2. Treating the twelve months last year as a random sample of all months, and assuming that the other conditions for inference are met, at what level of significance do last year's results provide evidence of a non-zero slope in the population regression line of y on x? (A) At the 0.01 level (B) At the 0.05 level, but not at the 0.01 level (C) At the 0.1 level, but not at the 0.05 level (D) At the 0.05 level, but not at the 0.1 level (E) Not at any reasonable significance level

2. Treating the twelve months last year as a random sample of all months, and assuming that the other conditions for inference are met, at what level of significance do last year's results provide evidence of a non-zero slope in the population regression line of y on x? (A) At the 0.01 level (B) At the 0.05 level, but not at the 0.01 level (C) At the 0.1 level, but not at the 0.05 level (D) At the 0.05 level, but not at the 0.1 level (E) Not at any reasonable significance level

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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Ten observations were provided for a dependent variable y and two independent variables x1 and x2; for these data, SST = 15,177.6 and SSR = 14,056.5. (a) Compute R2. (Round your answer to three decimal places.) R2 = (b)Compute Ra2.( Round your answer to three decimal places.) Ra2 = (c)Does the estimated regression equation explain a large amount of the variability in the data? Explain. (For purposes of this exercise, consider an amount large if it is at least 55%. Round your answer to one decimal place.) (Select Yes OR No) after adjusting for the number of independent variables in the model, we see that ______% of the variability in y has been accounted for.
Month No. of Advertisements Amt of sales 1 20 61000 2 24 77000 3 30 72000 4 23 66000 5 27 85000 6 25 77000 7 32 90000 8 35 10000 9 21 63000 10 34 97000 11 26 83000 12 29 70000 a) show above data on a scatter plot and include regression line. b) calculate the regression equation and a r-squared c) construct a 95% confidence interval for question b.
11:12 AA www-awn.aleks.com O REGRESSION AND CORRELA Computing the sample. OD O DO An advertising firm wishes to demonstrate to its clients the effectiveness of the advertising campaigns it has conducted. The following bivariate data on twelve recent campaigns, including the cost of each campaign (denoted by x, in millions of dollars) and the resulting percentage increase in sales (denoted by y) following the campaign, were presented by the firm. A scatter plot of the data is shown in Figure 1. Also given are the products of the values for campaign cost and values for percentage increase in sales for each of the twelve campaigns. (These products, written in the column labelled "xy," may aid in calculations.) Campaign cost, Increase in sales, y (percent) xy (in milions o dollars) 3.71 6.73 24.9683 72 3.84 7.03 26.9952 2.18 6.40 13.952 3.06 6.94 21.2364 3.27 6.55 21.4185 1.50 6.28 9.42 2.25 6.57 14.7825 2.00 6.77 13.54 1.47 6.63 9.7461 3.58 6.91 24.7378 1.31 6.41 8.3971 Figure 1 3.01 6.59…
1. A study compared the number of tree species in unlogged forest plots to similar plots logged 8 years earlier. Independent random samples of both logged and unlogged plots were analyzed and the number of tree species was recorded. Tables 1 and 2 present the Shapiro-Wilk normality test for both types of forest plots and the Independent Samples t-test results. Use the information presented in these tables to answer the questions. Table 1: Tests of Normality Tests of Normality Kolmogorov-Smirnov Shapiro-Wilk Forest Plot Statistic df Sig. Statistic df Sig. Tree_Species Logged .181 12 .200 .936 12 .444 Unlogged .110 14 .200 .945 14 .480 *. This is a lower bound of the true significance. a. Lilliefors Significance Correction Table 2: Independent Samples Test Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means 95% Confidence Interval of the Difference Mean Std. Error F Sig. t df Sig. (2-tailed) Difference Difference Lower Upper Equal variances…
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Part A of question one asks for the variance (sigma squared), not the equation of regression line. Is the variance 2.79 as I listed on my answer sheet? Maybe my image didn't go through, but I already had the answer to subparts B and C to the question, which you list as #2 and #3. But I need help with parts D, E, and F. I have the following answers for D. d. Y hat (fitted value = 426.46), with residual of -1.62. e. r squared value = 1.00 g. 99% confidence interval = (-11.63, -1.05) Thanks thanks
In a certain type of metal test specimen, the normal stress on a specimen is known to be functionally related to the shear resistance. The following is a set of coded experimental data on the two variables: Normal Stress, x Shear Resistance, y 16 5 6. 12 8 9 4 15 7 7 (a) estimate the regression line (b) estimate the shear resistance for a normal stress of 10 (c) evaluate the unbiased estimate of the variance (d) a 95% confidence interval for the mean shear resistance when x = 10; (e) a 95% prediction interval for a single predicted value of the shear resistance when x = 10. WORK THIS ENTIRE PROBLEM WITH ALL 5 PARTS ,BEFORE PROCEEDING TO THE NEXT PROBLEM WRITE EVERYTHING DOWN ON YOUR ANSWER SHEETS. As.you proceed to the other problems, you will encounter this entire problem 4 more times. Each time you will be given a chance to answer a problem part. This time select your answer to part c)
The following data represent the speed at which a ball was hit (in miles per hour) and the distance it traveled (in feet) for a random sample of home runs in a Major League baseball game in 2018. Complete parts (a) through (f). Click here to view the data. Click here to view the critical values of the correlation coefficient. (a) Find the least-squares regression line treating speed at which the ball was hit as the explanatory variable and distance the ball traveled as the response variable. y = 5x+ (5 (Round to three decimal places as needed.) (b) Interpret the slope and y-intercept, if appropriate. Begin by interpreting the slope. A. The slope of this least-squares regression line says that the distance the ball travels increases by the slope with every 1 mile per hour increase in the speed that the ball was hit. O B. The slope of this least-squares regression line shows the increase in the speed that the ball was hit with every 1 foot increase in the distance that the ball was hit.…
1. A study compared the number of tree species in unlogged forest plots to similar plots logged 8 years earlier. Independent random samples of both logged and unlogged plots were analyzed and the number of tree species was recorded. Tables 1 and 2 present the Shapiro-Wilk normality test for both types of forest plots and the Independent Samples t-test results. Use the information presented in these tables to answer the questions. Table 1: Tests of Normality Tests of Normality Kolmogorov-Smirnov Shapiro-Wilk Forest Plot Statistic df Sig. Statistic df Sig. Tree_Species Logged .181 12 .200 .936 12 .444 Unlogged .110 14 .200 .945 14 .480 *. This is a lower bound of the true significance. a. Lilliefors Significance Correction Table 2: Independent Samples Test Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means 95% Confidence Interval of the Difference Mean Std. Error F Sig. t df Sig. (2-tailed) Difference Difference Lower Upper Equal variances…