The accompanying data represent the percentages of teenagers in various countries that have used certain drugs. Complete parts (a) through (c) below.K547.3832 24BG.H.E F36415C.CountryDrug 1, xOther Drugs,y19244022,22188 13 3a. Determine the correlation coefficient between the percentage of teenagers who have used Drug 1 and the percentage who have used other drugs.NexEces The accompanying data represent the percentages of teenagers in various countries that have used certain drugs. Complete parts (a) through (c) below.a. Determine the correlation coefficient between the percentage of teenagers who have used Drug 1 and the percentage who have used other drugs.(Round to two decimal places as needed.)b. Find the equation of the regression line for the percentage of teenagers who have used Drug 1 and the percentage who have used other drugs.y=x+y%3D(Round to two decimal places as needed.)Nextes

The question is based on a correlation and regression Given :

Answered: The accompanying data represent the…

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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Similar questions

Which set of variables has correlation and causation? A. distance traveled and money spent on gas B. distance traveled and money spent on snacks C. distance traveled and number of drinks consumed D. distance traveled and time spent listening to music
You wish to determine if there is a linear correlation between the age of a driver and the number of driver deaths. The following table represents the age of a driver and the number of driver deaths per 100,000. Use a significance level of 0.05 and round all values to 4 decimal places. Driver Age Number of Driver Deaths per 100,000 21 22 39 21 38 18 23 22 79 36 42 22 65 29 Ho: p = 0 Ha: p= 0 Find the Linear Correlation Coefficient r = Find the p-value p-value = The p-value is O Less than (or equal to) a Greater than a The p-value leads to a decision to O Reject Ho O Accept Ho O Do Not Reject Ho The conclusion is O There is insufficient evidence to make a conclusion about the linear correlation between driver age and number of driver deaths. There is a significant linear correlation between driver age and number of driver deaths. O There is a significant negative linear correlation between driver age and number of driver deaths. O There is a significant positive linear correlation…
Statistics Question
In order to advise students properly, a college advisor is interested in the relationship between a student's GPA and the number of hours the student an average weck. The data are shown in the table. Study Time (in hours) 33 Student GPA 3.2 19 16 2.4 31 3.1 5. 24 2.7 28 2.9 7 1.7 34 3.3 14 2.2 10 35 3.4 11 1.8 Part 1 of 5 (a) Let I represent study time and let y nepresent GPA. Graph the points. Grade Point Average vs. Weekly Study Time Weckly Study Time (hours) Part 2 of 5 (b) Does there appear to be a linear trend? Yes Part: 2/5 Part 3 of 5 (c) use the data points (16, 2.4) and (34, 3 3) to find an eguation of the line through these points. Express numbers as decimas or integers. Write answer in slope-intercept form (y = MI+ b). The equation is GPA
The data below represent the number of days absent, x, and the final grade, y, for a sample of college students at a large university. Complete parts (a) through (e) below. У, No. of absences, x 1 2 4 6. 7 8 9. Final grade, y 88.8 85.9 83.0 80.6 77.7 73.3 63.5 68.3 65.4 62.6 (Round to three decimal places as needed.) A. For every unit change in the final grade, the number of days absent falls by days, on average. B. For every day absent, the final grade falls by on average. C. For zero days absent, the final score is predicted to be 88.778 . D. For a final score of zero, the number of days absent is predicted to be days. E. It is not appropriate to interpret the y-intercept. (c) Predict the final grade for a student who misses five class periods and compute the residual. Is the observed final grade above or below average for this number of absences? The predicted final grade is |. This observation has a residual of, which indicates that the final grade is average. (Round to one decimal…
Cigarette smoking and cancer have been linked. Assume the number of bladder cancer deaths (in deaths per 100 thousand) and cigarette sales (in cigarettes sold/person) for 35 randomly selected countries are in the table below. X, cigarette sales (in cigarettes/person) Y, the number of bladder cancer deaths (in deaths/100 thousand) 26.18 4.09 23.78 4.89 28.27 4.46 21.25 5.14 24.96 5.27 28.6 4.46 26.92 4.69 20.1 3.08 19.96 2.89 23.44 2.93 14 3.31 30.34 3.46 20.08 2.94 23.32 3.72 29.18 4.99 28.04 3.2 27.91 4.75 18.24 2.99 40.46 5.6 20.94 3.64 16.08 3.06 18.2 2.9 22.86 4.78 27.56 4.04 18.06 3.25 29.14 5.3 21.58 4.65 33.6 4.78 21.17 4.04 26.38 4.47 21.84 2.91 31.1 5.11 28.92 4.79 42.4 6.54 22.12 4.23 a) State the random variables. rv X = of rv Y = of b) Make a scatterplot of X versus Y in StatCrunch (optional). Why do we wish to sketch a scatterplot? c) Find the equation…
3. You would like to determine if there is a statistical relationship between the amount of caffein in a cup of coffee and their sales at their coffee franchises. The data is included in the set "Coffee by the Cup". Here is information about the variables. Variable Caffeine Cups Sold Measurement Amount of caffeine in one cup Number of cups of the coffee Units Milligrams Cups sold sold at all of the franchises a. Which variable is the explanatory variable and which variable is the response variable? b. Construct a scatterplot of the data. Based upon the scatterplot is there a linear relationship between the amount of caffeine in one cup of the coffee and the number of cups of coffee sold? Justify your reasoning using the scatterplot. c. Run a t-test for correlation using technology. Make sure you include the p-value and the printout. According to the t-test, is there a statistical relationship between the amount of caffeine in a cup of coffee and the number of cups sold? Justify your…
Based on the given scatter diagram, choose the correct statement. a. It is a positive correlation. The more time an individual spends running, the higher their body fat tends to be. b. It is a positive correlation. The more time an individual spends running, the lower their body fat tends to be. c. It is a negative correlation. The more time an individual spends running, the higher their body fat tends to be. d. It is a no correlation. The amount of time an individual spends running has no correlation with his/her body fat tends to be. e. It is a negative correlation. The more time an individual spends running, the lower their body fat tends to be.
Construct a scatter plot from the given points and describe the correlation.
You wish to determine if there is a linear correlation between the age of a driver and the number of driver deaths. The following table represents the age of a driver and the number of driver deaths per 100,000. Use a significance level of 0.01 and round all values to 4 decimal places. Driver Age 65 69 48 37 49 27 62 64 Ho: p = 0 Ha: p = 0 r= Find the p-value p-value= Number of Driver Deaths per 100,000 22 22 34 Find the Linear Correlation Coefficient The p-value is Greater than a Less than (or equal to) a 23 28 20 The p-value leads to a decision to O Do Not Reject Ho O Accept Ho O Reject Ho 33 33 The conclusion is O There is a significant negative linear correlation between driver age and number of driver deaths. There is a significant linear correlation between driver age and number of driver deaths. O There is insufficient evidence to make a conclusion about the linear correlation between driver age and number of driver deaths. O There is a significant positive linear correlation…
Which one of the following summary statistics best matches the data on the abundance of various bird species shown here? Frequency (No. species) 25 20 15 10 5 0 0 Mean = Mean = Mean = 100 200 300 400 500 600 Abundance (No. individuals) 75 individuals, s.d. = 122 individuals 300 individuals, s.d. = 14871 individuals 10 individuals, s.d. = 10 individuals Mean = 10 individuals, s.d. = 14871 individuals Mean 75 individuals, s.d. = 14871 individuals

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