6.7: Key Terms
- Page ID
- 58309
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Key Terms and Definitions
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Mean — The arithmetic average of all values in a dataset.
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Median — The middle value that divides sorted data into two equal halves.
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Standard Deviation — The square root of variance; measures typical distance of data points from the mean.
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Normal Distribution — A symmetric, bell-shaped continuous distribution defined by mean and standard deviation.
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Binomial Distribution — A discrete distribution modeling the number of successes in a fixed number of independent trials.
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Poisson Distribution — A discrete distribution modeling counts of events occurring at a constant average rate.
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Central Limit Theorem — States that the sampling distribution of the mean approaches normal as sample size increases.
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Confidence Interval — A range of values likely to contain the true population parameter at a given confidence level.
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p-value — The probability of observing results as extreme as the data, assuming the null hypothesis is true.
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Null Hypothesis — The default assumption of no effect or no difference, tested against the alternative.
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Type I Error — Rejecting a true null hypothesis (false positive).
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Type II Error — Failing to reject a false null hypothesis (false negative).
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Significance Level (α) — The threshold probability (often 0.05) below which the null hypothesis is rejected.
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Correlation — A statistical measure of the strength and direction of a linear relationship between two variables.
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Variance — The average of the squared deviations from the mean; measures data spread in squared units.


