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
3. Describing Data Numerically
Mean
Problem 2.3.66a
Textbook Question
Extending Concepts
Trimmed Mean To find the 10% trimmed mean of a data set, order the data, delete the lowest 10% of the entries and the highest 10% of the entries, and find the mean of the remaining entries.
a. Find the 10% trimmed mean for the data in Exercise 65.

1
Order the data set in ascending order to ensure the values are arranged from smallest to largest.
Determine the number of data points to trim from both the lowest and highest ends. This is calculated as 10% of the total number of data points. If the result is not an integer, round to the nearest whole number.
Remove the lowest 10% of the data points and the highest 10% of the data points from the ordered list.
Calculate the mean of the remaining data points by summing them and dividing by the number of remaining data points.
Express the result as the 10% trimmed mean of the data set.

This video solution was recommended by our tutors as helpful for the problem above
Video duration:
2mPlay a video:
Was this helpful?
Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Trimmed Mean
A trimmed mean is a statistical measure that reduces the influence of outliers by removing a specified percentage of the lowest and highest values from a data set before calculating the mean. For example, a 10% trimmed mean involves discarding the lowest 10% and the highest 10% of data points, which helps provide a more robust average that better represents the central tendency of the remaining data.
Recommended video:
Guided course
Calculating the Mean
Data Ordering
Data ordering is the process of arranging data points in a specific sequence, typically from lowest to highest. This step is crucial for calculating the trimmed mean, as it allows for the systematic removal of the specified percentage of extreme values, ensuring that the calculation of the mean is based on a representative subset of the data.
Recommended video:
Guided course
Visualizing Qualitative vs. Quantitative Data
Mean Calculation
The mean, or average, is a fundamental statistical measure calculated by summing all values in a data set and dividing by the number of values. In the context of a trimmed mean, the mean is computed only from the data points that remain after the specified percentage of extreme values has been removed, providing a more accurate reflection of the central tendency of the data.
Recommended video:
Guided course
Calculating the Mean
Watch next
Master Calculating the Mean with a bite sized video explanation from Patrick
Start learningRelated Videos
Related Practice