Question: a. display the data in a scatter
a. display the data in a scatter plot,
b. calculate the sample correlation coefficient r,
c. describe the type of correlation, if any, and interpret the correlation in the context of the data, and
d. use Table 11 in Appendix B to make a conclusion about the correlation coefficient.
If convenient, use technology. Let α = 0.01.
The ages (in years) of 11 children and the numbers of words in their vocabulary
Transcribed Image Text:
Age, r 1 2 3 4 5 6 3 5 2 4 6 Vocabulary size, y 3 220 540 1100 2100 2600 730 2200 260 1200 2500
> a. construct a scatter plot of the data, b. identify any possible outliers, and c. determine whether the point is influential. Explain your reasoning. 1 3 6 8 8 12 14 у 4 7 10 9 15 3.
> a. construct a scatter plot of the data, b. identify any possible outliers, and c. determine whether the point is influential. Explain your reasoning. 5 6 9 | 33 28 10 14 17 19 44 32 26 25 23 23 8.
> a. find the equation of the regression line, b. construct a scatter plot of the data and draw the regression line, c. construct a residual plot, and d. determine whether there are any patterns in the residual plot and explain what they suggest about t
> a. find the equation of the regression line, b. construct a scatter plot of the data and draw the regression line, c. construct a residual plot, and d. determine whether there are any patterns in the residual plot and explain what they suggest about t
> Describe type I and type II errors for a hypothesis test of the indicated claim. A cellphone repair shop advertises that the mean cost of repairing a phone screen is less than $75.
> Perform the steps below. a. Find the equation of the regression line for the data, letting Row 1 represent the x-values and Row 2 the y-values. Sketch a scatter plot of the data and draw the regression line. b. Find the equation of the regression line fo
> Perform the steps below. a. Find the equation of the regression line for the data, letting Row 1 represent the x-values and Row 2 the y-values. Sketch a scatter plot of the data and draw the regression line. b. Find the equation of the regression line fo
> Use the table, which shows the years of experience of 14 registered nurses and their annual salaries (in thousands of dollars). A salary analyst claims that the population has a significant correlation for α = 0.01. Test this claim. Ye
> Explain how to predict y-values using the equation of a regression line.
> Use the table, which shows the years of experience of 14 registered nurses and their annual salaries (in thousands of dollars). An analyst used the regression line you found in Exercise 28 to predict the annual salary for a registered nurse with 28 year
> Use the table, which shows the years of experience of 14 registered nurses and their annual salaries (in thousands of dollars). Find an equation of the regression line for the data. Sketch a scatter plot of the data and draw the regression line. Yea
> Use the table, which shows the years of experience of 14 registered nurses and their annual salaries (in thousands of dollars). Using the scatter plot of the registered nurse salary data shown below, what type of correlation, if any, do you think the da
> Find the equation of the regression line for the data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of
> Find the equation of the regression line for the data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of
> Find the equation of the regression line for the data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of
> Describe type I and type II errors for a hypothesis test of the indicated claim. A campus security department publicizes that at most 25% of applicants become campus security officers.
> Find the equation of the regression line for the data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of
> Find the equation of the regression line for the data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of
> Find the equation of the regression line for the data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of
> Find the equation of the regression line for the data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of
> Two variables have a positive linear correlation. Is the slope of the regression line for the variables positive or negative?
> Find the equation of the regression line for the data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of
> Find the equation of the regression line for the data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of
> Find the equation of the regression line for the data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of
> Describe type I and type II errors for a hypothesis test of the indicated claim. A researcher claims that the percentage of adults in the United States who own a video game system is not 26%.
> What is a residual? Explain when a residual is positive, negative, and zero.
> Determine whether there is a perfect positive linear correlation, a strong positive linear correlation, a perfect negative linear correlation, a strong negative linear correlation, or no linear correlation between the variables.
> In your own words, what does it mean to say “correlation does not imply causation”? List a pair of variables that have correlation but no cause-and-effect relationship.
> What are the null and alternate hypotheses for a two-tailed t-test for the population correlation coefficient ρ? When do you reject the null hypothesis?
> Discuss the difference between r and ρ.
> Describe type I and type II errors for a hypothesis test of the indicated claim. A local chess club claims that the length of time to play a game has a standard deviation of more than 12 minutes.
> Explain how to determine whether a sample correlation coefficient indicates that the population correlation coefficient is significant.
