Question

A researcher wishes to determine whether people with high blood pressure can reduce their blood pressure by following a particular diet. Subjects were randomly assigned to either a treatment group (the diet) or a control group (no diet). The mean blood pressure was determined for each group, and a 95% confidence interval for the difference in the means for the treatment group versus the control group, μt - μc, was found to be (-21, -6). The probability that the mean blood pressure for those on the diet is lower than for those not on the diet is 0.95. We are 95% confident that the average blood pressure of those who follow the diet is between 6 and 21 points higher than the average for those who do not follow the diet. We are 95% confident that the average blood pressure of those who follow the diet is between 6 and 21 points lower than the average for those who do not follow the diet. Since all of the values in the confidence interval are less than 0, we are unable to conclude that there is a difference in blood pressure for those who follow the diet and those who do not. A 95% confidence interval for a paired means difference is calculated for the difference in systolic blood pressure. The effect of a specific exercise treatment is subtracted from the baseline values for each subject; the interval is [-10.3, -19.9]. a. There is a 95% probability that blood pressure of the baseline group is at least 10.3 points less than the exercise treatment group. We would not reject the null hypothesis with a p-value of -19.9. We are 95% confident that the exercise treatment lowers average blood pressure by between 10.3 and 19.9 points. A high school coach uses a new technique in training middle distance runners. He records the times for 12 different athletes to run 800 meters before and after this training. A 95% confidence interval for the difference of the means before and after the training is determined to be (2.7, 4.2). Which method was used to obtain the interval? A confidence interval for matched pairs data. None of the above. The paired means test is a good option when: One wants to minimize the effect of lurking variables due to subjects. Two quantitative variables are studied for a relationship. Researchers wanted to compare the effectiveness of a water softener used with a filtering process to that of a water softener used without filtering. Ninety locations were randomly divided into two groups of equal size. Group A locations used a water softener and the filtering process, while group B used only the water softener. At the end of three months, water samples were tested at each location for softness level. (Water softness was measured on a scale of 1 to 5, with 5 being the softest water.) The results were as follows: Group A (water softener and filtering) x1 = 2.1 s1 = 0.7 Group B (water softener only) x2 = 1.7 s2 = 0.4 Using a 0.05 significance level, determine whether there is a difference between the two types of treatments. H0: μ1 - μ2 = 0 Ha: μ1 - μ2 ≠ 0 Test statistic t = 3.328, significance = 0.0014, DF = 69.97 Since the significance is less than 0.05, we are unable to reject the null hypothesis; there is insufficient evidence to conclude that there is a difference in the softness level achieved by the two processes. Since the significance is less than 0.05, we reject the null hypothesis and conclude that there is a difference in the softness level achieved by the two processes. Since the significance is less than 0.05, we accept the null hypothesis and conclude that there is no difference in the softness level achieved from the two processes. Since the significance is less than 0.05, we reject the alternative hypothesis and conclude that there is no significant difference in the softness level achieved by the two processes. A research group is interested in the effect of a specific exercise routine on managing the blood pressure of patients who have marginally high blood pressure. Each subject in the study will randomly be assigned to no change in habits and the specific exercise routine to determine the average difference in blood pressure. The most appropriate hypothesis test for this study is: a paired means test. The U.S. Department of Labor and Statistics wanted to compare the results of an unemployment program for the past two months in the U.S. Suppose the proportion of the unemployed two months ago is p2 and the proportion of the unemployed one month ago is p1. A study found a 99% confidence interval for p2 - p1 to be (-0.0012, 0.003). What conclusions can we draw about the unemployment percentage for the past two months? Since most of the values in the interval are positive, the unemployment program is statistically significant in lowering the unemployment rate. Since 0 is included in the interval, the unemployment program is statistically significant in lowering the unemployment rate over the past two months. Since 0 is included in the interval, the unemployment program was not shown to be statistically significant in lowering the unemployment rate for the past two months. Since the values in the interval are all close to 0, the unemployment program was not shown to be statistically significant in lowering the unemployment rate for the past two months.

