated slope. Round your answer to three decimal places. Table Copy Data Next

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