AP Statistics Flashcards: Complete 5-Unit Course Review

Review all five revised AP Statistics units with 250 original cards on data, study design, probability, inference, and regression.

Über dieses Lernkartenset

Review the revised five-unit AP Statistics course with 250 independently written English flashcards. The deck follows the framework effective fall 2026: Exploring One-Variable Data and Collecting Data; Probability, Random Variables, and Probability Distributions; Inference for Categorical Data: Proportions; Inference for Quantitative Data: Means; and Regression Analysis.

What the cards ask you to retrieve

  • concept or condition → meaning
  • scenario → appropriate method
  • representation → interpretation
  • result → contextual conclusion
  • formula → use
  • common error → correction

The order follows Units 1–5, with prerequisite ideas introduced before later inference and regression applications. Every card has the root ap-statistics tag and exactly one unit tag.

What's deliberately left out

This is a compact active-recall review, not a complete course, an official curriculum, or a promise of a particular score. It does not include full free-response questions, timed multiple-choice simulation, calculator-button tutorials, AP Classroom content, copied official examples, or scoring-guideline imitation.

Scope was reviewed against the official AP Statistics course page and the Course and Exam Description effective fall 2026. Check those official sources for current policies, exam details, and later revisions.

Statistical facts and the official course outline are not claimed as original. The CC0 dedication applies to the deck's independently written card wording, organization, and original cover to the extent the contributor can dedicate those elements.

This independent, unofficial deck is not affiliated with, endorsed by, or sponsored by the College Board. AP® and Advanced Placement® are trademarks owned by the College Board. No exam questions, scoring guidelines, curriculum passages, official examples, tables, logos, or trade dress are copied.

Karten in diesem Lernkartenset

  1. Karte 1

    Frage

    What makes a question a statistical investigative question?

    Antwort

    It anticipates variability in data and can be answered by collecting and analyzing data about a population or process.

  2. Karte 2

    Frage

    What is an observational unit?

    Antwort

    An individual item or person from which data are collected.

  3. Karte 3

    Frage

    A student's class year is recorded as freshman, sophomore, junior, or senior. What type of variable is this?

    Antwort

    Categorical. The values name groups rather than measure a numerical amount.

  4. Karte 4

    Frage

    How does a parameter differ from a statistic?

    Antwort

    A parameter describes a population; a statistic describes a sample.

  5. Karte 5

    Frage

    How is a category's relative frequency calculated?

    Antwort

    Divide the category count by the total number of observations.

  6. Karte 6

    Frage

    What should the height of a bar represent in a relative-frequency bar chart?

    Antwort

    The proportion or percentage of observations in that category.

  7. Karte 7

    Frage

    Number of text messages sent in a day: discrete or continuous?

    Antwort

    Discrete. It is a count with separated possible values.

  8. Karte 8

    Frage

    Which displays preserve individual quantitative data values?

    Antwort

    Dotplots and stem-and-leaf plots. A histogram groups values into intervals.

  9. Karte 9

    Frage

    What four features should a description of a quantitative distribution address?

    Antwort

    Shape, center, variability, and unusual features such as gaps or outliers.

  10. Karte 10

    Frage

    Which measure of center is usually better for a strongly right-skewed distribution?

    Antwort

    The median, because it is resistant to extreme high values.

  11. Karte 11

    Frage

    The values are 3, 5, 5, and 11. What is the mean?

    Antwort

    1. The sum is 24, divided by 4 observations.
  12. Karte 12

    Frage

    The ordered values are 2, 4, 7, 9, 12, and 20. What is the median?

    Antwort

    8, the average of the two middle values 7 and 9.

  13. Karte 13

    Frage

    How is the interquartile range calculated?

    Antwort

    IQR = Q3 − Q1. It measures the spread of the middle 50% of the data.

  14. Karte 14

    Frage

    What does a small standard deviation say about a data set?

    Antwort

    Values typically lie close to the mean.

  15. Karte 15

    Frage

    Which common summaries are resistant to extreme values?

    Antwort

    The median and IQR are resistant; the mean and standard deviation are not.

  16. Karte 16

    Frage

    In a modified boxplot, where do the whiskers end?

    Antwort

    At the smallest and largest observed values within the 1.5 × IQR fences; values beyond the fences are plotted separately as potential outliers.

  17. Karte 17

    Frage

    What are the 1.5 × IQR outlier fences?

    Antwort

    Lower fence = Q1 − 1.5(IQR); upper fence = Q3 + 1.5(IQR). Values beyond them are flagged as potential outliers.

  18. Karte 18

    Frage

    How should two quantitative distributions be compared?

    Antwort

    Compare shape, center, variability, and unusual features in context, using the same measure or display basis.

  19. Karte 19

    Frage

    What does a z-score of −1.8 mean?

    Antwort

    The value is 1.8 standard deviations below the mean.

  20. Karte 20

    Frage

    Every observation is converted from meters to centimeters by multiplying by 100. What happens to the mean and standard deviation?

    Antwort

    Both are multiplied by 100.

  21. Karte 21

    Frage

    What should an investigative question identify so the conclusion has a clear scope?

    Antwort

    The variable or parameter of interest and the population to which the conclusion may apply.

  22. Karte 22

    Frage

    What is a census?

    Antwort

    A study that collects data from every member of the population.

  23. Karte 23

    Frage

    What makes a study an experiment?

    Antwort

    Researchers deliberately assign treatments to experimental units.

  24. Karte 24

    Frage

    How do prospective and retrospective observational studies differ?

    Antwort

    A prospective study follows units forward and gathers future data; a retrospective study uses data from the past.

  25. Karte 25

    Frage

    What is a confounding variable in an observational study?

    Antwort

    A variable associated with both the explanatory and response variables that offers an alternative explanation for their relationship.

  26. Karte 26

    Frage

    What study feature supports generalizing results to a population?

