Atkins Weight Loss Program In a test of weight loss programs, 40 adults used the Atkins weight loss program. After 12 months, their mean weight loss was found to be 2.1 lb, with a standard deviation of 4.8 lb. Construct a 90% confidence interval estimate of the mean weight loss for all such subjects. Does the Atkins program appear to be effective? Does it appear to be practical?
Table of contents
- 1. Intro to Stats and Collecting Data55m
- 2. Describing Data with Tables and Graphs1h 55m
- 3. Describing Data Numerically1h 45m
- 4. Probability2h 16m
- 5. Binomial Distribution & Discrete Random Variables2h 33m
- 6. Normal Distribution and Continuous Random Variables1h 38m
- 7. Sampling Distributions & Confidence Intervals: Mean1h 53m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 12m
- 9. Hypothesis Testing for One Sample2h 19m
- 10. Hypothesis Testing for Two Samples3h 22m
- 11. Correlation1h 6m
- 12. Regression1h 4m
- 13. Chi-Square Tests & Goodness of Fit1h 20m
- 14. ANOVA1h 0m
7. Sampling Distributions & Confidence Intervals: Mean
Confidence Intervals for Population Mean
Problem 7.2.17
Textbook Question
Genes Samples of DNA are collected, and the four DNA bases of A, G, C, and T are coded as 1, 2, 3, and 4, respectively. The results are listed below. Construct a 95% confidence interval estimate of the mean. What is the practical use of the confidence interval?
2 2 1 4 3 3 3 3 4 1

1
Step 1: Calculate the sample mean (\( \bar{x} \)) of the given data. Add all the values in the dataset (2, 2, 1, 4, 3, 3, 3, 3, 4, 1) and divide by the total number of observations (n = 10). The formula is \( \bar{x} = \frac{\sum x_i}{n} \).
Step 2: Calculate the sample standard deviation (s). Use the formula \( s = \sqrt{\frac{\sum (x_i - \bar{x})^2}{n-1}} \), where \( x_i \) represents each data point, \( \bar{x} \) is the sample mean, and \( n \) is the sample size.
Step 3: Determine the critical value (t*) for a 95% confidence level. Since the sample size is small (n = 10), use the t-distribution table with degrees of freedom \( df = n - 1 \) (in this case, \( df = 9 \)). Look up the t-value corresponding to a 95% confidence level.
Step 4: Calculate the margin of error (ME) using the formula \( ME = t^* \cdot \frac{s}{\sqrt{n}} \), where \( t^* \) is the critical value, \( s \) is the sample standard deviation, and \( n \) is the sample size.
Step 5: Construct the confidence interval. The 95% confidence interval is given by \( \bar{x} \pm ME \), where \( \bar{x} \) is the sample mean and \( ME \) is the margin of error. Interpret the interval in the context of the problem, explaining that it provides a range of plausible values for the true mean of the DNA base codes.

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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Confidence Interval
A confidence interval is a range of values, derived from sample statistics, that is likely to contain the true population parameter with a specified level of confidence, typically 95%. It provides an estimate of uncertainty around the sample mean, indicating how much the sample mean might vary from the actual population mean.
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Sample Mean
The sample mean is the average of a set of values collected from a sample, calculated by summing all the sample values and dividing by the number of observations. It serves as a point estimate of the population mean and is crucial for constructing confidence intervals.
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Standard Deviation
Standard deviation is a measure of the amount of variation or dispersion in a set of values. In the context of confidence intervals, it helps quantify the variability of the sample data, which is essential for determining the width of the confidence interval and thus the precision of the estimate.
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