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 3m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 12m
- 9. Hypothesis Testing for One Sample1h 1m
- 10. Hypothesis Testing for Two Samples2h 8m
- 11. Correlation48m
- 12. Regression1h 4m
- 13. Chi-Square Tests & Goodness of Fit1h 20m
- 14. ANOVA1h 0m
8. Sampling Distributions & Confidence Intervals: Proportion
Sampling Distribution of Sample Proportion
Problem 9c
Textbook Question
In Exercises 7–10, use the same population of {4, 5, 9} that was used in Examples 2 and 5. As in Examples 2 and 5, assume that samples of size n = 2 are randomly selected with replacement.
Sampling Distribution of the Sample Median
c. Find the mean of the sampling distribution of the sample median.

1
Step 1: Identify the population and the sample size. The population is {4, 5, 9}, and the sample size is n = 2. Sampling is done with replacement, meaning each element can be selected more than once.
Step 2: List all possible samples of size 2. Since sampling is with replacement, the possible samples are: (4, 4), (4, 5), (4, 9), (5, 4), (5, 5), (5, 9), (9, 4), (9, 5), (9, 9).
Step 3: For each sample, calculate the median. The median of a sample is the middle value when the sample is ordered. For example, the median of (4, 5) is 4.5, and the median of (5, 9) is 7. Repeat this for all samples.
Step 4: Construct the sampling distribution of the sample median. This involves listing all unique median values and their corresponding probabilities. The probability of each median value is determined by the frequency of occurrence of that median divided by the total number of samples.
Step 5: Calculate the mean of the sampling distribution of the sample median. Use the formula for the mean of a probability distribution: \( \mu = \sum (x_i \cdot P(x_i)) \), where \(x_i\) represents each unique median value and \(P(x_i)\) is its probability. Sum the products of each median value and its probability to find the mean.

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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Sampling Distribution
A sampling distribution is the probability distribution of a statistic (like the sample median) obtained from a large number of samples drawn from a specific population. It describes how the statistic varies from sample to sample and is crucial for understanding the behavior of sample statistics in inferential statistics.
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Sampling Distribution of Sample Proportion
Sample Median
The sample median is the middle value of a sample when the data points are arranged in ascending order. For an even number of observations, it is the average of the two middle values. The median is a measure of central tendency that is less affected by outliers than the mean, making it useful in skewed distributions.
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Sampling Distribution of Sample Proportion
Mean of the Sampling Distribution
The mean of the sampling distribution of a statistic is the expected value of that statistic across all possible samples. For the sample median, this mean provides insight into the central tendency of the sample medians derived from the population, allowing for predictions about the sample median's behavior in repeated sampling.
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Sampling Distribution of Sample Proportion
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