    Antwort

    Random selection from that population.

  27. Karte 27

    Frage

    What makes a study observational?

    Antwort

    Researchers observe variables without assigning treatments.

  28. Karte 28

    Frage

    What study feature supports a cause-and-effect conclusion?

    Antwort

    Random assignment of treatments in a well-designed experiment.

  29. Karte 29

    Frage

    What defines a simple random sample of size n?

    Antwort

    Every possible sample of size n has the same chance of selection.

  30. Karte 30

    Frage

    What changes when sampling is done with replacement?

    Antwort

    A selected unit returns to the population and can be selected again.

  31. Karte 31

    Frage

    Why can a convenience sample be biased?

    Antwort

    Easy-to-reach units may differ systematically from the target population.

  32. Karte 32

    Frage

    Why should an experiment compare at least two treatment groups?

    Antwort

    The comparison provides a baseline for judging whether responses differ by treatment.

  33. Karte 33

    Frage

    A school samples 20 students at random from each grade. Which sampling method is this?

    Antwort

    Stratified random sampling, with grade as the stratum.

  34. Karte 34

    Frage

    What is the purpose of random assignment?

    Antwort

    It tends to balance lurking variables across treatment groups, supporting causal inference.

  35. Karte 35

    Frage

    Why can a voluntary-response sample be biased?

    Antwort

    People with strong opinions are often more likely to participate.

  36. Karte 36

    Frage

    What does replication mean in an experiment?

    Antwort

    Assigning more than one experimental unit to each treatment so treatment differences can be separated from individual variability.

  37. Karte 37

    Frage

    A city randomly selects 8 apartment buildings and surveys every household in those buildings. Which method is this?

    Antwort

    Cluster random sampling.

  38. Karte 38

    Frage

    What does direct control do in an experiment?

    Antwort

    It holds potential extraneous sources of variation constant across experimental units.

  39. Karte 39

    Frage

    What is undercoverage?

    Antwort

    Some groups in the target population are left out of, or poorly represented in, the sampling frame.

  40. Karte 40

    Frage

    What is the role of a control group?

    Antwort

    It supplies a comparison condition for evaluating the treatment of interest.

  41. Karte 41

    Frage

    After a random start, a quality inspector checks every 40th item. Which sampling method is this?

    Antwort

    Systematic random sampling.

  42. Karte 42

    Frage

    Why might an experiment use a placebo?

    Antwort

    To separate a treatment's effect from responses caused by expecting treatment.

  43. Karte 43

    Frage

    What is nonresponse bias?

    Antwort

    Selected individuals who do not respond differ in a relevant way from those who do.

  44. Karte 44

    Frage

    What is single blinding designed to reduce?

    Antwort

    Bias caused when participants or evaluators know which treatment was received, depending on who is blinded.

  45. Karte 45

    Frage

    Why use a randomized block design?

    Antwort

    To group units that are similar on an important source of variation, then compare treatments within each block.

  46. Karte 46

    Frage

    What defines a matched-pairs design?

    Antwort

    Two treatments are compared using paired similar units or by giving both treatments to each unit in randomized order.

  47. Karte 47

    Frage

    A survey asks, “Don't you agree the new schedule is unfair?” What problem does this create?

    Antwort

    Response bias from leading wording.

  48. Karte 48

    Frage

    What usually makes an experiment double-blind?

    Antwort

    Neither the participants nor the people evaluating responses know treatment assignments while outcomes are measured.

  49. Karte 49

    Frage

    A researcher randomly assigns 80 volunteers to two diets and compares blood-pressure change. What conclusion can random assignment support?

    Antwort

    A cause-and-effect conclusion for people similar to the volunteers, assuming the experiment is well designed; volunteer recruitment does not support broad population generalization.

  50. Karte 50

    Frage

    A researcher records coffee intake and sleep duration without assigning either. Can the study establish that coffee causes less sleep?

    Antwort

    No. It is observational, so confounding can provide alternative explanations.

  51. Karte 51

    Frage

    What is the difference between a population and a sample?

    Antwort

    The population is the full group of interest; a sample is the subset actually observed.

  52. Karte 52

    Frage

    Which graph is appropriate for the distribution of one quantitative variable measured on 600 people?

    Antwort

    A histogram is appropriate; it groups the many numerical values into intervals.

  53. Karte 53

    Frage

    In a strongly right-skewed distribution, how do the mean and median usually compare?

    Antwort

    The mean is usually larger because high values pull it to the right.

  54. Karte 54

    Frage

    Every score increases by 7 points. What happens to the mean and standard deviation?

    Antwort

    The mean increases by 7; the standard deviation stays unchanged.

  55. Karte 55

    Frage

    What does it mean that a score is at the 80th percentile?

    Antwort

    About 80% of scores are at or below it.

  56. Karte 56

    Frage

    Why should gaps and clusters be mentioned when describing a distribution?

    Antwort

    They may reveal distinct subgroups, collection effects, or other structure that center and spread alone hide.

  57. Karte 57

    Frage

    What is the minimum ethical safeguard when collecting identifiable human data?

    Antwort

    Obtain informed consent when required and protect participants' privacy and confidentiality.

  58. Karte 58

    Frage

    Every measurement is multiplied by −2. What happens to the mean and standard deviation?

    Antwort

    The mean is multiplied by −2; the standard deviation is multiplied by 2.

  59. Karte 59

    Frage

    A study uses random sampling but no assigned treatment. What can it support?

    Antwort

    Population generalization, but not a cause-and-effect conclusion.

  60. Karte 60

    Frage

    A report calls any unmeasured variable a confounder. What is the correction?

    Antwort

    A confounder must be related to both the explanatory and response variables and create an alternative explanation.

  61. Karte 61

    Frage

    What does a two-way table summarize?

    Antwort

    Counts or relative frequencies for combinations of two categorical variables.

