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Statistics, section 2, Fall 2019
My Assignments

Rosner, Fundamentals of Biostatistics 8/e (Homework)

James Finch

Statistics, section 2, Fall 2019

Instructor: Dr. Friendly

Current Score : 18 / 155

Due : Sunday, January 27, 2030 23:30 EST

Last Saved : n/a Saving... ()

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Question

Points

1	2	3	4	5	6	7	8	9	10
7/13	5/33	0/3	3/4	0/13	3/4	–/19	–/19	–/29	–/18

Total

18/155 (11.6%)

Instructions

Fundamentals of Biostatistics, 8th edition, by Bernard Rosner, published by Cengage Learning, is a practical introduction to the methods, techniques, and computation of statistics with human subjects. It prepares students for their future courses and careers by introducing the statistical methods most often used in medical literature. Rosner minimizes the amount of mathematical formulation (algebra-based) while still giving complete explanations of all the important concepts. As in previous editions, a major strength of this book is that every new concept is developed systematically through completely worked out examples from current medical research problems. Most methods are illustrated with specific instructions as to implementation using software either from SAS, Stata, R, Excel or Minitab. In addition, WebAssign questions integrated with the new Statistical Analysis and Learning Tool (SALT) help turn students into statistical thinkers.

These questions show a variety of question types in WebAssign for use with this title.

Question 1 asks students to use SALT to find summary statistics for a given dataset, use them to describe the dataset, and then apply scaling to some of the summary statistics.

Question 2 asks students to use SALT to find summary statistics for five variables, draw a histogram, a boxplot, a bar chart to display the data, and draw conclusions based on the graphs.

Question 3 asks students to use SALT to find normal probabilities for a normally distributed random variable.

Question 4 asks students to use SALT to create and interpret a 95% Confidence Interval for a proportion.

Question 5 asks students to complete the steps for two one proportion z-tests and consider the power of the tests.

Question 6 is a video introduction to testing the difference between two means or proportions. There are 24 such videos available.

Question 7 is a Stats in Practice Question that demonstrates the use of videos displayed within a question, followed by multiple-choice and discussion questions in a unique two-part accordion-style type of display.

Question 8 is a SALT tutorial showing how to estimate the difference of two independent means.

Question 9 provides students three topic choices to practice estimating the difference of two independent means.

Question 10 is an example of a Statistical Lab. There are versions that support Excel, Minitab, SPSS, R, JMP, or TI83/84 calculator.

Question 11 highlights Milestone 1, the first step in presenting and tracking Project Milestones for a statistical research project. This demo assignment allows many submissions and allows you to try another version of the same question for practice wherever the problem has randomized values.

The answer key and solutions will display after the first submission for demonstration purposes. Instructors can configure these to display after the due date or after a specified number of submissions.

Assignment Submission

For this assignment, you submit answers by question parts. The number of submissions remaining for each question part only changes if you submit or change the answer.

Assignment Scoring

Your last submission is used for your score.

1. 7/13 points | Previous Answers RosBioStat8 2.E.001-007. My Notes

Infectious Disease

The data in the given dataset are a sample from a larger data set collected on people discharged from a selected Pennsylvania hospital as part of a retrospective chart review of antibiotic usage in hospitals. The data can be found in SALT through the link below.

A button hyperlink to the SALT program that reads: Use SALT.

(a)

Compute the mean duration of hospitalization (in days) for the 25 patients.

days

Compute the median duration of hospitalization (in days) for the 25 patients.

days

(b)

Compute the standard deviation for the duration of hospitalization (in days) for the 25 patients. (Round your answer to four decimal places.)

days

Compute the range for the duration of hospitalization (in days) for the 25 patients.

days

(c)

It is of clinical interest to know if the duration of hospitalization is affected by whether a patient has received antibiotics. Answer this question descriptively using numeric methods. (Enter your answers in days. Round your answers to four decimal places.)

For patients who received antibiotics, the mean duration of hospitalization was days. For patients who did not receive antibiotics, the mean duration of hospitalization was days. However, there appears to be an outlier in the group of patients who antibiotics. After removing the outlier, the mean duration of hospitalization for this group is days, so the mean durations of the two groups appear .

