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This deck focuses on Introducing Statistics Are My Results Unexpected, giving you a quick way to review the definitions, rules, and examples that matter most for AP Statistics.
Study Introducing Statistics Are My Results Unexpected 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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Quantitative variable. Numerical measurements that can be meaningfully ordered.
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This deck focuses on Introducing Statistics Are My Results Unexpected, 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: Quantitative variable. Numerical measurements that can be meaningfully ordered.
Answer: n−1. Reflects loss of information from estimating population SD.
Answer: 1.96. Corresponds to 2.5% in each tail of standard normal.
Answer: xˉ=10. (5+10+15)/3=30/3=10.
Answer: A test where effects in both directions are considered. Alternative hypothesis allows for effects in either direction.
Answer: To compare means from the same group at different times. Controls for individual differences by using matched pairs.
Answer: A data point that differs significantly from other observations. Unusual values that don't fit the general pattern.
Answer: xˉ=10. (5+10+15)/3=30/3=10.
Answer: xˉ±z∗nσ. Uses critical value and standard error of the mean.
Answer: z=1. (10−8)/2=1 standard deviation above mean.
Answer: To compare means from the same group at different times. Controls for individual differences by using matched pairs.
Answer: All group means are equal. ANOVA tests if all population means are identical.
Answer: 1.96. Corresponds to 2.5% in each tail of standard normal.
Answer: At least one group mean is different. Large F suggests between-group variation exceeds within-group.
Answer: Reject the null hypothesis. Evidence is strong enough to conclude Ha is true.
Answer: σ2 or s2. Variance equals standard deviation squared.
Answer: Reject the null hypothesis. Evidence is strong enough to conclude Ha is true.
Answer: How many standard deviations an element is from the mean. It standardizes position relative to the distribution.
Answer: All group means are equal. ANOVA tests if all population means are identical.
Answer: Mean 0, standard deviation 1. The reference distribution for z-scores.
Answer: σ2 or s2. Variance equals standard deviation squared.
Answer: Categorical variable. Qualities or labels that classify observations.
Answer: Type II error. False negative: failing to reject a false null hypothesis.
Answer: To determine if there is enough evidence to reject the null hypothesis. Provides systematic framework for decision-making with data.
Answer: μ. Greek letter mu represents the true population average.
Answer: The result is unlikely due to chance, given α. The observed difference is unlikely to be due to chance.
Answer: s. Lowercase s measures sample spread.
Answer: A data point that differs significantly from other observations. Unusual values that don't fit the general pattern.
Answer: z=σx−μ. Standardizes values by subtracting mean and dividing by SD.
Answer: α. Greek letter alpha sets our threshold for significance.
Answer: A test where effects in only one direction are considered. Alternative hypothesis specifies direction of the effect.
Answer: μ. Greek letter mu represents the true population average.
Answer: ANOVA. Analysis of variance extends t-tests to multiple groups.
Answer: Reject the null hypothesis. P-value is less than significance level.
Answer: The result is unlikely due to chance, given α. The observed difference is unlikely to be due to chance.
Answer: The probability of correctly rejecting a false null hypothesis. Higher power means better ability to detect real effects.
Answer: 0.05. This is the standard cutoff for statistical significance.
Answer: A test where effects in only one direction are considered. Alternative hypothesis specifies direction of the effect.
Answer: xˉ. X-bar represents the calculated average from sample data.
Answer: z=1. (10−8)/2=1 standard deviation above mean.
Answer: The alternative hypothesis states there is an effect or difference. It's what we're trying to prove or find evidence for.
Answer: Type II error. False negative: failing to reject a false null hypothesis.
Answer: z=σx−μ. Standardizes values by subtracting mean and dividing by SD.
Answer: n−1. Reflects loss of information from estimating population SD.
Answer: 95% of intervals will contain the true population parameter. It's about the method's long-run capture rate.
Answer: Type I error. False positive: rejecting a true null hypothesis.
Answer: The probability of observing data at least as extreme assuming the null hypothesis is true. It measures how unusual our data would be under H0.
Answer: Quantitative variable. Numerical measurements that can be meaningfully ordered.
Answer: n=(Ez∗σ)2. Balances desired precision with critical value and variability.
Answer: ANOVA. Analysis of variance extends t-tests to multiple groups.
Answer: The null hypothesis states there is no effect or difference. It's the baseline assumption we test against.
Answer: The probability of observing data at least as extreme assuming the null hypothesis is true. It measures how unusual our data would be under H0.
Answer: σ. Greek letter sigma measures population spread.
Answer: Testing independence or goodness of fit. Compares observed and expected frequencies in categories.
Answer: How many standard deviations an element is from the mean. It standardizes position relative to the distribution.
Answer: At least one group mean is different. Large F suggests between-group variation exceeds within-group.
Answer: α. Greek letter alpha sets our threshold for significance.
Answer: Data are normally distributed. Required for t-distribution to be appropriate.
Answer: The alternative hypothesis states there is an effect or difference. It's what we're trying to prove or find evidence for.
Answer: The null hypothesis states there is no effect or difference. It's the baseline assumption we test against.
Answer: xˉ. X-bar represents the calculated average from sample data.
Answer: A test where effects in both directions are considered. Alternative hypothesis allows for effects in either direction.
Answer: Type I error. False positive: rejecting a true null hypothesis.
Answer: n=(Ez∗σ)2. Balances desired precision with critical value and variability.
Answer: s. Lowercase s measures sample spread.
Answer: Categorical variable. Qualities or labels that classify observations.
Answer: Mean 0, standard deviation 1. The reference distribution for z-scores.
Answer: t=nsxˉ−μ. Uses sample SD when population SD is unknown.
Answer: xˉ±z∗nσ. Uses critical value and standard error of the mean.
Answer: 0.05. This is the standard cutoff for statistical significance.
Answer: Reject the null hypothesis. P-value is less than significance level.
Answer: t=nsxˉ−μ. Uses sample SD when population SD is unknown.
Answer: σ. Greek letter sigma measures population spread.
Answer: Data are normally distributed. Required for t-distribution to be appropriate.
Answer: The probability of correctly rejecting a false null hypothesis. Higher power means better ability to detect real effects.