  62. Karte 62

    Frage

    What is a joint relative frequency?

    Antwort

    A cell count divided by the grand total, representing one combination of categories.

  63. Karte 63

    Frage

    What is a marginal relative frequency?

    Antwort

    A row or column total divided by the grand total.

  64. Karte 64

    Frage

    How is a conditional relative frequency calculated within one row?

    Antwort

    Divide each cell in that row by the row total.

  65. Karte 65

    Frage

    What pattern suggests association between two categorical variables?

    Antwort

    The conditional distribution of one variable changes across categories of the other.

  66. Karte 66

    Frage

    Why are segmented bar charts useful for two categorical variables?

    Antwort

    They place conditional distributions on the same 100% scale, making category patterns easy to compare.

  67. Karte 67

    Frage

    How do an outcome and an event differ?

    Antwort

    An outcome is one result of a trial; an event is a set of one or more outcomes.

  68. Karte 68

    Frage

    What must a valid probability simulation specify?

    Antwort

    A chance mechanism whose outcomes match the event probabilities, one trial definition, the statistic recorded, and many repetitions.

  69. Karte 69

    Frage

    What does the law of large numbers predict?

    Antwort

    As independent trials accumulate, an event's long-run relative frequency tends to approach its probability.

  70. Karte 70

    Frage

    What two requirements must probabilities in a sample space satisfy?

    Antwort

    Each probability is between 0 and 1, and the probabilities of all nonoverlapping outcomes sum to 1.

  71. Karte 71

    Frage

    What is the complement rule?

    Antwort

    P(Aᶜ) = 1 − P(A). It is often useful for “at least one” events.

  72. Karte 72

    Frage

    How can you verify that events A and B are mutually exclusive?

    Antwort

    Their intersection is impossible, so P(A ∩ B) = 0.

  73. Karte 73

    Frage

    What is the formula for P(A | B), when P(B) > 0?

    Antwort

    P(A | B) = P(A ∩ B) / P(B). The restricted sample space is B.

  74. Karte 74

    Frage

    What is the general multiplication rule for two events?

    Antwort

    P(A ∩ B) = P(A)P(B | A), or equivalently P(B)P(A | B).

  75. Karte 75

    Frage

    What does it mean for events A and B to be independent?

    Antwort

    Knowing that one occurred does not change the probability of the other.

  76. Karte 76

    Frage

    What is the general addition rule?

    Antwort

    P(A ∪ B) = P(A) + P(B) − P(A ∩ B).

  77. Karte 77

    Frage

    Why are two mutually exclusive events with positive probabilities not independent?

    Antwort

    If one occurs, the other cannot occur, so its conditional probability drops to 0.

  78. Karte 78

    Frage

    What is a random variable?

    Antwort

    A numerical value determined by the outcome of a random process.

  79. Karte 79

    Frage

    What makes a table a valid discrete probability distribution?

    Antwort

    It lists every possible value with probabilities from 0 to 1 that sum to 1.

  80. Karte 80

    Frage

    What does a cumulative distribution value F(x) represent?

    Antwort

    P(X ≤ x), the probability that the random variable is at most x.

  81. Karte 81

    Frage

    How is the expected value of a discrete random variable calculated?

    Antwort

    Multiply each possible value by its probability and add: E(X) = ΣxP(X = x).

  82. Karte 82

    Frage

    What does the standard deviation of a random variable measure?

    Antwort

    The typical distance of long-run outcomes from the random variable's mean.

  83. Karte 83

    Frage

    How is the standard deviation of a discrete random variable calculated?

    Antwort

    σₓ = √[Σ(x − μₓ)²P(X = x)]. The quantity inside the square root is Var(X).

  84. Karte 84

    Frage

    A game has E(X) = −$0.40 per play. What does this mean?

    Antwort

    Over many plays, the player's average net result approaches a loss of 40 cents per play; it does not predict every play.

  85. Karte 85

    Frage

    What conditions define a binomial random variable?

    Antwort

    A fixed number of independent trials, two outcomes per trial, constant success probability, and X counts successes.

  86. Karte 86

    Frage

    For X ~ Binomial(n, p), what are the mean and standard deviation?

    Antwort

    Mean = np; standard deviation = √[np(1 − p)].

  87. Karte 87

    Frage

    For X ~ Binomial(n, p), what is P(X = x)?

    Antwort

    Choose x success positions, then multiply: C(n, x)pˣ(1 − p)ⁿ⁻ˣ.

  88. Karte 88

    Frage

    How can P(X ≥ 1) be found efficiently for a binomial variable?

    Antwort

    Use the complement: P(X ≥ 1) = 1 − P(X = 0).

  89. Karte 89

    Frage

    What should one simulated trial represent when estimating P(X ≥ 4) for X ~ Binomial(10, 0.3)?

    Antwort

    Ten independent success/failure observations with success probability 0.3, followed by recording whether at least four successes occurred.

  90. Karte 90

    Frage

    What features characterize a normal distribution?

    Antwort

    It is continuous, symmetric, unimodal, and bell-shaped.

  91. Karte 91

    Frage

    Which parameters determine a normal distribution?

    Antwort

    Its mean μ sets the center, and its standard deviation σ sets the spread.

  92. Karte 92

    Frage

    What is the standard normal distribution?

    Antwort

    The normal distribution with mean 0 and standard deviation 1.

  93. Karte 93

    Frage

    What is the 68–95–99.7 rule?

    Antwort

    For an approximately normal distribution, about 68%, 95%, and 99.7% of values lie within 1, 2, and 3 standard deviations of the mean.

  94. Karte 94

    Frage

    What does an area under a normal curve represent?

    Antwort

    The probability or population proportion within the corresponding interval.

  95. Karte 95

    Frage

    How do you find the value cutting off the lowest 10% of a normal distribution?