Suppose the scale for a data set is changed by multiplying each observation by a positive constant.

(d)

What is the effect on the median? (Use c for the constant and med for the old median.)

new median =

c·med

(e)

What is the effect on the mode? (Use c for the constant and m for the old mode.)

new mode =

m+c

(f)

What is the effect on the geometric mean? (Use c for the constant and g for the old geometric mean.)

new geometric mean =

m+c

(g)

What is the effect on the range? (Use c for the constant and r for the old range.)

new range =

r

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2. 5/33 points | Previous Answers RosBioStat8 2.E.023-025.S. My Notes

Question Part

Points

Submissions Used

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1/1

0/1

1/1

0/1

1/1

0/1

1/1

0/1

1/1

2/100

1/100

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1/100

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Pulmonary Disease

Forced expiratory volume (FEV) is an index of pulmonary function that measures the volume of air expelled after 1 second of constant effort. The data set obtainable using SALT contains determinations of FEV on 654 children ages 3 through 19 who were seen in a child respiratory disease study. These data are part of a longitudinal study to follow the change in pulmonary function over time in children.

(a)

For each variable (other than ID), obtain appropriate descriptive statistics (both numeric and graphic).

Complete the table below by calculating the means, medians, and standard deviations for each of the variables. (Round your means and standard deviations to four decimal places.)

	Age (years)	FEV (liters)	Hgt (inches)
Mean
Median
Standard Deviation

Complete the table below by calculating the sample proportion of female children and male children in the study. (Round your answers to four decimal places.)

Female	Male

Complete the table below by calculating the sample proportion of noncurrent smokers and current smokers in the study. (Round your answers to four decimal places.)

Noncurrent Smoker	Current Smoker

Construct a histogram for the variable age.

A histogram graph has a horizontal axis labeled "Age" with values from 2.5 to 19.5 and a vertical axis labeled "Count" with values from 0 to 100. The histogram graph has 17 bars of equal width. Each bar is associated with an interval and an approximate value as listed below.
2.5 to 3.5: 94

3.5 to 4.5: 90

4.5 to 5.5: 85

5.5 to 6.5: 81

6.5 to 7.5: 57

7.5 to 8.5: 54

8.5 to 9.5: 43

9.5 to 10.5: 37

10.5 to 11.5: 28

11.5 to 12.5: 25

12.5 to 13.5: 19

13.5 to 14.5: 13

14.5 to 15.5: 9

15.5 to 16.5: 8

16.5 to 17.5: 6

17.5 to 18.5: 3

18.5 to 19.5: 2

Construct a boxplot for the variable FEV.

The box-and-whisker plot has a vertical axis numbered from 2 to 8. The box-and-whisker is also vertical. The bottom whisker is approximately 2.271, the bottom edge of the box is approximately 3.479, the line inside the box is approximately 4.0445, the top edge of the box is approximately 4.617, and the top whisker is approximately 6.321. There are 9 dots located at: 6.362; 6.714; 6.397; 6.573; 6.582; 7.273; 7.123; 7.118; 6.362.

The box-and-whisker plot has a vertical axis numbered from 0 to 6. The box-and-whisker is also vertical. The bottom whisker is approximately 0.771, the bottom edge of the box is approximately 1.979, the line inside the box is approximately 2.5445, the top edge of the box is approximately 3.117, and the top whisker is approximately 4.821. There are 9 dots located at: 4.862; 5.214; 4.897; 5.073; 5.082; 5.773; 5.623; 5.618; 4.862.

The box-and-whisker plot has a vertical axis numbered from 4 to 10. The box-and-whisker is also vertical. The bottom whisker is approximately 4.271, the bottom edge of the box is approximately 5.479, the line inside the box is approximately 6.0445, the top edge of the box is approximately 6.617, and the top whisker is approximately 8.321. There are 9 dots located at: 8.362; 8.714; 8.397; 8.573; 8.582; 9.273; 9.123; 9.118; 8.362.