Name: a researcher wishes to determine whether people with high blood pressure can reduce their blood pressure by following a particular diet subjects were randomly assigned to either a treatment 99769
Uploaded: 2023-02-06T21:28:06-08:00
Duration: 8 min 38 s
Channel: Ariana Nash
Description: a researcher wishes to determine whether people with high blood pressure can reduce their blood pressure by following a particular diet subjects were randomly assigned to either a treatment 99769

a. There is a 95% probability that blood pressure of the baseline group is at least 10.3 points less than the exercise treatment group.
We would not reject the null hypothesis with a p-value of -19.9.
We are 95% confident that the exercise treatment lowers average blood pressure by between 10.3 and 19.9 points.
A high school coach uses a new technique in training middle distance runners. He records the times for 12 different athletes to run 800 meters before and after this training. A 95% confidence interval for the difference of the means before and after the training is determined to be (2.7, 4.2). Which method was used to obtain the interval?
A confidence interval for matched pairs data.
None of the above.
The paired means test is a good option when:
One wants to minimize the effect of lurking variables due to subjects.
Two quantitative variables are studied for a relationship.
Researchers wanted to compare the effectiveness of a water softener used with a filtering process to that of a water softener used without filtering. Ninety locations were randomly divided into two groups of equal size. Group A locations used a water softener and the filtering process, while group B used only the water softener. At the end of three months, water samples were tested at each location for softness level. (Water softness was measured on a scale of 1 to 5, with 5 being the softest water.) The results were as follows:
Group A (water softener and filtering)
x1 = 2.1
s1 = 0.7
Group B (water softener only)
x2 = 1.7
s2 = 0.4
Using a 0.05 significance level, determine whether there is a difference between the two types of treatments.
H0: μ1 - μ2 = 0
Ha: μ1 - μ2 ≠ 0
Test statistic t = 3.328,
significance = 0.0014, DF = 69.97
Since the significance is less than 0.05, we are unable to reject the null hypothesis; there is insufficient evidence to conclude that there is a difference in the softness level achieved by the two processes.
Since the significance is less than 0.05, we reject the null hypothesis and conclude that there is a difference in the softness level achieved by the two processes.
Since the significance is less than 0.05, we accept the null hypothesis and conclude that there is no difference in the softness level achieved from the two processes.
Since the significance is less than 0.05, we reject the alternative hypothesis and conclude that there is no significant difference in the softness level achieved by the two processes.
A research group is interested in the effect of a specific exercise routine on managing the blood pressure of patients who have marginally high blood pressure. Each subject in the study will randomly be assigned to no change in habits and the specific exercise routine to determine the average difference in blood pressure. The most appropriate hypothesis test for this study is:
a paired means test.
The U.S. Department of Labor and Statistics wanted to compare the results of an unemployment program for the past two months in the U.S. Suppose the proportion of the unemployed two months ago is p2 and the proportion of the unemployed one month ago is p1. A study found a 99% confidence interval for p2 - p1 to be (-0.0012, 0.003). What conclusions can we draw about the unemployment percentage for the past two months?
Since most of the values in the interval are positive, the unemployment program is statistically significant in lowering the unemployment rate.
Since 0 is included in the interval, the unemployment program is statistically significant in lowering the unemployment rate over the past two months.
Since 0 is included in the interval, the unemployment program was not shown to be statistically significant in lowering the unemployment rate for the past two months.
Since the values in the interval are all close to 0, the unemployment program was not shown to be statistically significant in lowering the unemployment rate for the past two months.

Added by Danielle S.

