[DATA] Old Faithful In Problem 26 from Section 3.1, we drew a histogram of the length of eruption of California’s Old Faithful geyser and found that the distribution is symmetric. Draw a boxplot of these data. Use the boxplot and quartiles to confirm the distribution is symmetric. For convenience, the data are displayed again.
Table of contents
- 1. Intro to Stats and Collecting Data1h 14m
- 2. Describing Data with Tables and Graphs1h 55m
- 3. Describing Data Numerically2h 5m
- 4. Probability2h 16m
- 5. Binomial Distribution & Discrete Random Variables3h 6m
- 6. Normal Distribution and Continuous Random Variables2h 11m
- 7. Sampling Distributions & Confidence Intervals: Mean3h 23m
- Sampling Distribution of the Sample Mean and Central Limit Theorem19m
- Distribution of Sample Mean - Excel23m
- Introduction to Confidence Intervals15m
- Confidence Intervals for Population Mean1h 18m
- Determining the Minimum Sample Size Required12m
- Finding Probabilities and T Critical Values - Excel28m
- Confidence Intervals for Population Means - Excel25m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 25m
- 9. Hypothesis Testing for One Sample3h 29m
- 10. Hypothesis Testing for Two Samples4h 50m
- Two Proportions1h 13m
- Two Proportions Hypothesis Test - Excel28m
- Two Means - Unknown, Unequal Variance1h 3m
- Two Means - Unknown Variances Hypothesis Test - Excel12m
- Two Means - Unknown, Equal Variance15m
- Two Means - Unknown, Equal Variances Hypothesis Test - Excel9m
- Two Means - Known Variance12m
- Two Means - Sigma Known Hypothesis Test - Excel21m
- Two Means - Matched Pairs (Dependent Samples)42m
- Matched Pairs Hypothesis Test - Excel12m
- 11. Correlation1h 24m
- 12. Regression1h 50m
- 13. Chi-Square Tests & Goodness of Fit2h 21m
- 14. ANOVA1h 57m
3. Describing Data Numerically
Boxplots
Problem 2.5.15b
Textbook Question
Drawing a Box-and-Whisker Plot In Exercises 15–18,
(b) draw a box-and-whisker plot that represents the data set.
39 36 30 27 26 24 28 35 39 60 50 41 35 32 51
Verified step by step guidance1
Step 1: Organize the data set in ascending order. The given data set is: 39, 36, 30, 27, 26, 24, 28, 35, 39, 60, 50, 41, 35, 32, 51. Arrange these values from smallest to largest.
Step 2: Identify the five-number summary of the data set. This includes the minimum value, first quartile (Q1), median (Q2), third quartile (Q3), and maximum value. Use the ordered data to calculate these values.
Step 3: Calculate the interquartile range (IQR) by subtracting Q1 from Q3. The formula is: . This will help determine the range of the box in the plot.
Step 4: Draw a number line that includes the range of the data. Mark the five-number summary (minimum, Q1, median, Q3, and maximum) on the number line. Draw a box from Q1 to Q3, with a vertical line at the median. Extend whiskers from the box to the minimum and maximum values.
Step 5: Check for outliers using the 1.5 * IQR rule. Any data point below or above is considered an outlier. Adjust the whiskers accordingly if outliers are present.
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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Box-and-Whisker Plot
A box-and-whisker plot is a graphical representation of a data set that displays its minimum, first quartile, median, third quartile, and maximum. The 'box' shows the interquartile range (IQR), which contains the middle 50% of the data, while the 'whiskers' extend to the smallest and largest values within 1.5 times the IQR from the quartiles. This plot helps visualize the distribution, central tendency, and variability of the data.
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Quartiles
Quartiles are values that divide a data set into four equal parts, each containing 25% of the data. The first quartile (Q1) is the median of the lower half of the data, the second quartile (Q2) is the overall median, and the third quartile (Q3) is the median of the upper half. Understanding quartiles is essential for constructing a box-and-whisker plot, as they determine the boundaries of the box and the placement of the median.
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Interquartile Range (IQR)
The interquartile range (IQR) is a measure of statistical dispersion that represents the range between the first quartile (Q1) and the third quartile (Q3). It is calculated as IQR = Q3 - Q1 and indicates the spread of the middle 50% of the data. The IQR is crucial for identifying outliers and is used to determine the length of the box in a box-and-whisker plot, providing insight into the variability of the data set.
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