The box-and-whisker plot has a vertical axis numbered from 1 to 7. The box-and-whisker is also vertical. The bottom whisker is approximately 1.271, the bottom edge of the box is approximately 2.479, the line inside the box is approximately 3.0445, the top edge of the box is approximately 3.617, and the top whisker is approximately 5.321. There are 9 dots located at: 5.362; 5.714; 5.397; 5.573; 5.582; 6.273; 6.123; 6.118; 5.362.

Construct a boxplot for the variable Hgt.

The box-and-whisker plot has a vertical axis numbered from 70 to 100. The box-and-whisker is also vertical. The bottom whisker is approximately 70.99, the bottom edge of the box is approximately 82.02, the line inside the box is approximately 86.49, the top edge of the box is approximately 90.48, and the top whisker is approximately 99.02.

The box-and-whisker plot has a vertical axis numbered from 40 to 70. The box-and-whisker is also vertical. The bottom whisker is approximately 40.99, the bottom edge of the box is approximately 52.02, the line inside the box is approximately 56.49, the top edge of the box is approximately 60.48, and the top whisker is approximately 69.02.

The box-and-whisker plot has a vertical axis numbered from 30 to 60. The box-and-whisker is also vertical. The bottom whisker is approximately 30.99, the bottom edge of the box is approximately 42.02, the line inside the box is approximately 46.49, the top edge of the box is approximately 50.48, and the top whisker is approximately 59.02.

The box-and-whisker plot has a vertical axis numbered from 45 to 75. The box-and-whisker is also vertical. The bottom whisker is approximately 45.99, the bottom edge of the box is approximately 57.02, the line inside the box is approximately 61.49, the top edge of the box is approximately 65.48, and the top whisker is approximately 74.02.

Construct a bar chart for the variable Sex.

A bar graph has a horizontal axis labeled "Sex" and a vertical axis labeled "Count" with values from 0 to 500. The bar graph has 2 bars. Each bar is associated with a label and an approximate value as listed below.
female: 336

male: 318

Construct a bar chart for the variable smoke.

A bar graph has a horizontal axis labeled "Smoke" and a vertical axis labeled "Count" with values from 0 to 700. The bar graph has 2 bars. Each bar is associated with a label and an approximate value as listed below.
noncurrent smoker: 564

current smoker: 90

(b)

Use both numeric and graphic measures to assess the relationship of FEV to age, height, and smoking status. (Do this separately for boys and girls. Round your answers to four decimal places.)

Among female children we find that FEV . Among female children who smoke the average FEV was found to be with a standard deviation of . Among female children who do not smoke the average FEV was found to be approximately with a standard deviation of . This seems to suggest that, among female children in the sample, those who do not smoke have a FEV than female children who smoke.

Among male children we find that FEV . Among male children who smoke the average FEV was found to be with a standard deviation of . Among male children who do not smoke the average FEV was found to be approximately with a standard deviation of . This seems to suggest that, among male children in the sample, those who do not smoke have a FEV than male children who smoke.

(c)

Compare the pattern of growth of FEV by age for boys and girls. Are there any similarities? Any differences?

Comparing the results we find that the trend . We also find that the variability is . Finally, we see that the trend begins to flatten out at .

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3. 0/3 points | Previous Answers RosBioStat8 5.E.014-016.S. My Notes

Cardiovascular Disease

Serum cholesterol is an important risk factor for coronary disease. We can show that serum cholesterol is approximately normally distributed, with mean = 221 mg/dL and standard deviation = 59 mg/dL.

(a)

If the clinically desirable range for cholesterol is < 200 mg/dL, what proportion of people have clinically desirable levels of cholesterol? (Round your answer to four decimal places.)

0.3609

(b)

Some investigators believe that only cholesterol levels over 250 mg/dL indicate a high-enough risk for heart disease to warrant treatment. What proportion of the population does this group represent? (Round your answer to four decimal places.)

0.3115

(c)

What proportion of the general population has borderline high-cholesterol levels—that is, > 200 but < 250 mg/dL? (Round your answer to four decimal places.)

0.3275

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4. 3/4 points | Previous Answers RosBioStat8 6.E.027-029.S. My Notes

Sexually Transmitted Disease

Suppose a clinical trial is conducted to test the efficacy of a new drug, spectinomycin, for treating gonorrhea in females. Fifty-six patients are given a 4-g daily dose of the drug and are seen 1 week later, at which time 7 of the patients still have gonorrhea.