> Give examples of two variables that have perfect positive linear correlation and two variables that have perfect negative linear correlation.
> In Exercise 26, let the time (in seconds) to sprint 10 meters represent the x-values and the maximum weight (in kilograms) for which one repetition of a half squat can be performed represent the y-values. Calculate the correlation coefficient r. What eff
> Perform a hypothesis test using Table 5 in Appendix B to make a conclusion about the correlation coefficient. The table in Exercise 26 shows the maximum weights (in kilograms) for which one repetition of a half squat can be performed and the times (in se
> Perform a hypothesis test using Table 5 in Appendix B to make a conclusion about the correlation coefficient. The table in Exercise 25 shows the maximum weights (in kilograms) for which one repetition of a half squat can be performed and the jump heights
> Perform a hypothesis test using Table 5 in Appendix B to make a conclusion about the correlation coefficient. The weights (in pounds) of eight vehicles and the variabilities of their braking distances (in feet) when stopping on a wet surface are shown in
> Perform a hypothesis test using Table 5 in Appendix B to make a conclusion about the correlation coefficient. The weights (in pounds) of eight vehicles and the variabilities of their braking distances (in feet) when stopping on a dry surface are shown in
> In Exercise 26, add data for an international soccer player who can perform the half squat with a maximum of 210 kilograms and can sprint 10 meters in 2.00 seconds to the data set. Describe how this affects the correlation coefficient r.
> In Exercise 25, remove the data for the international soccer player with a maximum weight of 170 kilograms and a jump height of 64 centimeters from the data set. Describe how this affects the correlation coefficient r.
> In Exercise 24, remove the data for the girl who is 57 inches tall and scored 128 on the IQ test from the data set. Describe how this affects the correlation coefficient r.
> Describe type I and type II errors for a hypothesis test of the indicated claim. An urban planner claims that the noontime mean traffic flow rate on a busy downtown college campus street is 35 cars per minute.
> What does the sample correlation coefficient r measure? Which value indicates a stronger correlation: r = 0.918 or r = -0.932? Explain your reasoning.
> In Exercise 23, add data for a child who is 6 years old and has a vocabulary size of 900 words to the data set. Describe how this affects the correlation coefficient r
> a. display the data in a scatter plot, b. calculate the sample correlation coefficient r, c. describe the type of correlation, if any, and interpret the correlation in the context of the data, and d. use Table 11 in Appendix B to make a conclusion abo
> a. display the data in a scatter plot, b. calculate the sample correlation coefficient r, c. describe the type of correlation, if any, and interpret the correlation in the context of the data, and d. use Table 11 in Appendix B to make a conclusion abo
> a. display the data in a scatter plot, b. calculate the sample correlation coefficient r, c. describe the type of correlation, if any, and interpret the correlation in the context of the data, and d. use Table 11 in Appendix B to make a conclusion abo
> a. display the data in a scatter plot, b. calculate the sample correlation coefficient r, c. describe the type of correlation, if any, and interpret the correlation in the context of the data, and d. use Table 11 in Appendix B to make a conclusion abo
> a. display the data in a scatter plot, b. calculate the sample correlation coefficient r, c. describe the type of correlation, if any, and interpret the correlation in the context of the data, and d. use Table 11 in Appendix B to make a conclusion abo
> Two variables are given that have been shown to have correlation but no cause-and-effect relationship. Describe at least one possible reason for the correlation. Marriage rate in Kentucky and number of deaths caused by falling out of a fishing boat
> Two variables are given that have been shown to have correlation but no cause-and-effect relationship. Describe at least one possible reason for the correlation. Ice cream sales and homicide rates
> Describe type I and type II errors for a hypothesis test of the indicated claim. A used textbook selling website claims that at least 60% of its new customers will return to buy their next textbook.
> Two variables are given that have been shown to have correlation but no cause-and-effect relationship. Describe at least one possible reason for the correlation. Alcohol use and tobacco use
> Describe the range of values for the correlation coefficient.