    Antwort

    Find the z-score with cumulative area 0.10, then convert with x = μ + zσ.

  96. Karte 96

    Frage

    A normal variable has μ = 50 and σ = 8. What z-score corresponds to x = 62?

    Antwort

    1.5, because z = (62 − 50) / 8.

  97. Karte 97

    Frage

    Two exam scores come from different normal distributions. What makes their percentiles comparable?

    Antwort

    Standardize each score with its own distribution's mean and standard deviation, then compare z-scores or cumulative areas.

  98. Karte 98

    Frage

    What is a sampling distribution of a statistic?

    Antwort

    The distribution of that statistic over all possible random samples of a fixed size from a population.

  99. Karte 99

    Frage

    How can a sampling distribution be approximated by simulation?

    Antwort

    Repeatedly take random samples of the same size, calculate the statistic each time, and graph the resulting values.

  100. Karte 100

    Frage

    What is a randomization distribution?

    Antwort

    A simulated distribution of a statistic produced by repeatedly reallocating responses or labels as specified by a null model.

  101. Karte 101

    Frage

    What does the central limit theorem say about sample means?

    Antwort

    For random samples, the sampling distribution of the sample mean becomes approximately normal as sample size grows, even when the population is not normal.

  102. Karte 102

    Frage

    How does increasing sample size affect the normal approximation in the central limit theorem?

    Antwort

    It generally improves the approximation, especially for skewed or irregular populations.

  103. Karte 103

    Frage

    A segmented bar chart shows nearly identical category proportions for every group. What does that suggest?

    Antwort

    Little or no association between the two categorical variables.

  104. Karte 104

    Frage

    In a survey, 30 of 120 students both bike to school and arrive before 8:00. What is the joint relative frequency?

    Antwort

    0.25, because 30 / 120 = 0.25.

  105. Karte 105

    Frage

    Why can P(A | B) differ from P(B | A)?

    Antwort

    They use different restricted sample spaces and usually have different denominators.

  106. Karte 106

    Frage

    If P(A) = 0.4 and P(A | B) = 0.4 with P(B) > 0, what does this indicate?

    Antwort

    A and B are independent because learning B does not change the probability of A.

  107. Karte 107

    Frage

    If independent events have probabilities 0.6 and 0.5, what is the probability that both occur?

    Antwort

    0.30, using P(A ∩ B) = P(A)P(B).

  108. Karte 108

    Frage

    A prize is $0 with probability 0.7 and $10 with probability 0.3. What is the expected prize?

    Antwort

    $3, because 0(0.7) + 10(0.3) = 3.

  109. Karte 109

    Frage

    A machine produces defective items independently with probability 0.02. What distribution models the number of defectives in 50 items?

    Antwort

    Binomial with n = 50 and p = 0.02.

  110. Karte 110

    Frage

    Heights are approximately normal with μ = 170 cm and σ = 6 cm. About what percent lie from 158 to 182 cm?

    Antwort

    About 95%, because the interval is μ ± 2σ.

  111. Karte 111

    Frage

    What makes an estimator unbiased?

    Antwort

    Its sampling distribution is centered at the population parameter it estimates.

  112. Karte 112

    Frage

    For random samples of size n, what is the mean of the sampling distribution of p̂?

    Antwort

    μₚ̂ = p, where p is the population proportion.

  113. Karte 113

    Frage

    Which procedure estimates one population proportion from a random sample?

    Antwort

    A one-sample z-interval for a population proportion.

  114. Karte 114

    Frage

    How should a confidence interval for a population proportion be interpreted?

    Antwort

    We are confident at the stated level that the interval captures the true population proportion, in context.

  115. Karte 115

    Frage

    What hypotheses test whether a population proportion differs from 0.40?

    Antwort

    H₀: p = 0.40 versus Hₐ: p ≠ 0.40.

  116. Karte 116

    Frage

    What is a p-value?

    Antwort

    Assuming H₀ is true, it is the probability of a test statistic as extreme as or more extreme than the observed statistic in the direction of Hₐ.

  117. Karte 117

    Frage

    What is the hypothesis-test decision rule using significance level α?

    Antwort

    Reject H₀ when the p-value ≤ α; otherwise fail to reject H₀.

  118. Karte 118

    Frage

    What is a Type I error?

    Antwort

    Rejecting H₀ when H₀ is actually true.

  119. Karte 119

    Frage

    What is the mean of p̂₁ − p̂₂ for independent random samples?

    Antwort

    p₁ − p₂.

  120. Karte 120

    Frage

    Which procedure estimates p₁ − p₂ from two independent samples or randomized groups?

    Antwort

    A two-sample z-interval for a difference between population proportions.

  121. Karte 121

    Frage

    How should a confidence interval for p₁ − p₂ be interpreted?

    Antwort

    We are confident at the stated level that the interval captures the true difference p₁ − p₂, in context.

  122. Karte 122

    Frage

    What null hypothesis is standard when testing whether two population proportions differ?

    Antwort

    H₀: p₁ − p₂ = 0, equivalently p₁ = p₂.

  123. Karte 123

    Frage

    A two-proportion test gives p-value 0.018 at α = 0.05. What decision follows?

    Antwort

    Reject H₀ because 0.018 < 0.05.

  124. Karte 124

    Frage

    When is a chi-square test for independence appropriate?

    Antwort

    When one random sample provides two categorical variables and the question asks whether they are associated in one population.

  125. Karte 125

    Frage

    How should a chi-square test p-value be interpreted?

    Antwort

    Assuming the null model of independence or homogeneity is true, it is the probability of a chi-square statistic at least as large as the one observed.

    Five connected statistical stages show observations becoming a distribution, a sample, a probability curve, and a regression scatterplot.

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  126. Karte 126

    Frage

    How do bias and variability differ for an estimator?

