A statistical study found a correlationbetween the percent of family incomespent on food and the percent of familyincome spent on leisure activities. This isan example ofO a) a cause-and-effect relationshipO b)a common-cause factora presumed cause-and-effectrelationshipa reverse cause-and-effectrelationshipOc)O d)

It is an example of a common-cause factor as the correlation between the percent of family income…

Answered: A statistical study found a correlation…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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A researcher found that sales of televisions and lawn fertilizer have been increasing over the past 12 years. The sales had a strong positive linear correlation, but no evidence could be found to support a cause-and-effect relationship. Rather, this would have been purely coincidental. This is an example of a) an accidental cause-and-effect relationship b) a cause-and-effect relationship O c a reverse cause-and-effect relationship O a presumed cause-and-effect d) relationship
Example 4: A baker for a large supermarket has received a total of 185 bags of flour from different supplier. As a result, the bags he has received are of varying weight. The histogram shows information about the weight of the bags of flour: Frequency Density 30 40 50 60 70 80 90 100 Weight (pounds) 15 bags of flour weight between 35 and 40pounds. a) How many bags of flour weigh more than 80 pounds? b) What is the median of a bag flour.
A statistical program is recommended. A study of emergency service facilities investigated the relationship between the number of facilities and the average distance traveled to provide the emergency service. The following table gives the data collected. Average Number of Facilities Distance (miles) 1.67 11 1.11 16 0.82 21 0.62 27 0.50 30 0.47 (a) Develop a scatter diagram for these data, treating average distance traveled as the dependent variable. 1.8 1.8 35 1.8- 1.6 1.6 1.6 1.4 30 1.4 1.4 a 1.2 1.2 25 1.2 1. 1. E 1. 0.8 20 0.8 0.8- 0.6 0.6- 15 0.6- 0.4- 0.4- 0.4 0.2 10 0.2- 0. 5 0.2 10 15 20 25 30 35 0. 5 0. 10 15 20 25 30 35 0. 0.2 0.4 0.6 0.8 1. 1.2 1.4 1.6 1.8 10 15 20 25 30 35 Number Number Distance Number (b) Does a simple linear regression model appear to be appropriate? Explain. O Yes, the scatter diagram suggests that there is a linear relationship. O No, the scatter diagram suggests that there is a curvilinear relationship. O No, the scatter diagram suggests that there is…
A state's park system statistical report for the 2014/2015 fiscal year gave the accompanying data on x = amount of money collected in user fees (in thousands of dollars) and y = operating cost (in thousands of dollars) for nine state parks in a certain district. User Fees (thousands of dollars) Operating Costs (thousands of dollars) 17 99 74 363 811 3,618 380 1,377 33 241 427 768 500 1,034 734 2,205 760 1,620 (a) Construct a scatterplot of the data. A scatterplot has 9 points. The horizontal axis is labeled "x" and ranges from approximately 0 to 900. The vertical axis is labeled "y" and ranges from 0 to 4,000. The points are plotted from left to right in a horizontal band, starting from the middle left of the diagram. The points are somewhat scattered, becoming more scattered from left to right, and are between the approximate horizontal axis values of 10 and 820 and between the approximate vertical axis values of 100 and 2,000. A scatterplot has 9 points. The horizontal axis is…
find : c ) Does data provide evid. of an association between age and opinion of brand? Justify your answer.
The data provides information on life expectancy and the number of televisions per thousand people in a sample of 22 countries, as reported by the world almanac and book of facts 2006 A. Describe the Direction and strength of the correlation between the two variables B. Because of the association between the variables, someone might mistakenly conclude that simply sending televisions to the countries with the lower life expectancies would cause their inhabitants to live longer. Comment on this argument and the reason televisions are likely associated with longer life expectancies C. In general, if two variables are strongly associated, does it follow there must be a cause and effect relationship between them? Explain
A research study reports the results of a correlational study that shows a negative relationship between parent stress at work and the mental health of their children. What possible findings would show this? A. Parents who report higher stress at work tend to have children with higher mental well-being scores B. Parents to report higher stressed out work tend to have children with higher anxiety scores C. Parents who report lower stress at work tend to have children with lower anxiety scores D. Parents who report lower stress at work tend to have children with higher mental well-being scores
“The incidence of depression among college students is negatively correlated with the number of sunny days each year in the locale where they attend college.” This statement means that: a. a student attending college in a locale with very few sunny days will become depressed. b. if a depressed student were to move to a locale with more sunny days, the student's depression would subside. c. the chances of a college student being depressed tend to increase as the number of sunny days increases. d. the chances of a college student being depressed tend to increase as there are fewer sunny days.
Online clothes An online clothing retailer keeps trackof its customers’ purchases. For those customers who signed up for the company’s credit card, the com-pany also has information on the customer’s Age and Income. A random sample of 500 of these customers shows the following scatterplot of Total Yearly Pur-chases by Age:The correlation between Total Yearly Purchases and Age isr = 0.037. Summary statistics for the two variables are: a) What is the linear regression equation for predictingTotal Yearly Purchase from Age?b) Do the assumptions and conditions for regressionappear to be met?c) What is the predicted average Total Yearly Purchasefor an 18-year-old? For a 50-year-old? d) What percent of the variability in Total Yearly Pur-chases is accounted for by this model? e) Do you think the regression might be a useful one forthe company? Explain.
There is a strong correlation between the number of students graduating from SVS and the population of squirrels in York Region. The most likely type of causal relationship is:A.cause and effect B.accidental C.presumed D.reverse cause and effect
GRC often rely heavily on raising money for an "annual fund" to support operations. Alumni are typically solicited for donations to the annual fund. Studies suggest that the graduate's annual income is a good predictor of the amount of money he or she would be willing to donate, and there is a reasonably strong, positive, linear relationship between these variables. In the studies described: O a. annual income is the predictor variable O b. the correlation between annual income and the size of the donation is negative. O c. the size of the donation to the annual fund is the predictor variable O d. All of the above O e. None of the above
Correlation studies are often used to help determine whether certain characteristics are controlled more by genetic influences or by environmental influences. These studies often examine adopted children and compare their behaviors with the behaviors of their birth parents and their adoptive parents. One study examined how much time individuals spend watching TV (Plomin, Corley, DeFries, & Fulker, 1990). The following data are similar to the results obtained in the study. a. Compute the correlation between the children and their birth parents. b. Compute the correlation between the children and their adoptive parents. c. Based on the two correlations, does TV watching appear to be inherited from the birth parents or is it learned from the adoptive parents?

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