> Two variables are given that have been shown to have correlation but no cause-and-effect relationship. Describe at least one possible reason for the correlation. Value of home and life span
> The scatter plots show the results of a survey of 20 randomly selected males ages 24–35. Using age as the explanatory variable, match each graph with the appropriate description. Explain your reasoning. a. Age and body temperature b. A
> The scatter plots show the results of a survey of 20 randomly selected males ages 24–35. Using age as the explanatory variable, match each graph with the appropriate description. Explain your reasoning. a. Age and body temperature b. A
> The scatter plots show the results of a survey of 20 randomly selected males ages 24–35. Using age as the explanatory variable, match each graph with the appropriate description. Explain your reasoning. a. Age and body temperature b. A
> The scatter plots show the results of a survey of 20 randomly selected males ages 24–35. Using age as the explanatory variable, match each graph with the appropriate description. Explain your reasoning. a. Age and body temperature b. A
> Identify the explanatory variable and the response variable. An actuary at an insurance company wants to determine whether the number of hours of safety driving classes can be used to predict the number of driving accidents for each driver.
> Identify the explanatory variable and the response variable. A nutritionist wants to determine whether the amounts of water consumed each day by persons of the same weight and on the same diet can be used to predict individual weight loss.
> Determine whether there is a perfect positive linear correlation, a strong positive linear correlation, a perfect negative linear correlation, a strong negative linear correlation, or no linear correlation between the variables.
> The table at the right shows the residential natural gas expenditures (in dollars) in one year for a random sample of households in four regions of the United States. Assume that the populations are normally distributed and the population variances are e
> a. Identify the claim and state H0 and Ha. b. Determine whether the hypothesis test is left-tailed, right-tailed, or two-tailed, and whether to use a z-test, a t-test, or a chi-square test. Explain your reasoning. c. Choose one of the options. Option
> Determine whether there is a perfect positive linear correlation, a strong positive linear correlation, a perfect negative linear correlation, a strong negative linear correlation, or no linear correlation between the variables.
> Determine whether there is a perfect positive linear correlation, a strong positive linear correlation, a perfect negative linear correlation, a strong negative linear correlation, or no linear correlation between the variables.
> Two variables have a positive linear correlation. Does the dependent variable increase or decrease as the independent variable increases? What if the variables have a negative linear correlation?
> a. identify the claim and state H0 and Ha, b. find the critical value(s) and identify the rejection region(s), c. find the standardized test statistic z, d. decide whether to reject or fail to reject the null hypothesis, and e. interpret the decision
> a. identify the claim and state H0 and Ha, b. find the critical value(s) and identify the rejection region(s), c. find the standardized test statistic z, d. decide whether to reject or fail to reject the null hypothesis, and e. interpret the decision
> a. identify the claim and state H0 and Ha, b. find the critical value(s) and identify the rejection region(s), c. find the standardized test statistic z, d. decide whether to reject or fail to reject the null hypothesis, and e. interpret the decision
> Determine whether a normal sampling distribution can be used. If it can be used, test the claim about the difference between two population proportions p1 and p2 at the level of significance a. Assume the samples are random and independent. Claim: p1 > p
> Determine whether a normal sampling distribution can be used. If it can be used, test the claim about the difference between two population proportions p1 and p2 at the level of significance a. Assume the samples are random and independent. Claim: p1 = p
> Determine whether a normal sampling distribution can be used. If it can be used, test the claim about the difference between two population proportions p1 and p2 at the level of significance a. Assume the samples are random and independent. Claim: p1 < p
> Determine whether a normal sampling distribution can be used. If it can be used, test the claim about the difference between two population proportions p1 and p2 at the level of significance a. Assume the samples are random and independent. Claim: p1 ≠ p
> The table below shows the winning times (in seconds) for the men’s and women’s 100-meter runs in the Summer Olympics from 1928 to 2016. a. Display the data in a scatter plot, calculate the correlation coefficient r, a
> Construct the indicated confidence interval for p1 - p2. Assume the samples are random and independent. Repeat Exercise 25 but with a 99% confidence interval. Compare your result with the result in Section 6.3, Exercise 27, part (b).