    Antwort

    Bias concerns where the sampling distribution is centered; variability concerns how spread out it is.

  127. Karte 127

    Frage

    What is the standard deviation of p̂ when observations are independent?

    Antwort

    σₚ̂ = √[p(1 − p) / n].

  128. Karte 128

    Frage

    What is the one-proportion z-interval formula?

    Antwort

    p̂ ± z*√[p̂(1 − p̂) / n].

  129. Karte 129

    Frage

    What does a 95% confidence level describe?

    Antwort

    In repeated random sampling with the same method, about 95% of the resulting intervals would capture the true parameter.

  130. Karte 130

    Frage

    Which method tests a claim about one population proportion when its conditions hold?

    Antwort

    A one-sample z-test for a population proportion.

  131. Karte 131

    Frage

    How does the alternative hypothesis determine a p-value's tail area?

    Antwort

    A greater-than alternative uses the upper tail, a less-than alternative uses the lower tail, and a not-equal alternative uses both tails.

  132. Karte 132

    Frage

    What wording should follow a rejected null hypothesis?

    Antwort

    There is convincing statistical evidence for the alternative claim about the population parameter, stated in context.

  133. Karte 133

    Frage

    What is a Type II error?

    Antwort

    Failing to reject H₀ when Hₐ is actually true.

  134. Karte 134

    Frage

    What is the standard deviation of p̂₁ − p̂₂ for independent samples?

    Antwort

    √[p₁(1 − p₁)/n₁ + p₂(1 − p₂)/n₂].

  135. Karte 135

    Frage

    What standard error is used in a confidence interval for p₁ − p₂?

    Antwort

    √[p̂₁(1 − p̂₁)/n₁ + p̂₂(1 − p̂₂)/n₂]; the sample proportions are not pooled.

  136. Karte 136

    Frage

    A confidence interval for p₁ − p₂ contains 0. What does that imply?

    Antwort

    The interval does not provide convincing evidence of a difference between the population proportions at the corresponding two-sided significance level.

  137. Karte 137

    Frage

    Why is a pooled proportion used in a two-proportion z-test with H₀: p₁ = p₂?

    Antwort

    The null model assumes both samples share one common population proportion, estimated by combining successes and observations.

  138. Karte 138

    Frage

    How should a p-value for a two-proportion test be stated?

    Antwort

    Assuming the population proportions are equal, it is the probability of observing a difference in sample proportions at least as extreme as the one found, in the direction of Hₐ.

  139. Karte 139

    Frage

    When is a chi-square test for homogeneity appropriate?

    Antwort

    When independent samples or randomized groups are compared on the distribution of one categorical response variable.

  140. Karte 140

    Frage

    What is the chi-square test statistic formula?

    Antwort

    χ² = Σ[(observed − expected)² / expected], summed over all cells.

  141. Karte 141

    Frage

    What usually happens to an estimator's sampling variability as sample size increases?

    Antwort

    It decreases; estimates from larger random samples tend to cluster more tightly around the parameter.

  142. Karte 142

    Frage

    When is the sampling distribution of p̂ approximately normal?

    Antwort

    When the expected counts np and n(1 − p) are both at least 10.

  143. Karte 143

    Frage

    What conditions justify a one-proportion z-interval?

    Antwort

    Random data; independence, checked with n ≤ 10% of the population when sampling without replacement; and at least 10 observed successes and 10 observed failures.

  144. Karte 144

    Frage

    A 95% confidence interval for p is (0.52, 0.61). What does it say about the claim p = 0.50?

    Antwort

    The interval excludes 0.50, so the data provide evidence against p = 0.50 in a two-sided test at α = 0.05.

  145. Karte 145

    Frage

    What is the one-proportion z-test statistic?

    Antwort

    z = (p̂ − p₀) / √[p₀(1 − p₀)/n], using the null proportion p₀ in the standard error.

  146. Karte 146

    Frage

    How is a simulation-based p-value estimated?

    Antwort

    Find the proportion of simulated null statistics at least as extreme as the observed statistic in the direction of Hₐ.

  147. Karte 147

    Frage

    What does “fail to reject H₀” mean?

    Antwort

    The data do not provide convincing evidence for Hₐ; it does not prove H₀ true.

  148. Karte 148

    Frage

    With sample size and effect fixed, what often happens when α is lowered?

    Antwort

    The chance of a Type I error decreases, while the chance of a Type II error increases.

  149. Karte 149

    Frage

    What conditions support the usual model for p̂₁ − p̂₂?

    Antwort

    Independent random samples or randomized groups, independence within each group, and large enough expected success and failure counts for normal approximation.

  150. Karte 150

    Frage

    What conditions justify a two-proportion z-interval?

    Antwort

    Independent random samples or randomized groups; each sample no more than 10% of its population when sampling without replacement; and at least 10 observed successes and failures in each group.

  151. Karte 151

    Frage

    How does increasing both sample sizes affect a confidence interval for p₁ − p₂?

    Antwort

    It reduces the standard error and usually narrows the interval when other factors stay the same.

  152. Karte 152

    Frage

    What standard error is used in the two-proportion z-test?

    Antwort

    √[p̂c(1 − p̂c)(1/n₁ + 1/n₂)], where p̂c is the pooled sample proportion.

  153. Karte 153

    Frage

    A randomized experiment uses volunteers assigned to two treatments. A significant two-proportion test supports what scope?

    Antwort

    A cause-and-effect conclusion for people similar to the volunteers, not automatic generalization to a broader population.

  154. Karte 154

    Frage

    How is an expected count computed in a two-way table under independence?

    Antwort

    Expected count = (row total × column total) / grand total.

  155. Karte 155

    Frage

    What conditions justify a chi-square test for a two-way table?

    Antwort

    Random data; independent observations, including the 10% check when sampling without replacement; and every expected cell count greater than 5.

