The correlation between a family's weekly income and the amount they spend on restaurant meals is found to ber = 0.30. Which must be true? . I. The equation used to describe the correlation between income and money spent on restaurant meals only explains about 9% of the variation in the data. . II. In general, the lower the income, the more the family spends in restaurants. . III. The line of best fit passes through 30% of the (income, restaurant$) data point O I. Only O I, II, and II II. Only O I. and II. Only O III. Only

The correlation between a family's weekly income and the amount they spend on restaurant meals is found to ber = 0.30. Which must be true? . I. The equation used to describe the correlation between income and money spent on restaurant meals only explains about 9% of the variation in the data. . II. In general, the lower the income, the more the family spends in restaurants. . III. The line of best fit passes through 30% of the (income, restaurant$) data point O I. Only O I, II, and II II. Only O I. and II. Only O III. Only

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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Test for a significance of the positive slope. Use =0.05. State your decision and conclusion. a. Fail to reject Ho. No evidence for a positive slope. b. Fail to reject Ho. There is evidence for a positive slope. c. Reject Ho. No evidence for a positive slope. d. Reject Ho. There is evidence for a positive slope.
A researcher that there is a linear association between the level of potassium content (y) in milligrams and the amount of fiber (x) in grams in cereal. The regression line for the data is computed to y=37+28x rate. It was also computed that r=.59 A. What does the value . 59 tell you? B. What does the value 37 tell you? C. What does the value 28 tell you ? 2. For the line in question 1 what percentage of variability in potassium can be explained by variability in fiber?
The arm span and foot length were both measured (in centimeters) for each of 20 students in a biology class. The computer output displays the regression analysis. Which of the following is the best interpretation of the coefficient of determination r2? About 37% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 65% of the variation in foot length is accounted for by the linear relationship formed with the arm span. About 63% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 63% of the variation in foot length is accounted for by the linear relationship formed with the arm span.
Below is the actual data on the speed a person walks or runs in miles/hour and the calories the person burns per lap. Find the linear equation of best fit for this data. Compare the model to the data. Does the model seem to fit the data? Explain. What is the significance of the y-intercept? What is the slope and what does it mean? What is the x-intercept and what does it mean? What is the correlation coefficient and what does it mean? Speed (mph) Calories/lap 1 42 2 31 3 27 4 41 5 40 6 40 7 39 8 38 r answers to the nearest hundredth. The y-intercept means that if a person runs at ----------mph they will burn__________ per lap. The slope means that for each mph you increase your speed, you will burn an additional------------calories pay lap
Q4. What is the true interpretation for R Square? A) 49% of the correlation of GDP per capita explains by independent variables. B) 49% of the correlation of independent variables can explain by GDP per capita. C) 49% of the variation of GDP per capita explains by independent variables. D) 49% of the auto-correlation of independent variables can explain by GDP per capita.
3. Marge aims to find out whether income predicts life satisfaction in any way. She assesses income and life satisfaction in 30 citizens of Springfield. Her calculations result in a slope b = 2.2 and an SE = 0.4. Can she conclude that income significantly predicts life satisfaction on the 5% level? . HO: B=0 H1: ẞ#0
A grocery store is interested in how customers' income affects the amount of money they spend each week. A regression analysis is performed to test this analysis. The results of the analysis are that the intercept is $17.80 and the slope is 0.0012. Based on these results, what is the predicted weekly grocery expenditure (to the nearest cent) for a household with an income of $65,000? $95.80 O$78.00 $45.23 $17.80 Ho: mean weekly expenditure = $78.00
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A biologist was recording various temperatures (in degrees Celsius) and predicting the amount of glucose produced by a plant (in milligrams). Suppose the linear equation was the following: ?̂ = 12.7 − 0.223? d) Suppose the correlation coefficient was −0.12. How would you classify the correlation between temperature and amount of glucose?