Below is the Minitab display of the scatterplot and regression line for asample of 10 pharmacies. The pharmacies are used to examine the relationbetween prescription sales volume and the percentage of prescriptioningredients purchased directly from the supplier. Use the Minitab displayto answer questions 22 through 25.Prescription Sales versus % of Prescription Ingredients Analyisy=4.70+1.97x1401201008060402010203040506070% of Prescription IngredientsQuestion 22. A student calculates the linear correlation coefficient and getsr = 1.18. Which of the following statements correctly explains how you knowthat student's calculation is incorrect?(a) The value obtained for r cannot be more than 1.(b) The value obtained for r cannot be positive.(c) The value obtained for r should be -1.18.(d) All of the above.Prescription Sales Question 23. A different student claims that the linear correlation coeffi-cient is r =-0.46. Which of the following statements correctly explains howyou know that the student's calculation is incorrect?(a) The value of r should be closer to -1.(b) The slope of the regression line is positive.(c) None of the above.(d) All of the above.Question 24. Which of the following is the best estimate for the value ofthe linear correlation coefficient r?(a) r is between -1.0 and -0.50(b) r is between -0.50 and 0(c) r is between 0 and 0.50(d) r is between 0.50 and 1.0Question 25. Predict sales volume for a pharmacy that purchases 15% ofits prescription ingredients directly from the supplier.(a) 4.9955(b) 34.25(c) 7.655(а) 44.1

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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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Several years ago, the state of California launched an aggressively advertisement campaign against smoking. We've interviewed students from 16 college campuses in California and recorded for each campus the percentage of students who claimed that they had encountered assay least one anti smoking advertisement on campus in the past month. Here are those percentages. 53 39 30 49 48 42 41 38 26 36 40 42 52 51 45 50 Construct a box and whisker plot for the data.
Please help 11 and 12
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An economist wants to determine whether there is a linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. The data are shown in the table below. c. Compute and interpret the correlation coefficient. d. Compute and interpret the coefficient of determination. e. Test for the significance of the linear relationship. Use a 0.05 level of significance. State your conclusion. Hint: Your conclusion is either of the following. • There is a significant linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. • There is no significant linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. GDP 1.6 3.6 4.9 1.1 0.9 2.9 2.7 2.3 1.6 1.5 (trillion dollars) Carbon Dioxide Emissions 428.2 828.8 1214.2 444.6 264 415.3 571.8 454.9 358.7 573.5 (millions of metric tons)
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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…
Refer back to the histogram from question #4. Compute the mean number of shipping days Compute the median number of shipping days Write the 5-number summary for this data. Create box plot.
What is the stem-and-leaf plot for the data set? Name Stanley Ben Prusiner Torsten Nils Wiesel Richard Axel 57 58 Robert Coleman Richards 59 James Alexander Mirrlees 60 O O Stem Stem 5 Stem 6 7 5 Stem 6 7 6 5 5 7 6 Age 55 7 Leaf 8 5 Leaf O O 0 O 5 Leaf O O Leaf 5 O O Name Age Robert Merton Solow 63 Stanley Cohen 64 Peter Mansfield 70 Vernon Lomax Smith 75 Richard Fred Heck 79 8 89 2 3 4 5 9 8 89 2 5 9 8 89 4 4 5 9 7 8 9 3 4 5 9

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