  156. Karte 156

    Frage

    A sampling distribution is centered away from the true parameter. What problem does this reveal?

    Antwort

    Bias in the estimator.

  157. Karte 157

    Frage

    If p = 0.30 and n = 100, what does μₚ̂ = 0.30 mean?

    Antwort

    Across many random samples of 100, the average sample proportion would be 0.30.

  158. Karte 158

    Frage

    For a planned proportion interval with margin of error m, what conservative p-value is used when no prior estimate exists?

    Antwort

    Use p* = 0.50 in n ≥ (z*/m)²p*(1 − p*) because it gives the largest required sample size.

  159. Karte 159

    Frage

    What two changes widen a confidence interval for a proportion?

    Antwort

    Using a higher confidence level or a smaller sample size.

  160. Karte 160

    Frage

    Which counts check normality for a one-proportion z-test?

    Antwort

    Use the null model: np₀ ≥ 10 and n(1 − p₀) ≥ 10.

  161. Karte 161

    Frage

    What is wrong with saying “the p-value is the probability that H₀ is true”?

    Antwort

    The p-value assumes H₀ is true and measures how unusual the observed statistic would be under that assumption; it does not assign probability to H₀.

  162. Karte 162

    Frage

    What does “statistically significant at α = 0.01” mean?

    Antwort

    The p-value is at most 0.01, so H₀ is rejected at that significance level.

  163. Karte 163

    Frage

    What is the power of a hypothesis test?

    Antwort

    The probability that the test rejects H₀ when a particular alternative is true.

  164. Karte 164

    Frage

    If p₁ = p₂, where is the sampling distribution of p̂₁ − p̂₂ centered?

    Antwort

    At 0, because its mean is p₁ − p₂.

  165. Karte 165

    Frage

    Why must the order p̂₁ − p̂₂ stay consistent throughout an interval?

    Antwort

    Changing the order reverses the sign and changes the contextual interpretation of every endpoint.

  166. Karte 166

    Frage

    A 95% interval for p₁ − p₂ is (0.04, 0.15). What conclusion is supported?

    Antwort

    p₁ is plausibly 0.04 to 0.15 higher than p₂; the interval supports a positive difference.

  167. Karte 167

    Frage

    Which success-failure counts are checked for a two-proportion z-test?

    Antwort

    Expected counts based on the pooled null proportion: n₁p̂c, n₁(1 − p̂c), n₂p̂c, and n₂(1 − p̂c), each at least 10.

  168. Karte 168

    Frage

    A two-proportion test with Hₐ: p₁ ≠ p₂ fails to reject H₀. What conclusion is valid?

    Antwort

    There is not convincing evidence that the two population proportions differ.

  169. Karte 169

    Frage

    What are the degrees of freedom for a chi-square test on an r × c table?

    Antwort

    (r − 1)(c − 1).

  170. Karte 170

    Frage

    A chi-square test for independence has a small p-value. What conclusion is appropriate?

    Antwort

    There is convincing evidence of an association between the two categorical variables in the population, stated in context.

  171. Karte 171

    Frage

    What is the mean of the sampling distribution of x̄ for random samples from a population with mean μ?

    Antwort

    μₓ̄ = μ.

  172. Karte 172

    Frage

    Which procedure estimates one population mean when the population standard deviation is unknown?

    Antwort

    A one-sample t-interval for a population mean.

  173. Karte 173

    Frage

    How should a confidence interval for a population mean be interpreted?

    Antwort

    We are confident at the stated level that the interval captures the true population mean, in context.

  174. Karte 174

    Frage

    What hypotheses test whether a population mean exceeds 12?

    Antwort

    H₀: μ = 12 versus Hₐ: μ > 12.

  175. Karte 175

    Frage

    A one-sample t-test gives p-value 0.08 at α = 0.05. What decision follows?

    Antwort

    Fail to reject H₀ because 0.08 > 0.05.

  176. Karte 176

    Frage

    What is the mean of x̄₁ − x̄₂ for independent random samples?

    Antwort

    μ₁ − μ₂.

  177. Karte 177

    Frage

    Which procedure estimates μ₁ − μ₂ from two independent samples?

    Antwort

    A two-sample t-interval for a difference between population means.

  178. Karte 178

    Frage

    How should a confidence interval for μ₁ − μ₂ be interpreted?

    Antwort

    We are confident at the stated level that the interval captures the true difference μ₁ − μ₂, in context.

  179. Karte 179

    Frage

    What null hypothesis is standard when testing whether two population means differ?

    Antwort

    H₀: μ₁ − μ₂ = 0, equivalently μ₁ = μ₂.

  180. Karte 180

    Frage

    A two-sample t-test gives p-value 0.004 at α = 0.01. What decision follows?

    Antwort

    Reject H₀ because 0.004 < 0.01.

  181. Karte 181

    Frage

    What is the standard deviation of x̄ when observations are independent?

    Antwort

    σₓ̄ = σ / √n.

  182. Karte 182

    Frage

    What is the one-sample t-interval formula for μ?

    Antwort

    x̄ ± t* × s/√n, with t* based on n − 1 degrees of freedom.

  183. Karte 183

    Frage

    What does a 90% confidence level mean for a mean interval procedure?

    Antwort

    Across many random samples using the same procedure, about 90% of the intervals would capture the true population mean.

  184. Karte 184

    Frage

    Which procedure tests a claim about one population mean when σ is unknown?

    Antwort

    A one-sample t-test for a population mean.

  185. Karte 185

    Frage

    How should a one-mean test p-value be interpreted?

    Antwort

    Assuming the null mean is true, it is the probability of a t-statistic as extreme as or more extreme than observed in the direction of Hₐ.

  186. Karte 186

    Frage

    What is the standard deviation of x̄₁ − x̄₂ for independent samples?

    Antwort

    √(σ₁²/n₁ + σ₂²/n₂).

