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
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.

1
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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