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This deck focuses on The Normal Distribution Revisited, giving you a quick way to review the definitions, rules, and examples that matter most for AP Statistics.
Study The Normal Distribution Revisited in AP Statistics with focused flashcards that help you recognize the idea, recall the key rule, and apply it in practice-style prompts.
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What does a z-score represent?
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Number of standard deviations from the mean. Measures distance from mean in standard deviation units.
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This deck focuses on The Normal Distribution Revisited, giving you a quick way to review the definitions, rules, and examples that matter most for AP Statistics.
Work through these flashcards in short sessions. Try to answer each prompt before flipping the card, then revisit any cards you miss until the explanation feels automatic.
Answer: Number of standard deviations from the mean. Measures distance from mean in standard deviation units.
Answer: A symmetric, bell-shaped curve. Characteristic appearance of normal probability distributions.
Answer: They are equal. Symmetry property of normal distributions.
Answer: Approximately 2.28%. Lower tail probability beyond two standard deviations.
Answer: The mean is 0. Defining characteristic of the standard normal distribution.
Answer: z≈1.28. Critical value for 90% of data below this point.
Answer: The tails are asymptotic to the x-axis. Approach but never touch the horizontal axis.
Answer: z≈0.675. Third quartile z-score in standard normal distribution.
Answer: μ (mu). Greek letter representing population mean parameter.
Answer: Approximately 2.5%. Upper tail beyond critical value for 95% confidence.
Answer: The total area is 1. Property of all probability distributions.
Answer: Normal distribution with μ=0, σ=1. Normalized version with mean 0 and standard deviation 1.
Answer: Normal distribution with μ=0, σ=1. Normalized version with mean 0 and standard deviation 1.
Answer: 5%. Upper tail probability beyond 1.645 standard deviations.
Answer: Approximately 0.13%. Lower tail probability beyond three standard deviations.
Answer: Number of standard deviations from the mean. Measures distance from mean in standard deviation units.
Answer: z≈0.675. Third quartile z-score in standard normal distribution.
Answer: 0.5. At mean, exactly half the data is below.
Answer: Approximately 62.97%. Cumulative probability up to 0.33 standard deviations.
Answer: Approximately 5%. Combined tail probabilities beyond critical values.
Answer: x=90. Solving −1=10x−100 gives x=90.
Answer: Approximately 95%. From the empirical rule for normal distributions.
Answer: Approximately 69.15%. Half standard deviation above mean corresponds to this percentile.
Answer: IQR = 1.349. Distance between 75th and 25th percentiles.
Answer: Approximately 0.13%. Combined tail areas beyond three standard deviations.
Answer: σ (sigma). Greek letter representing population standard deviation parameter.
Answer: z≈−0.675. First quartile z-score in standard normal distribution.
Answer: Approximately 13.59%. Area between one and two standard deviations above mean.
Answer: Approximately 0.13%. Lower tail probability beyond three standard deviations.
Answer: Approximately 62.97%. Cumulative probability up to 0.33 standard deviations.
Answer: Approximately 79.93%. Cumulative probability up to 0.84 standard deviations.
Answer: 0.5. At mean, exactly half the data is below.
Answer: They are equal. Symmetry property of normal distributions.
Answer: Approximately 79.93%. Cumulative probability up to 0.84 standard deviations.
Answer: Approximately 99.7%. From the empirical rule for normal distributions.
Answer: Approximately 2.5%. Upper tail beyond critical value for 95% confidence.
Answer: The skewness is 0. Normal distributions are perfectly symmetric, not skewed.
Answer: Approximately 0.13%. Combined tail areas beyond three standard deviations.
Answer: Approximately 68%. From the empirical rule for normal distributions.
Answer: z=−1. Using z=892−100=−1.
Answer: Approximately 97.5%. Two standard deviations above mean in standard normal distribution.
Answer: Approximately 95%. From the empirical rule for normal distributions.
Answer: z=σx−μ. Standardizes values by subtracting mean and dividing by standard deviation.
Answer: x=90. Solving −1=10x−100 gives x=90.
Answer: z=1. Using z=585−80=1.
Answer: The tails are asymptotic to the x-axis. Approach but never touch the horizontal axis.
Answer: 68%-95%-99.7% of data within 1, 2, 3 standard deviations. Also known as the 68-95-99.7 rule for normal distributions.
Answer: Approximately 13.59%. Area between one and two standard deviations above mean.
Answer: z=σx−μ. Standardizes values by subtracting mean and dividing by standard deviation.
Answer: Symmetric around the mean. Mean divides distribution into two equal halves.
Answer: z=−1. Using z=892−100=−1.
Answer: z≈−0.675. First quartile z-score in standard normal distribution.
Answer: The standard deviation is 1. Standard normal has unit variance and standard deviation.
Answer: IQR = 1.349. Distance between 75th and 25th percentiles.
Answer: 5%. Upper tail probability beyond 1.645 standard deviations.
Answer: z≈1.28. Critical value for 90% of data below this point.
Answer: Approximately 68%. From the empirical rule for normal distributions.
Answer: σ (sigma). Greek letter representing population standard deviation parameter.
Answer: Approximately 99.7%. From the empirical rule for normal distributions.
Answer: Approximately 2.28%. Lower tail probability beyond two standard deviations.
Answer: z=1. Using z=585−80=1.
Answer: 68%-95%-99.7% of data within 1, 2, 3 standard deviations. Also known as the 68-95-99.7 rule for normal distributions.
Answer: Approximately 5%. Combined tail probabilities beyond critical values.
Answer: μ (mu). Greek letter representing population mean parameter.
Answer: Approximately 97.5%. Two standard deviations above mean in standard normal distribution.
Answer: Approximately 69.15%. Half standard deviation above mean corresponds to this percentile.
Answer: Symmetric around the mean. Mean divides distribution into two equal halves.