  187. Karte 187

    Frage

    What standard error is used in a two-sample t-interval for μ₁ − μ₂?

    Antwort

    √(s₁²/n₁ + s₂²/n₂).

  188. Karte 188

    Frage

    A confidence interval for μ₁ − μ₂ contains 0. What does that imply?

    Antwort

    The interval does not provide convincing evidence of a difference between the population means at the corresponding two-sided significance level.

  189. Karte 189

    Frage

    What is the two-sample t-statistic for testing H₀: μ₁ − μ₂ = 0?

    Antwort

    t = [(x̄₁ − x̄₂) − 0] / √(s₁²/n₁ + s₂²/n₂).

  190. Karte 190

    Frage

    How should a two-mean test p-value be interpreted?

    Antwort

    Assuming the population means are equal, it is the probability of a sample-mean difference at least as extreme as observed, standardized in the direction of Hₐ.

  191. Karte 191

    Frage

    When is the sampling distribution of x̄ approximately normal?

    Antwort

    When the population is approximately normal or the random sample is large enough for the central limit theorem to apply.

  192. Karte 192

    Frage

    What conditions justify a one-sample t-interval?

    Antwort

    Random data; independence, checked with n ≤ 10% of the population when sampling without replacement; and for the Normal/Large Sample condition, n ≥ 30 is sufficient, while n < 30 requires sample data with no strong skewness or outliers.

  193. Karte 193

    Frage

    How does increasing sample size affect a confidence interval for μ?

    Antwort

    It lowers the standard error and usually narrows the interval when confidence level and variability stay comparable.

  194. Karte 194

    Frage

    What is the one-sample t-test statistic?

    Antwort

    t = (x̄ − μ₀) / (s/√n), with n − 1 degrees of freedom.

  195. Karte 195

    Frage

    A t-test fails to reject H₀. What should the conclusion avoid?

    Antwort

    Avoid saying H₀ is true; say the data do not provide convincing evidence for Hₐ.

  196. Karte 196

    Frage

    When is x̄₁ − x̄₂ approximately normal?

    Antwort

    When both populations are approximately normal or both independent random samples are large enough for normal approximations.

  197. Karte 197

    Frage

    What conditions justify a two-sample t-interval?

    Antwort

    Independent random samples or randomized groups; each sample no more than 10% of its population when sampling without replacement; and for the Normal/Large Sample condition, both sample sizes ≥ 30 are sufficient, while either sample below 30 requires sample data with no strong skewness or outliers.

  198. Karte 198

    Frage

    A 95% interval for μ₁ − μ₂ is (−7.2, −1.4). What does it support?

    Antwort

    μ₁ is plausibly 1.4 to 7.2 units lower than μ₂; the interval supports a negative difference.

  199. Karte 199

    Frage

    What sample-shape condition is checked for a two-sample t-test with small samples?

    Antwort

    Both sample distributions should be free of strong skewness and outliers unless both populations are known to be approximately normal.

  200. Karte 200

    Frage

    A randomized experiment finds a significant difference in mean response. What can random assignment support?

    Antwort

    A cause-and-effect conclusion for units like those studied, assuming the experiment was well designed.

  201. Karte 201

    Frage

    A population has μ = 40. What does μₓ̄ = 40 mean for samples of size 25?

    Antwort

    Across all random samples of 25, the average sample mean is 40.

  202. Karte 202

    Frage

    How is a matched-pairs confidence interval analyzed?

    Antwort

    Compute one difference for each pair, then use a one-sample t-interval on the population mean difference.

  203. Karte 203

    Frage

    A 95% confidence interval for μ is (18.2, 21.7). What does it say about μ = 22?

    Antwort

    The interval excludes 22, providing evidence against μ = 22 in a two-sided test at α = 0.05.

  204. Karte 204

    Frage

    Which observations enter a matched-pairs t-test?

    Antwort

    The within-pair differences, not the two original columns treated as independent samples.

  205. Karte 205

    Frage

    A test reports p-value 0.032. At which common levels is it significant: 0.05 or 0.01?

    Antwort

    Significant at 0.05, but not at 0.01.

  206. Karte 206

    Frage

    If μ₁ − μ₂ = 5, where is the sampling distribution of x̄₁ − x̄₂ centered?

    Antwort

    At 5.

  207. Karte 207

    Frage

    Does the standard AP two-sample t procedure require equal population variances?

    Antwort

    No. It uses separate sample variances in the standard error rather than pooling them.

  208. Karte 208

    Frage

    What two changes usually widen a confidence interval for μ₁ − μ₂?

    Antwort

    Higher confidence or smaller sample sizes.

  209. Karte 209

    Frage

    Why must the order x̄₁ − x̄₂ match the order μ₁ − μ₂ in the hypotheses?

    Antwort

    Reversing the order reverses the sign and changes the direction of the claim.

  210. Karte 210

    Frage

    A two-sample test with Hₐ: μ₁ > μ₂ fails to reject H₀. What conclusion is valid?

    Antwort

    There is not convincing evidence that μ₁ exceeds μ₂.

  211. Karte 211

    Frage

    A population has σ = 18 and random samples have n = 36. What is σₓ̄?

    Antwort

    3, because 18/√36 = 3.

  212. Karte 212

    Frage

    Why is a t distribution used for inference about a mean when σ is unknown?

    Antwort

    Replacing σ with the sample standard deviation s adds uncertainty, which the heavier-tailed t distribution accounts for.

  213. Karte 213

    Frage

    What conditions justify a one-sample t-test?

    Antwort

    Random data; independence, checked with n ≤ 10% of the population when sampling without replacement; and for the Normal/Large Sample condition, n ≥ 30 is sufficient, while n < 30 requires sample data with no strong skewness or outliers.

  214. Karte 214

    Frage

    What distinguishes a two-sample means procedure from a matched-pairs procedure?