> Construct the indicated confidence interval for p1 - p2. Assume the samples are random and independent. In Section 6.3, Exercises 27 and 28, let p1 be the proportion of the population of U.S. college graduates who expect to stay at their first employer f
> Construct the indicated confidence interval for p1 - p2. Assume the samples are random and independent. In a survey of 10,000 students taking the SAT, 7% were undecided on an intended college major. In another survey of 8000 students taken 10 years befor
> Construct the indicated confidence interval for p1 - p2. Assume the samples are random and independent. In a survey of 10,000 students taking the SAT, 7% were planning to study visual and performing arts in college. In another survey of 8000 students tak
> Use the figure shown at the left, which gives the percentages of full-time employed men and women in the United States who work 40 hours per week and who work more than 40 hours per week. Assume the survey included random samples of 300 men and 250 women
> Use the figure shown at the left, which gives the percentages of full-time employed men and women in the United States who work 40 hours per week and who work more than 40 hours per week. Assume the survey included random samples of 300 men and 250 women
> Use the figure shown at the left, which gives the percentages of full-time employed men and women in the United States who work 40 hours per week and who work more than 40 hours per week. Assume the survey included random samples of 300 men and 250 women
> Explain how to perform a two-sample z-test for the difference between two population proportions.
> Use the figure shown at the left, which gives the percentages of full-time employed men and women in the United States who work 40 hours per week and who work more than 40 hours per week. Assume the survey included random samples of 300 men and 250 women
> Use the figure, which shows the percentages of newlyweds in the United States who have a spouse of a different race or ethnicity. The survey included random samples of 1000 Asian newlyweds, 1000Â Hispanic newlyweds, 1000 black newlyweds, and 1
> Use the figure, which shows the percentages of newlyweds in the United States who have a spouse of a different race or ethnicity. The survey included random samples of 1000 Asian newlyweds, 1000Â Hispanic newlyweds, 1000 black newlyweds, and 1
> Use the figure, which shows the percentages of newlyweds in the United States who have a spouse of a different race or ethnicity. The survey included random samples of 1000 Asian newlyweds, 1000Â Hispanic newlyweds, 1000 black newlyweds, and 1
> Use the figure, which shows the percentages of newlyweds in the United States who have a spouse of a different race or ethnicity. The survey included random samples of 1000 Asian newlyweds, 1000Â Hispanic newlyweds, 1000 black newlyweds, and 1
> Use the figure, which shows the percentages of newlyweds in the United States who have a spouse of a different race or ethnicity. The survey included random samples of 1000 Asian newlyweds, 1000Â Hispanic newlyweds, 1000 black newlyweds, and 1
> Use the figure, which shows the percentages of newlyweds in the United States who have a spouse of a different race or ethnicity. The survey included random samples of 1000 Asian newlyweds, 1000Â Hispanic newlyweds, 1000 black newlyweds, and 1
> a. identify the claim and state H0 and Ha, b. find the critical value(s) and identify the rejection region(s), c. find the standardized test statistic z, d. decide whether to reject or fail to reject the null hypothesis, and e. interpret the decision
> a. identify the claim and state H0 and Ha, b. find the critical value(s) and identify the rejection region(s), c. find the standardized test statistic z, d. decide whether to reject or fail to reject the null hypothesis, and e. interpret the decision
> a. identify the claim and state H0 and Ha, b. find the critical value(s) and identify the rejection region(s), c. find the standardized test statistic z, d. decide whether to reject or fail to reject the null hypothesis, and e. interpret the decision
> What conditions are necessary in order to use the z-test to test the difference between two population proportions?
> The contingency table shows how a random sample of adults rated a newly released movie and gender. At α = 0.05, can you conclude that the adults’ ratings are related to gender? Rating Gender Excellent Good Fair Роor Ma
> Test the claim about the mean of the differences for a population of paired data at the level of significance α. Assume the samples are random and dependent, and the populations are normally distributed. Claim: µd ≠ 0; α = 0.10. Sample statistics: d = -1
> Test the claim about the mean of the differences for a population of paired data at the level of significance α. Assume the samples are random and dependent, and the populations are normally distributed. Claim: µd ≥ 0; α = 0.01. Sample statistics: d = -2
> Test the claim about the mean of the differences for a population of paired data at the level of significance α. Assume the samples are random and dependent, and the populations are normally distributed. Claim: µd > 0; α = 0.05. Sample statistics: d = 0.
> Test the claim about the mean of the differences for a population of paired data at the level of significance α. Assume the samples are random and dependent, and the populations are normally distributed. Claim: µd ≤ 0; α = 0.10. Sample statistics: d = 6.
> Test the claim about the mean of the differences for a population of paired data at the level of significance α. Assume the samples are random and dependent, and the populations are normally distributed. Claim: µd = 0; α = 0.01. Sample statistics: d = 3.