(a)

What is the best point estimate for p, the probability of a failure with the drug?

p̂ =

0.125

(b)

What is a 95% CI for p? (Enter your answer using interval notation. Round your numerical values to three decimal places.)

0.119

$webMathematica generated answer key$

(c)

Suppose we know penicillin G at a daily dose of 4.8 megaunits has a 10% failure rate. What can be said in comparing the two drugs?

Since the 10% failure rate for penicillin is

within

the bounds of the 95% CI, we can conclude that it is plausible that spectinomycin is

equally

effective than penicillin G.

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5. 0/13 points | Previous Answers RosBioStat8 7.E.012-016. My Notes

Cardiovascular Disease

Suppose the incidence rate of myocardial infarction (MI) was 4 per 1,000 among 45- to 54-year-old men in 2000. To look at changes in incidence over time, 4,400 men in this age group were followed for 1 year starting in 2010. Fifteen new cases of MI were found.

You can use the Distribution Calculators page in SALT to find critical values and/or p -values to answer parts of this question. Please note that the Inferential Statistics page does not use the continuity-corrected version of the test statistic.

(a)

Using the critical-value method with α = 0.05, test the hypothesis that incidence rates of MI changed from 2000 to 2010.

State the null and alternative hypotheses. State the null and alternative hypotheses. (Enter != for ≠ as needed.)

H₀:

H₁:

What is the test statistic? (Round your answer to two decimal places.)

What is the critical value? (Round your answer to two decimal places.)

What conclusions can we draw from these results?

Reject H₀; based on the results we find that there is insufficient evidence to conclude that incidence rates of MI changed from 2000 to 2010. Reject H₀; based on the results we find that there is sufficient evidence to conclude that incidence rates of MI changed from 2000 to 2010. Fail to reject H₀; based on the results we find that there is insufficient evidence to conclude that incidence rates of MI changed from 2000 to 2010. Fail to reject H₀; based on the results we find that there is sufficient evidence to conclude that incidence rates of MI changed from 2000 to 2010.

(b)

Use technology to report a p-value to correspond to your answer to part (a). (Round your answer to four decimal places.)

p-value =

(c)

Suppose that 24% of patients with MI in 2000 died within 24 hours. This proportion is called the 24-hour case-fatality rate. Of the 15 new MI cases in the preceding study, 5 died within 24 hours. Test whether the 24-hour case-fatality rate changed from 2000 to 2010. (Use α = 0.05.)

State the null and alternative hypotheses. State the null and alternative hypotheses. (Enter != for ≠ as needed.)

H₀:

H|lθ|

H₁:

What is the test statistic? (If the test does not have a defined test statistic, enter DNE. Round your answer to two decimal places.)

Use technology to find the p-value. (Round your answer to four decimal places.)

p-value =

What conclusions can we draw from these results?

Reject H₀; based on the results we find that there is insufficient evidence to conclude that the 24-hour case-fatality rate changed from 2000 to 2010. Fail to reject H₀; based on the results we find that there is insufficient evidence to conclude that the 24-hour case-fatality rate changed from 2000 to 2010. Fail to reject H₀; based on the results we find that there is sufficient evidence to conclude that the 24-hour case-fatality rate changed from 2000 to 2010. Reject H₀; based on the results we find that there is sufficient evidence to conclude that the 24-hour case-fatality rate changed from 2000 to 2010.

(d)

Suppose we eventually plan to accumulate 55 MI cases during the period 2010–2015. Assume that the 24-hour case-fatality rate is truly 20% during this period. How much power would such a study have in distinguishing between case-fatality rates in 2000 and 2010–2015 if a two-sided test with significance level 0.05 is planned? (Round your answer to four decimal places.)

(e)

How large a sample is needed in part (d) to achieve 90% power? (Round your answer up to the next whole number.)

MI cases

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6. 3/4 points | Previous Answers RosBioStat8 12.CE.001.SIP. My Notes

7. –/19 points RosBioStat8 8.E.ST.001.S. My Notes

Question Part

Points

Submissions Used

–/1

0/100

Total

–/19

The following exercise will guide you through how to use SALT to obtain a confidence interval to estimate the mean difference in two independent sample means.

