Graphical Analysis In Exercises 19–22, use the box-and-whisker plot to determine whether the shape of the distribution represented is symmetric, skewed left, skewed right, or none of these. Justify your answer.
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
6. Normal Distribution and Continuous Random Variables
Standard Normal Distribution
Problem 2.Q.1d
Textbook Question
The data set represents the number of minutes a sample of 27 people exercise each week.
108 139 120 123 120 132 123 131 131
157 150 124 111 101 135 119 116 117
127 128 139 119 118 114 127 142 130
d. Describe the shape of the distribution as symmetric, uniform, skewed left, skewed right, or none of these.
Verified step by step guidance1
Step 1: Organize the data set in ascending order to make it easier to analyze the distribution. This helps in identifying patterns or trends in the data.
Step 2: Create a frequency distribution or histogram by grouping the data into intervals (bins). This visual representation will help you observe the shape of the distribution.
Step 3: Analyze the histogram or frequency distribution. Look for symmetry, peaks, and tails. A symmetric distribution will have a bell-shaped curve, while skewed distributions will have longer tails on one side.
Step 4: Calculate measures of central tendency (mean, median, mode) and compare them. If the mean is greater than the median, the distribution is likely skewed right. If the mean is less than the median, the distribution is likely skewed left.
Step 5: Based on the visual representation and the comparison of central tendency measures, describe the shape of the distribution as symmetric, uniform, skewed left, skewed right, or none of these.
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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Distribution Shape
The shape of a distribution refers to the visual representation of data points across a range of values. Common shapes include symmetric, where data is evenly distributed around a central point; skewed left, where more data points fall on the right; and skewed right, where more data points fall on the left. Understanding the shape helps in identifying patterns and making inferences about the data.
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Skewness
Skewness measures the asymmetry of a distribution. A distribution is skewed left (negatively skewed) if it has a longer tail on the left side, indicating that most data points are concentrated on the right. Conversely, a right skew (positively skewed) has a longer tail on the right, suggesting that most values are on the left. Identifying skewness is crucial for understanding the data's behavior and potential outliers.
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Descriptive Statistics
Descriptive statistics summarize and describe the main features of a data set. Key measures include the mean, median, mode, and range, which provide insights into the central tendency and variability of the data. These statistics are essential for interpreting the distribution's shape and understanding the overall characteristics of the exercise minutes recorded in the sample.
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