Categorical and quantitative variables, distributions, center and spread, boxplots, z-scores and the normal model.
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- What is a categorical variable?
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A variable that records categories or qualities (not numerical amounts)- What is a quantitative variable?
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A variable that records numerical amounts or measurements- Give two examples of categorical variables.
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Color, gender, type of car, yes/no response, brand, state, or any grouping that is not numerical- Give two examples of quantitative variables.
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Height, weight, temperature, age, income, test score, time, or any measurement that has numerical meaning- What does the distribution of a variable show?
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How the values of a variable are spread out, or the pattern of values in a dataset- What does SOCS stand for when describing a distribution?
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Shape, Outliers, Center, Spread- Describe a left-skewed distribution.
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A distribution with a long tail extending to the left, where the mean is less than the median- Describe a right-skewed distribution.
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A distribution with a long tail extending to the right, where the mean is greater than the median- What is a symmetric distribution?
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A distribution that looks the same on both sides of its center, with mean equal to median- What is a bimodal distribution?
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A distribution with two distinct peaks or modes, indicating two common values- Define an outlier.
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A value that is far from the rest of the data, much larger or much smaller than most other values- What does the center of a distribution refer to?
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A typical or representative value in the dataset, measured by mean, median, or mode- Define the mean.
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The sum of all values divided by the number of values (the arithmetic average)- Define the median.
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The middle value when the data is arranged in order from smallest to largest- Define the mode.
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The value that appears most frequently in a dataset
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