Part 1 of 5

Calcium is the most abundant mineral in the body, and it is one of the most important nutrients for bone health. Unfortunately, individuals over the age of 65 are especially vulnerable to calcium deficiency—largely due to changes in the body from advancing age. A random sample of 176 elderly patient records in the United States were reviewed and data on the results of a laboratory analysis of calcium was recorded for further study. The age and sex of each patient was also recorded.

Researchers are hoping to determine an estimate of the actual difference in mean calcium levels in biological males and biological females over the age of 65 years. We will create a 98% confidence interval to estimate the difference in these two population means.

The first five rows of data look like this.

Sex	Calcium (mmol per L)
Female	2.53
Female	2.5
Female	2.43
Female	2.48
Female	2.33

Import the dataset into SALT for analyzing.

We will use SALT to summarize the data and fill in the table.

Sex	Sample Size	Mean Calcium (mmol per L)	Standard deviation
Male
Female

How many patients are biologically Male and how many are biologically Female?

Click on the "Descriptive Statistics" tab along the top menu bar.

The top menu bar of SALT is shown. The tab labeled "Descriptive Statistics" is highlighted and has an arrow pointing to it.

Locate the "Summary Table" for "Categorical Variables" and read this table.

The text "Summary Table" is shown. Below this text is a square symbol containing the letters A and Z followed by the text "Categorical Variables."

Enter the sample sizes, number of observations in SALT, for these two groups in the table.

Sex	Sample Size	Mean Calcium (mmol per L)	Standard deviation
Male	(No Response) 91
Female	(No Response) 85

Part 2 of 5

For SALT to calculate the mean calcium (mmol per L) level for each Sex group, the data needs to be grouped by Sex status. We will do this on the "Charts and Graphs" page by creating a histogram of the Calcium for each group.

Click on the "Charts and Graphs" tab along the top menu bar.

The top menu bar of SALT is shown. The tab labeled "Charts and Graphs" is highlighted and has an arrow pointing to it.

There are several types of charts and graphs SALT can draw; these are listed below the top menu bar on the "Charts and Graphs" page. Histogram is the default choice, and this is the type of graph we will create.

In the Settings menu on the left of the screen, select "Calcium (mmol per L)" in the "Variable to graph" menu and "Sex" in the "Grouping Variable" menu.

A menu labeled "Settings" is shown. The menu contains two drop-down menus labeled "Variable to Graph" and "Grouping Variable." Both drop-down lists show the text "Select a Variable" by default.

These selections will result in SALT drawing a histogram of the calcium level of patients whose sex is male and a histogram of the calcium level of patients whose sex is female.

Scroll further down the page to see the Summary Table below the graphs. Here is where SALT displays the sample mean calcium (mmol per L) levels and standard deviation for the two groups.

Enter the mean calcium (mmol per L) level and standard deviation for these two groups in the table, rounded to three decimal places.

Sex	Sample Size	Mean Calcium (mmol per L)	Standard deviation
Male	91	(No Response) 2.324	(No Response) 0.123
Female	85	(No Response) 2.389	(No Response) 0.143

Part 3 of 5

We need to verify the assumptions for using the two-sample t confidence interval for a difference in population means before estimating the difference in these population means.

First, the two samples must be independent and randomly selected. The data were recorded after reviewing a random sample of 176 elderly patient records in the United States. This indicates that the first assumption (No Response)

has been

met.

Second, the sample sizes generally should be 30 or larger. We have 91 patients whose sex is male and 85 patients whose sex is female. This indicates that the second assumption (No Response)

has been

met.

Part 4 of 5

Because both assumptions have been met, we can compute a 98% confidence interval for the difference in population means to estimate the true difference in mean calcium levels for biological males over 65 years and biological females over 65 years.

Define the population characteristics of interest as follows.

μ₁ = mean Calcium (mmol per L) for biological males over age 65
μ₂ = mean Calcium (mmol per L) for biological females over age 65
μ₁ − μ₂ = difference in mean Calcium (mmol per L) for these populations

Recall our summary statistics.

