91Ó°ÊÓ

A seven-year medical research study reported that women whose mothers took the drug DES during pregnancy were twice as likely to develop tissue abnormalities that might lead to cancer as were women whose mothers did not take the drug. a. This study involved the comparison of two populations. What were the populations? b. Do you suppose the data were obtained in a survey or an experiment? c. For the population of women whose mothers took the drug DES during pregnancy, a sample of 3980 women showed 63 developed tissue abnormalities that might lead to cancer. Provide a descriptive statistic that could be used to estimate the number of women out of 1000 in this population who have tissue abnormalities. d. For the population of women whose mothers did not take the drug DES during pregnancy, what is the estimate of the number of women out of 1000 who would be expected to have tissue abnormalities? e. Medical studies often use a relatively large sample (in this case, 3980 ). Why?

Step by step solution

01

Identify the Populations

The problem discusses two groups: (1) women whose mothers took the drug DES during pregnancy and (2) women whose mothers did not take the drug DES during pregnancy. Therefore, the populations being compared are the daughters of these two groups of women.

02

Determine Data Collection Method

Given that the study is observing outcomes of past events (whether mothers took DES and the resulting health outcomes in daughters), it is likely that the data were collected through observational surveys rather than conducting a controlled experiment.

03

Calculate the Abnormality Rate for DES

For the group of women whose mothers took DES, 63 out of 3980 developed tissue abnormalities. To find the rate per 1000 women, we calculate: \( \frac{63}{3980} \times 1000 \approx 15.8 \). This means about 16 women out of 1000 in this group might develop tissue abnormalities.

04

Calculate for Non-DES Women

We know that the risk for women whose mothers took DES is twice that of women whose mothers did not take DES. Therefore, the rate for the non-DES group is half of 15.8, which is \( \frac{15.8}{2} \approx 7.9 \). Round off to about 8 women per 1000.

05

Reason for Large Sample Size

In medical studies, a large sample size like 3980 is used to ensure that the findings are statistically significant and can better reflect the true risk in the overall population. Larger samples reduce the impact of outliers and increase the reliability of statistical estimates.

Unlock Step-by-Step Solutions & Ace Your Exams!

• Full Textbook Solutions

  Get detailed explanations and key concepts

• Unlimited Al creation

  Al flashcards, explanations, exams and more...

• Ads-free access

  To over 500 millions flashcards

• Money-back guarantee

  We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with 91Ó°ÊÓ!

Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Population Comparison

When conducting a statistical analysis to compare two groups, it's important to accurately identify the populations being studied. In the given medical research study, the populations under comparison are:

• Women whose mothers took the drug DES during pregnancy.
• Women whose mothers did not take the drug DES during pregnancy.

The goal is to determine if there is a difference in the health outcomes of these two groups. In this case, the outcome of interest is the development of tissue abnormalities in the daughters of these women. Properly defining these populations helps ensure that the study results are relevant and can be generalized to similar groups.

Descriptive Statistics

Descriptive statistics provide a summary of data from a sample, offering a way to understand and share information about the population. In this study, we calculated a descriptive statistic to estimate the rate of tissue abnormalities for women whose mothers took DES. This was found to be approximately 16 women per 1000.
To obtain this, we used the formula:
\[ \text{Abnormality Rate} = \frac{63}{3980} \times 1000 \approx 15.8 \]
This descriptive statistic allows us to make evidence-based predictions about the prevalence of abnormalities in the broader DES-exposed daughter population based on the sample data. By converting raw numbers into a rate per 1000, it becomes easier to compare with other populations.

Observational Study

The data collection in this study was most likely based on an observational study rather than a controlled experiment. Observational studies observe subjects in their natural settings and often study events from the past, like whether mothers took DES during pregnancy.
These studies are essential when controlled experiments are impractical or unethical. For example, it would be unethical to expose new mothers to DES just for research purposes. Hence, researchers analyze existing data to observe the natural outcomes without intervening directly.
Although such studies can show associations, they do not establish causation, as many other uncontrolled factors could influence the results.

Sample Size Significance

The significance of sample size in a study is crucial for the accuracy and reliability of the results. In medical studies like the one discussed, large sample sizes, such as 3980, help ensure the conclusions drawn are statistically significant.
Larger samples provide:

• More precise estimates of population parameters by reducing sampling variability.
• Higher confidence in findings, as the results are less likely to be affected by anomalies or outliers.
• Increased power to detect any real effects or differences between groups being studied.

By using a large sample, the researchers aimed to mirror the diversity of the broader population more accurately, thus ensuring more generalizable and credible results.