Elementary Statistics a Step by Step Approach

Allan G. Bluman 9th Edition

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Solved by Expert Ariana Nash

02/06/2023

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The researcher's study on high blood pressure and diet: The 95% confidence interval for the difference in means is (-21, -6). This means that we are 95% confident that the average blood pressure of those who follow the diet is between 6 and 21 points lower than Show more…

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A researcher wishes to determine whether people with high blood pressure can reduce their blood pressure by following a particular diet. Subjects were randomly assigned to either a treatment group (the diet) or a control group (no diet). The mean blood pressure was determined for each group, and a 95% confidence interval for the difference in the means for the treatment group versus the control group, μt - μc, was found to be (-21, -6). The probability that the mean blood pressure for those on the diet is lower than for those not on the diet is 0.95. We are 95% confident that the average blood pressure of those who follow the diet is between 6 and 21 points higher than the average for those who do not follow the diet. We are 95% confident that the average blood pressure of those who follow the diet is between 6 and 21 points lower than the average for those who do not follow the diet. Since all of the values in the confidence interval are less than 0, we are unable to conclude that there is a difference in blood pressure for those who follow the diet and those who do not. A 95% confidence interval for a paired means difference is calculated for the difference in systolic blood pressure. The effect of a specific exercise treatment is subtracted from the baseline values for each subject; the interval is [-10.3, -19.9]. a. There is a 95% probability that blood pressure of the baseline group is at least 10.3 points less than the exercise treatment group. We would not reject the null hypothesis with a p-value of -19.9. We are 95% confident that the exercise treatment lowers average blood pressure by between 10.3 and 19.9 points. A high school coach uses a new technique in training middle distance runners. He records the times for 12 different athletes to run 800 meters before and after this training. A 95% confidence interval for the difference of the means before and after the training is determined to be (2.7, 4.2). Which method was used to obtain the interval? A confidence interval for matched pairs data. None of the above. The paired means test is a good option when: One wants to minimize the effect of lurking variables due to subjects. Two quantitative variables are studied for a relationship. Researchers wanted to compare the effectiveness of a water softener used with a filtering process to that of a water softener used without filtering. Ninety locations were randomly divided into two groups of equal size. Group A locations used a water softener and the filtering process, while group B used only the water softener. At the end of three months, water samples were tested at each location for softness level. (Water softness was measured on a scale of 1 to 5, with 5 being the softest water.) The results were as follows: Group A (water softener and filtering) x1 = 2.1 s1 = 0.7 Group B (water softener only) x2 = 1.7 s2 = 0.4 Using a 0.05 significance level, determine whether there is a difference between the two types of treatments. H0: μ1 - μ2 = 0 Ha: μ1 - μ2 ≠ 0 Test statistic t = 3.328, significance = 0.0014, DF = 69.97 Since the significance is less than 0.05, we are unable to reject the null hypothesis; there is insufficient evidence to conclude that there is a difference in the softness level achieved by the two processes. Since the significance is less than 0.05, we reject the null hypothesis and conclude that there is a difference in the softness level achieved by the two processes. Since the significance is less than 0.05, we accept the null hypothesis and conclude that there is no difference in the softness level achieved from the two processes. Since the significance is less than 0.05, we reject the alternative hypothesis and conclude that there is no significant difference in the softness level achieved by the two processes. A research group is interested in the effect of a specific exercise routine on managing the blood pressure of patients who have marginally high blood pressure. Each subject in the study will randomly be assigned to no change in habits and the specific exercise routine to determine the average difference in blood pressure. The most appropriate hypothesis test for this study is: a paired means test. The U.S. Department of Labor and Statistics wanted to compare the results of an unemployment program for the past two months in the U.S. Suppose the proportion of the unemployed two months ago is p2 and the proportion of the unemployed one month ago is p1. A study found a 99% confidence interval for p2 - p1 to be (-0.0012, 0.003). What conclusions can we draw about the unemployment percentage for the past two months? Since most of the values in the interval are positive, the unemployment program is statistically significant in lowering the unemployment rate. Since 0 is included in the interval, the unemployment program is statistically significant in lowering the unemployment rate over the past two months. Since 0 is included in the interval, the unemployment program was not shown to be statistically significant in lowering the unemployment rate for the past two months. Since the values in the interval are all close to 0, the unemployment program was not shown to be statistically significant in lowering the unemployment rate for the past two months.