Sex	Sample Size	Mean Calcium (mmol per L)	Standard deviation
Male	91	2.324	0.123
Female	85	2.389	0.143

In SALT, click on the "Inferential Statistics" page.

The top menu bar of SALT is shown. The tab labeled "Inferential Statistics" is highlighted and has an arrow pointing to it.

Select the "Two Sample t" procedure in the "Procedure Selection" menu.

A menu labeled "Settings" is shown. This menu contains a drop-down menu labeled "Procedure Selection," with an arrow pointing to it. The option "Two Sample t" is selected in the drop-down menu and another arrow points to this option.

Enter the summary statistics for each group in the input boxes on the left panel. Remember that biological males over 65 are defined as group 1, "Sample Variable #1," and biological females over 65 are defined as group 2, "Sample Variable #2."

Two menus labeled "Sample Variable #1" and "Sample Variable #2" are shown. Each menu contains three text entry boxes labeled "Sample Mean," "Sample St. Dev.," and "Sample Size." The default values for the text entry boxes are 0, 1, and 10 respectively.

With the radio button next the Confidence Interval marked, enter the given confidence level of 98 in the input box.

Two radio buttons labeled "Hypothesis Test" and "Confidence Interval" are shown, with "Confidence Interval" selected. Below the radio buttons, a text entry box labeled "Confidence Interval" is shown with a default value of 95 entered into it. A percent sign follows the text entry box. Below the text entry box, there is an unchecked check box labeled "Assume Equal Variances" and "Leave unchecked if you are unsure." Below the check box, there are two buttons labeled "Generate Results" and "Reset."

After clicking the Generate Results button, SALT will display the Two Sample t Confidence Interval Summary on the right side of the Inferential Statistics page.

Enter the requested values below, rounded to three decimal places as needed.

Difference of Means: (No Response)

-0.065

Lower Limit: (No Response)

-0.112

Upper Limit: (No Response)

-0.017

Degrees of Freedom: (No Response)

166.125

Standard Error: (No Response)

0.020

Part 5 of 5

Our estimate of the true difference in mean calcium levels for biological males over the age of 65 and biological females over the age of 65 is

(−0.112, −0.017).

Provide an interpretation of this confidence interval, worded in the context of this scenario.

You can be 98% confident that the actual difference in mean calcium (mmol per L) levels is between a lower limit of (No Response)

-0.112

and an upper limit of (No Response)

-0.017

. The endpoints of this interval (No Response)

are both negative

and zero (No Response)

is not

part of the interval. Therefore, you can estimate that the mean calcium levels (mmol per L) for biological males over 65 is (No Response)

less

than the mean calcium levels (mmol per L) for biological females over 65.

The method used to construct this interval estimate is successful in capturing the actual difference in population means about (No Response)

% of the time.

You have now completed the SALT Tutorial.

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8. –/19 points RosBioStat8 8.E.SYS.001.S. My Notes

Question Part

Points

Submissions Used

–/1

0/100

Total

–/19

Instructions

Select Your Scenario:

This problem contains data for 3 different scenarios: Consumer Research, Transportation, and Health Care.

Read the scenarios, and once finished, you will be asked to select which scenario you would like to be assessed on.

You will not be asked to answer questions for the other 2 scenarios.

Consumer Research

Young Business magazine recently polled a random sample of 410 of their subscribers and asked, among other things, age and whether the subscriber has purchased real estate. The results will be used to help the magazine choose articles of interest and provide advertisers with a profile of subscribers.

Researchers are hoping to determine an estimate of the actual difference in mean age in subscribers who have purchased real estate and subscribers who have not. We will create a 90% confidence interval to estimate the difference in these two population means.

The first five rows of data look like this.

Age	Real Estate Purchases
38	No
30	No
41	No
28	Yes
31	Yes

Define group 1 to be subscribers who have not purchased real estate and group 2 to be subscribers who have purchased real estate.

Transportation

How has a car's fuel efficiency changed over time? Can cars drive further on a gallon of gasoline than they did in the early 1990's? A random sample of 329 Cars that were new in either 1993 or 2004 was collected and their city miles per gallon (MPG) was recorded.

