A nationwide standardized test taken by high-school juniors and seniors may or may not measure academic potential, but we can nonetheless examine the relationship between scores on such tests and performance in college. We have chosen a random sample of 105 students just finishing their first year of college, and for each st
Do artificial sweeteners cause weight gain? People who use artificial sweeteners in place of sugar tend to be heavier than people who use sugar. Does this mean that artificial sweeteners cause weight gain? Give a more plausible explanation for this association.
Do you think there is a correlation between CEO salaries and the degree of success of a company? If you were to take a sample of companies with comparable size, market capitalization, and product category, and plot CEO salaries against the net profit of their respective companies, do you expect to find a linear correlation betw
Question 1: For an experiment comparing more than two treatment conditions you should use analysis of variance rather than separate t tests because: conducting several t tests would inflate the risk of a Type I error. separate t tests would require substantially more computations . a test based on variances is more sensiti
11-59. Marketers know that tastes differ in various regions of the country. In the rental car business, an industry expert has given the opinion that there are strong regional preferences for size of car and quotes the following data in support of that view: Region of Count
1. You are given the following data. Number of Absences Final grades 0 96 1 91 2 78 2 83 3 75 3 62 4 70 5 68 6 56 a. Make a scatter plot for the data. You do not need to turn this in, but based on your scatterplot, does it look like the correlation is significa
How to show a relationship between smoking and productivity, using a correlation coefficient. What would a visual of that formula as a scatterplot diagram look like for smoking and worker productivity.
In a study, the correlation coefficient for W and X is -0.25. The correlation coefficient for X and Y is 0.20. The coefficient of determination for X and Z is 0.16. The coefficient of alienation for Y and Z is 0.90. Which pair of variables has the highest amount of variance accounted for?
3. Individual Assignment: Inferential Problems Access the University of Phoenix Material, "Data for Inferential Practice Problems." Use the Excel® Analysis ToolPak? when necessary for the following: a. Determine the types of measurement scales for each variable (Nominal, Ordinal, Interval, Ratio): name gender absen
Share the practical applications of the study from the Unit 2 Individual Project. How would the results of this survey be used in the workplace? Briefly describe correlational research. Name a variable from this study and one from the workplace that might prove to provide a correlational relationship and explain why you would
Correlation: wish to determine the correlation between the height (in inches) and weight (in pounds) of 21-year-old males... 3. All but one of the following statements contains ... 4. I want to examine the relationship between gas mileage of cars and the engine size ... 8. A statistics student computes the correlation between two variables in her spreadsheet, and finds ...
2. I wish to determine the correlation between the height (in inches) and weight (in pounds) of 21-year-old males. To do this, I measure the height and weight of two 21-year-old men. The measured values are The correlation r computed from the measurements on these males is A. 1.0 B. -1.0 C. near 0 because the heights
For the following data calculate the correlation coefficient r and make a conclusion about the type of correlation. The number of hours 6 students watched T.V. during the weekend and the scores of each student who took a test the following Monday. Hours spent watching TV, X 0 1 2 3 3 5 Test Scores, Y
Calculate the correlation coefficient r, letting Row 1 represent the x-values and Row 2 the y-values. Then calculate it again, letting Row 2 represent the x-values and Row 1 the y-values. What effect does switching the variables have on r? Row 1 20 26 34 43 51 69 72 Row 2 165 144 112 180 20
Make up a scatter diagram with 10 dots for each of the following situations: (a) perfect positive linear correlation, (b) large but not perfect positive linear correlation, (c) small positive linear correlation, (d) large but not perfect negative linear correlation, (e) no correlation, (f) clear curvilinear correlati
Calculate the correlation coefficient r, letting Row 1 represent the x-values and Row 2 the y-values. What effect does switching the variable have on r? Row 1 Row 2 10 151 25 179 32 183 47 198 54 180 63 180 75 117 1. Calculate the correlat
(1.) What is the difference between strong positive and strong negative correlation? Is there value in a strong negative correlation? If so, what? In your answer provide examples from your life. (2) What does zero correlation tell you? When do you see this type of correlation in your life?
83 In which of the following situations would you get the largest benefit from diversifying your investment across two stocks? a. there is perfect positive correlation. b there is perfect negative correlation. c. there is modest positive correlation. d. there is modest negative correlation. e. there is not correlation.
A study was done to see if there is a relationship between the number of calories a sandwich has and the sodium content of a sandwich. Several different types of sandwiches were used. The data is as follows: Calories, x 174 231 354 240 419 386 419 Sodium(mg), y 787 1159 990 581 645 1202 495 Find the correlation a
Question # 1 If r=-0.726 and n=6, test the significance of the correlation coefficient at a=.05 Question # 2 For the conjecture "The average age of students in the class is 25", the null hypothesis is ???
A study of employees at a large company found a negative correlation between weight and distance walked on an average day. In other words, people who walked more weighed less. Would you conclude that walking causes lower weight? Can you think of an alternate explanation for the findings?
Why might a researcher want to use multivariate analysis rather than a univariate or bivariate analysis technique?
A correlation matrix (correlation coefficients and probability level under the hypothesis rho=0) for a company's sales force (age, years of service, and current sales) is given below. Comment. Age Years of Service Current Sales Age
The management of a regional bus line thought its cost of gas might be correlated with its passenger/mile ratio. Comment on the data and correlation matrix below.
The management of a regional bus line thought its cost of gas might be correlated with its passenger/mile ratio. Comment on the data and correlation matrix below. Average Wholesale Cost of Gas Passenger/Mile Ratio 56.5 8.37
For each of the fifty states if you look at the state average income and the percentage of people in that state who are foreign-born immigrants, you will see a positive correlation. Does this mean immigrants tend to earn more than other people? Or does it mean immigrants improve a state's economy? If not, what could expl
A manager would like to know which of the following factors has the strongest link to the salary an employee earns: age, gender, experience, time at the form, or education. Looking at the file employees.xls attached below, what do you conclude? I am stuck on this question.
A regional commuter airline selected a random sample of 25 flights and found that the correlation between the number of passengers and the total weight, in pounds, of luggage stored in the luggage compartment is 0.94. Using the .05 significance level, can we conclude that there is a positive association between the two varia
Compute the sample covariance and sample correlation coefficient for the following data. X Y 1 94 2 78 2 70 1 88 3 68 4 40 8 30 3 60 Please show me work on how it's done. Thanks.
I need help in doing these 2 equations step-by-step or if it is done in excel could you please explain how? ------------------------------------------------- #1 For the last 6 years, I have kept fairly detailed data on wind speed and the resultant hull speed of my sailboat. Here is the windspeed-hullspeed data
If the coefficient of correlation is 0.4, the percentage of variation in the dependent variable explained by the variation in the independent variable: a) 40% b) 16% c) 4% d) can be any positive value
If you were to draw a scatter plot of the number of women in the workforce versus the number of Christmas trees sold in the United States for each year between 1930 and the present, you would find a very strong correlation. Why do you think this would be true? Does one cause the other?