The table below show data that has been collected from different fields from various farms in acertain valley. The table contains the grams of Raspberries tested and the amount of theirVitamin C content in mg. Find a linear model that express Vitamin C content as a function of theweight of the Raspberries.grams70 75 801 859095100Vitamin Ccontent in mg18.120.323.22527.229.532.6A) Find the regression equation: y =Round your answers to 3 decimal places+XB) Answer the following questions using your un-rounded regression equation.If we test 130 grams of raspberries what is the expected Vitamin C content?the nearest tenth)mg (round to

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Answered: 100 32.6 A) Find the regression…

A First Course in Probability (10th Edition)

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Author:Sheldon Ross

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Chapter1: Combinatorial Analysis

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Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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Heip A regression of average weekly earnings (AWE, measured in dollars) on age (measured in years) using a random sample of college-educated full-time workers aged 25-65 yields the following: AWE = 647.9310 +8.9280 × Age, R2 = 0.021, SER=580.4. The coefficient shows the marginal effect of Age on AWE; that is, AWE is expected to increase by $ for each additional year of age. is the intercept of the regression line. It determines the overall level of the line. (Round your responses to four decimal places.) The standard error of the regression (SER) is 580.4. What are the units of measurement for the SER? O A. Dollars. O B. Dollars per year. C. Unit-free. O D. Dollars per week. The regression R is 0.021. What are the units of measurement for the R2? O A. Dollars per year. O B. Dollars. Click to select your answer(s). W 0正 e to search
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=ax+b a=-0.971 b=21.794 r²-0.872356 r=-0.934 Use this to predict the number of situps a person who watches 5 hours of TV can do (to one decimal place)
Using your dataset, run a regression of Y=GPA and X=# Friends.(do not need your actual data, just the regression results)a) State what this regression is attempting to analyze. “By running this regression, we areattempting to show.....”b) Write out the regression equation and describe what it shows (if Friends increase by 1, then. . . ).c) Find your hypothesized GPA when the # friends equals 17.d) Is the slope of # of Friends significantly different from zero?Include Ho, Ha, decision rule, t statistic from table, tc, decision, and conclusion.e) Is the r-squared of # of Friends significantly different from zero?Include Ho, Ha, decision rule, F statistic from table, Fc, decision, and conclusion.
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2. Participants were kept awake for a certain number of hours before given a visuospatial task. Researchers measured how many correct responses each participant had. Results are shown below. Use alpha = .01. Number of Correct Hours Kept Awake (X) Responses (Y) 21 X = 10 SS, = 422 Y = 10 SS, = 690 2 4 19 %3D 6. 13 SPxy =-525 ху 5 20 S, =5.70 S, = 7.29 9. 11 10 9. 14 5 15 5 17 2 18 1 17 1 13 4 18 8 11 A. Graph the data. B. State the hypotheses. C. Make a decision about the null. a. Calculate Pearson's r i. Decision about null hypothesis? b. Calculate effect size i. Interpret effect size. D. State your conclusion. E. Relate your conclusion to the research. F. Calculate the regression formula. G. If someone was kept awake for 9 hours, what is the predicted number of correct responses?
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=ax+b a=-1.34 b=36.954 r2=0.966289 r=-0.983 Use this to predict the number of situps a person who watches 5 hours of TV can do (to one decimal place)
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=a+bx b=-0.993 a=29.135 r2=0.463761 r=-0.681 Use this to predict the number of situps a person who watches 6 hours of TV can do. Round to one decimal place.
A regression analysis was performed to determine if there is a relationship between hours of TV watched per day (x) and number of sit ups a person can do (y ). The results of the regression were: y=ax+b a=-1.33 b=25.138 r2=0.712336 r=-0.844 Use this to predict the number of sit ups a person who watches 10 hours of TV can do, and please round your answer to a whole number.
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y = a x + b a = -1.043 b = 29.088 %3D %3! r2 = 0.390625 r = -0.625 Use this to predict the number of situps a person who watches 6.5 hours of TV can do. situps : %3D [one decimal accuracy1
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=a+bx b=-1.127 a=25.258 r2=0.695556 r=-0.834 Use this to predict the number of situps a person who watches 8 hours of TV can do. Round to one decimal place.

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100 32.6 A) Find the regression equation: y = Round your answers to 3 decimal places + X B) Answer the following questions using your un-rounded regression equation. If we test 130 grams of raspberries what is the expected Vitamin C content? the nearest tenth) mg (round to