Researchers are hoping to determine an estimate of the actual difference in mean city MPG for cars in 1993 and the mean city MPG for cars in 2004. We will create a 95% confidence interval to estimate the difference in these two population means.

The first five rows of data look like this.

City MPG	Highway MPG	Year
25	31	A
18	25	A
20	26	A
19	26	A
22	30	A

Define group 1 to be new cars in 1993 (denoted by A) and group 2 to be new cars in 2004 (denoted by B).

Health Care

Colorectal surgery is associated with a high rate of surgical site infection (SSI). Complications arising from SSI significantly increase an individual's length of hospital stay, reduce quality of life, and can also lead to additional health care needs. Outcomes of 2,919 colorectal surgeries were collected for research, including the patient's Body Mass Index (BMI) and whether an individual developed a surgical site infection. Medical researchers would like to use this sample data to learn about health outcomes for colorectal surgery.

Researchers are hoping to determine an estimate of the actual difference in mean BMI in patients who do not develop SSI and the mean BMI in patients who do. We will create a 99% confidence interval to estimate the difference in these two population means.

The first five rows of data look like this.

BMI	SSI
24.3	NotDevelop
20.3	NotDevelop
21.6	NotDevelop
22.3	NotDevelop
16	NotDevelop

Define group 1 to be patients who did not develop SSI and group 2 to be patients who did develop SSI.

Click the link below to begin the question by choosing a topic.

Pick your topic.

Choose the topic on which you would like to be assessed. Once you select your scenario, you cannot change your topic.

Consumer Research Transportation Health Care

Note: If you select Skip, you will be assessed on the Consumer Research topic.

Question

Instructions

Select Your Scenario:

First, select the tab that corresponds to the topic you chose above.

Note: Click the SALT button in the tab corresponding to the topic you chose.

Consumer Research

The first five rows of data look like this.

Age	Real Estate Purchases
38	No
30	No
41	No
28	Yes
31	Yes

Define group 1 to be subscribers who have not purchased real estate and group 2 to be subscribers who have purchased real estate.

Import the dataset into SALT for analyzing.

Transportation

The first five rows of data look like this.

City MPG	Highway MPG	Year
25	31	A
18	25	A
20	26	A
19	26	A
22	30	A

Define group 1 to be new cars in 1993 (denoted by A) and group 2 to be new cars in 2004 (denoted by B).

Import the dataset into SALT for analyzing.

Health Care

The first five rows of data look like this.

BMI	SSI
24.3	NotDevelop
20.3	NotDevelop
21.6	NotDevelop
22.3	NotDevelop
16	NotDevelop

Define group 1 to be patients who did not develop SSI and group 2 to be patients who did develop SSI.

Import the dataset into SALT for analyzing.

After you have clicked the tab for your selected topic and read the problem, answer the questions below.

(a)

Use SALT to summarize the data. Enter the sample size, mean, and standard deviation for these two groups in the table, rounded to three decimal places.

Grouping Variable	Sample Size	Mean	Standard deviation
Group 1	(No Response) 229	(No Response) 30.031	(No Response) 4.079
Group 2	(No Response) 181	(No Response) 30.215	(No Response) 3.963

(b)

We need to verify the assumptions for using the two-sample t confidence interval for a difference in population means before estimating the difference in these population means.

The first assumption states that the two samples must be independently and randomly selected from the populations of interest or a representative sample from the population. Another way to think of this first assumption is that independent individuals or objects must be randomly assigned to treatments.

Based on what you know about how this sample was collected, the two samples (No Response)

are

independent random samples from the populations of interest.

The second assumption requires the sample to be large enough to be reasonably sure that the sampling distribution will be at least approximately normal.

Based on the two sample sizes, the second assumption (No Response)

has been

met.

(c)

Recall how each group was defined. The population mean for group 1 and for group 2 will be defined as follows.

μ₁ = Mean of Group 1
μ₂ = Mean of Group 2
μ₁ − μ₂ = Difference in means for these populations

Use SALT to compute the confidence interval at the desired level.

Enter the requested values below, rounded to three decimal places as needed.

