A study was conducted that resulted in the following relative frequency histogram. Determine whether or not the histogram indicates that a normal distribution could be used as a model for the variable.
To determine if a normal distribution could be used as a model for the variable, we need to consider certain characteristics of the histogram
To determine if a normal distribution could be used as a model for the variable, we need to consider certain characteristics of the histogram.
1. Shape: The shape of a normal distribution is bell-shaped, where the data is symmetrically distributed around the mean. Look for a histogram that resembles a bell curve.
2. Symmetry: In a normal distribution, the mean, median, and mode are all equal. Check if the histogram’s center (peak) aligns with the mean, and if the left and right tails are approximately symmetrical.
3. Skewness: A normal distribution has zero skewness, meaning it is neither positively nor negatively skewed. Skewness refers to the degree of asymmetry in the data. If the data is skewed, it may not follow a normal distribution.
4. Outliers: Typically, a normal distribution has no outliers, or if they exist, they are very rare. Look for any extreme values that are far from the main body of the data.
Based on these criteria, you can analyze the given histogram to determine if a normal distribution could be used as a model for the variable.
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