The following table contains data from a sample of ten students regarding the numbers of parkingtickets they received during one semester and their monthly incomes (including allowances fromparents as well as paychecks from employment as income).Construct a 95 % confidence interval for the y-intercept of the regression line. Round your answersto two decimal places, if necessary.Parking Tickets and Monthly IncomeMonthly Income (inNumber of Tickets, xDollars). y1000525001700130073100419006.2100103400260042100Copy DataAnswerTablesКeypadKeyboard ShortcutsLower endpoint:2.3.

Answered: The following table contains data from…

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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ANSWER D ONLY
Q9 The explanatory variable in linear correlation/regression model is recorded on which of thesemeasurement scales: A. categorical B. ordinal C. quantitative D. none of the above
You generate a scatter plot using Excel. You then have Excel plot the trend line and report the equation and the r2r2 value. The regression equation is reported asy=60.71x+33.51y=60.71x+33.51and the r2=0.1764r2=0.1764.What is the correlation coefficient for this data set?r =
What is the relationship between the number of minutes per day a woman spends talking on the phone and the woman's weight? The time on the phone and weight for 8 women are shown in the table below. Time 46 60 43 39 18 20 35 18 Pounds 138 142 135 116 119 98 125 112 r2r2 = (Round to two decimal places) Interpret r2r2 : There is a 71% chance that the regression line will be a good predictor for women's weight based on their time spent on the phone. Given any group of women who all weight the same amount, 71% of all of these women will weigh the predicted amount. There is a large variation in women's weight, but if you only look at women with a fixed weight, this variation on average is reduced by 71%. 71% of all women will have the average weight. The equation of the linear regression line is: ˆyy^ = + xx (Please show your answers to two decimal places)
Bluereef real estate agent wants to form a relationship between the prices of houses, how many bedrooms, House size in sq ft and Lot Size in sq ft. The data pertaining to 100 houses were processed using MINITAB and the following is an extract of the output obtained:The regression equation is ????? = ? + ???????? + ?????? ???? + ???? ????Predictor Coef SE Coef T PConstant 37718 14177 2.66 **Bedrooms 2306 6994 0.33 0.742House Size 74.3 52.98 * 0.164Lot Size -4.36 17.02 -0.26 0.798S= 25023 R-Sq=56.0% R-Sq(adj)=54.6%Source DF SS MS F PRegression 3 76501718347 25500572782 *** ****Residual Error 96 60109046053 626135896Total 99a) Write out the regression equation. b) Fill in the missing values *, **, *** and ****. c) Use the p-value approach to determine if ? is significant at the 5% significance leveld) Is ? significantly different from -0.5? e) Perform the F test at the 1% level, making sure to state the null and alternative hypotheses. f) Give an interpretation to the term “R-sq” and…
The data show the number of viewers for television stars with certain salaries. Find the regression equation, letting salary be the independent (x) variable. Find the best predicted number of viewers for a television star with a salary of $6 million. Is the result close to the actual number of viewers, 8.9 million? Use a significance level of 0.05. Salary (millions of $) Viewers (millions) Click the icon to view the critical values of the Pearson correlation coefficient r. 98 3.5 3 7 13 12 13 10 2 6.8 6.3 10.2 8.5 4.4 1.8 2.7 What is the regression equation? y=+x (Round to three decimal places as needed.) What is the best predicted number of viewers for a television star with a salary of $6 million? The best predicted number of viewers for a television star with a salary of $6 million is million. (Round to one decimal place as needed.) Is the result close to the actual number of viewers, 8.9 million? O A. The result is very close to the actual number of viewers of 8.9 million. O B. The…
5
Please help me! I have no idea where to even start. Conclude that the mean height is not equal to 64 inches because the P-value is less than 0.05. a. Find the correlation coefficient between the height and the weight. b. Construct the equation of the regression line. c. Predict the weight of a student who is 68 inches tall.
Write your complete solutions. The final test and exam averages for 20 randomly selected students taking a course in engineering statistics and a course in operations research are in the table below. Assume that the final averages are jointly normally distributed. (a) Find the regression line relating the statistics final average to the OR final average. Graph the data. (b) Test for significance of regression using a = 0.05. (c) Estimate the correlation coefficient. (d) Test the hypothesis that p = 0, using a = 0.05. (e) Test the hypothesis that p = 0.5, using a = 0.05. equations on this slide to answer the question) (f) Construct a 95% confidence interval for the correlation coefficient. Statistics OR Statistics OR Statistics OR 86 80 86 81 83 81 75 81 71 76 75 69 75 65 72 71 75 81 84 85 90 92 71 72 94 95 62 65 83 80 90 93 76 84 97 70 73 72 80 98
Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $105 million. Use a significance level of a = 0.05. Budget ($)in Millions Gross ($) in Millions 41 23 114 75 78 47 120 64 10 59 127 22 12 150 2 0 127 18 111 65 113 112 102 94 64 98 211 41 22 288 57 Click the icon to view the critical values of the Pearson correlation coefficient r. ..... x. (Round to one decimal place as needed.) The regression equation is = + The best predicted gross for a movie with a $105 million budget is $ million. (Round to one decimal place as needed.)

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