Difference of means: (No Response)

-0.185

Lower Limit: (No Response)

-0.843

Upper Limit: (No Response)

0.473

Degrees of Freedom: (No Response)

391.135

Standard Error: (No Response)

0.399

(d)

Provide an interpretation of the confidence interval.

You can be (No Response)

% confident that the actual difference in population means is within the computed interval. The endpoints of this interval (No Response)

have different signs

and zero (No Response)

part of the interval. Therefore, you can estimate that the mean for group 1 is (No Response)

no different

than the mean for group 2.

The method used to construct this interval estimate is successful in capturing the actual difference in population means about (No Response)

% of the time.

You have now completed the question.

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9. –/29 points RosBioStat8 8.Lab.003.Minitab. My Notes

10. –/18 points RosBioStat8 PJT.1.001. My Notes

Question Part

Points

Submissions Used

–/1

0/100

Total

–/18

Milestone 1: Research Design

Question 1

What is your research question?

Your research question should be based on a topic that interests you and that you can reasonably obtain data for. Try to make your research question as specific as possible. Form a research question about a population that you will be able to sample. Some examples of research questions are: "Are students at my college able to taste the difference between regular coffee and decaffeinated coffee?", "Does the GPA, age, and number of credits needed for graduation for juniors at my university differ between transfer students and non-transfer students?", "Have the new water rates in my water district changed residents' water usage habits?", and "Do recent graduates from the business department at my university get larger starting salaries on average if they have participated in a summer internship?"

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Question 2

Has any research already been done that might help with your project?

You can search your university's online database to find articles that discuss research that has already been done on your research question. Please make note of any articles or other sources that helped guide your research question and research design. You will be asked to provide references to any sources you used.

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Question 3

What is your population of interest?

Your population of interest will be closely related to your research question. For instance, if you are testing the freshman 15 theory and you believe that students at your college do not gain 15 pounds on average over the course of freshman year, then your population of interest is the students at your college who have completed freshman year.

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Question 4

Describe your sampling plan.

You want to ensure that your sample is representative of the population of interest. How will you target your population of interest? Sampling involves tradeoffs; you may have to settle for a convenience sample, which is fine for this project as long as you acknowledge this. Sampling is about doing the best you can with the resources you have at your disposal.

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Question 5

Will this sample be representative of the population of interest? If so, why? If not, what population will the sample be representative of?

Is there any group of people within the population of interest that your sampling plan is likely to miss? For instance, if you are using a random sample of landline telephone numbers from your state in order to achieve a random sample of residents in your state, then you are missing all of the residents of your state who only have a cell phone and do not have a landline. Or, if your population of interest is all adults in your country, but you only conduct interview of adults from your local community, then your sample is only representative of the adults in your local community.

This answer has not been graded yet.

Question 6

What variables will you measure?

Make sure that the variables you choose are measurable. If you are performing an experiment where you are comparing two skin creams to determine which gives the skin a more youthful glow, how exactly will you measure "youthful glow"? Are there other variables that you will collect because they too may be of interest? Age? Gender? Level of education? Is your variable type numeric or categorical? If your variable type is numeric, is it discrete or continuous? Do your variables need to be measured using special equipment?

Variable	Type	How will you measure it?
		This answer has not been graded yet.
		This answer has not been graded yet.
		This answer has not been graded yet.
		This answer has not been graded yet.

Question 7

Describe your study design.

Will you be conducting an observational study or performing an experiment? What will your sample size be? If you will be performing an experiment, will there be a placebo? If so, describe the placebo. Will the experiment be blinded? Double-blinded? Who will carry out the experiment and how?

This answer has not been graded yet.

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Rosner, Fundamentals of Biostatistics 8/e (Homework)

Current Score : 18 / 155

Due : Sunday, January 27, 2030 23:30 EST

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Instructions

Assignment Submission

Assignment Scoring

Infectious Disease

Pulmonary Disease

Cardiovascular Disease

Sexually Transmitted Disease

Cardiovascular Disease

Stats in Practice: ANOVA

Part I - Multiple Choice Questions

Part II - Discussion Question

Statistical Lab

Background

Guidelines

About the Data

Tech Guide

Lab Questions

References

Milestone 1: Research Design

Question 1

Question 2

Question 3

Question 4

Question 5

Question 6

Question 7