    Antwort

    Two-sample procedures use independent groups; matched-pairs procedures analyze linked observations through their differences.

  215. Karte 215

    Frage

    How are degrees of freedom handled for a two-sample t procedure?

    Antwort

    Technology usually uses an approximation based on both sample variances and sizes; a conservative fallback uses the smaller of n₁ − 1 and n₂ − 1.

  216. Karte 216

    Frage

    What type of variables belong on a scatterplot?

    Antwort

    Two quantitative variables measured on the same observational units.

  217. Karte 217

    Frage

    What does the correlation coefficient r describe?

    Antwort

    The direction and strength of a linear relationship between two quantitative variables.

  218. Karte 218

    Frage

    What does ŷ = a + bx represent?

    Antwort

    A linear regression model predicting response y from explanatory variable x.

  219. Karte 219

    Frage

    What is a residual?

    Antwort

    Observed response minus predicted response: residual = y − ŷ.

  220. Karte 220

    Frage

    What makes a regression line the least-squares line?

    Antwort

    It minimizes the sum of squared residuals.

  221. Karte 221

    Frage

    What four features should a scatterplot description address?

    Antwort

    Direction, form, strength, and unusual features such as outliers or clusters.

  222. Karte 222

    Frage

    What values can r take?

    Antwort

    Any value from −1 to 1, inclusive.

  223. Karte 223

    Frage

    How is the slope b interpreted in context?

    Antwort

    For each one-unit increase in x, the predicted value of y changes by b units on average.

  224. Karte 224

    Frage

    What does a positive residual mean?

    Antwort

    The observed response is above the model's predicted response.

  225. Karte 225

    Frage

    What is the least-squares slope formula?

    Antwort

    b = r(sᵧ/sₓ).

  226. Karte 226

    Frage

    A scatterplot trends downward from left to right. What direction is the association?

    Antwort

    Negative: larger x-values tend to occur with smaller y-values.

  227. Karte 227

    Frage

    Why can r be near 0 even when two variables are strongly related?

    Antwort

    Correlation measures only linear association, so a strong curved relationship can have r near 0.

  228. Karte 228

    Frage

    How is the intercept a interpreted in context?

    Antwort

    It is the predicted response when x = 0, provided x = 0 is meaningful and within the data's scope.

  229. Karte 229

    Frage

    A model predicts 18, and the observed response is 21. What is the residual?

    Antwort

    3, because 21 − 18 = 3.

  230. Karte 230

    Frage

    How is the least-squares intercept found from the slope?

    Antwort

    a = ȳ − bx̄.

  231. Karte 231

    Frage

    What makes a linear association look strong?

    Antwort

    The points lie close to a straight-line pattern, regardless of whether the slope is steep or shallow.

  232. Karte 232

    Frage

    Does r have measurement units?

    Antwort

    No. Correlation is unitless because it is based on standardized values.

  233. Karte 233

    Frage

    For ŷ = 12 + 2.5x, what is predicted when x = 4?

    Antwort

    22, because 12 + 2.5(4) = 22.

  234. Karte 234

    Frage

    What residual-plot pattern supports using a linear model?

    Antwort

    Random scatter around zero with no clear curve, trend, or changing spread.

  235. Karte 235

    Frage

    What does r² measure in simple linear regression?

    Antwort

    The proportion of variation in the response variable explained by its linear relationship with the explanatory variable.

  236. Karte 236

    Frage

    A scatterplot shows a strong association. Does that establish causation?

    Antwort

    No. A scatterplot alone cannot rule out confounding or other explanations.

  237. Karte 237

    Frage

    Why should unusual points be checked before interpreting r?

    Antwort

    Correlation is not resistant; an outlier or influential point can change r substantially.

  238. Karte 238

    Frage

    Why is extrapolation risky?

    Antwort

    The relationship observed over the data range may not continue beyond that range.

  239. Karte 239

    Frage

    A point lies below the regression line. What sign is its residual?

    Antwort

    Negative, because observed y is less than predicted ŷ.

  240. Karte 240

    Frage

    Which point always lies on a least-squares regression line with an intercept?

    Antwort

    The point (x̄, ȳ).

  241. Karte 241

    Frage

    Which variable goes on each axis of a scatterplot used for prediction?

    Antwort

    The explanatory variable goes on the horizontal x-axis; the response variable goes on the vertical y-axis.

  242. Karte 242

    Frage

    What happens to r if the roles of x and y are swapped?

    Antwort

    Nothing. Correlation is symmetric.

  243. Karte 243

    Frage

    What is interpolation?

    Antwort

    Predicting a response for an x-value within the range of observed explanatory values.

  244. Karte 244

    Frage

    A residual plot has a clear U-shape. What is the correction?

    Antwort

    Do not treat the linear model as adequate; the curved pattern shows systematic structure remains.

  245. Karte 245

    Frage

    A regression has r² = 0.64. What does this mean?

    Antwort

    About 64% of the variation in the response is explained by its linear relationship with the explanatory variable.

  246. Karte 246

    Frage

    What is an outlier in a scatterplot?

    Antwort

    A point that falls away from the overall pattern of the other points.

  247. Karte 247

    Frage

    What happens to r when x is converted from centimeters to meters?

    Antwort

    It stays the same because multiplying by a positive constant does not change standardized linear association.

  248. Karte 248

    Frage

    When can a regression relationship support a causal conclusion?

    Antwort

    Only when the data come from a well-designed randomized experiment and the conclusion matches its scope.

  249. Karte 249

    Frage

    What units does a residual use?

    Antwort

    The same units as the response variable y.

  250. Karte 250

    Frage

    What is an influential point in regression?

    Antwort

    A point whose removal substantially changes the fitted regression line or another key regression result.

Five connected statistical stages show observations becoming a distribution, a sample, a probability curve, and a regression scatterplot.

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