AP Statistics: 250 Key Terms, Conditions and Traps
Most lost points come from checking the wrong condition, not from forgetting a formula.
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| Front | Back |
|---|---|
| Categorical variable | Meaning: A variable that places each individual into one of several groups. Detail: Summarised with counts and percentages, displayed with bar charts and pie charts. Watch for: A variable stored as a number can still be categorical, such as a zip code or a jersey number. |
| Distribution | Meaning: The values a variable takes and how often it takes them. Detail: Described by shape, centre, spread and unusual features, in context. Watch for: A description that names only the centre is incomplete and loses credit. |
| Dotplot | Meaning: A display that shows every observation as a dot above its value on a number line. Detail: Useful for small data sets because individual values remain visible. Watch for: It becomes unreadable for large data sets. A histogram is the better choice. |
| Mean | Meaning: The arithmetic average, found by summing the values and dividing by the number of values. Detail: It is the balance point of the distribution. Watch for: It is not resistant: a single extreme value shifts it noticeably. |
| Range | Meaning: The difference between the maximum and the minimum. Detail: A single number, not a pair of numbers. Watch for: Reporting the range as an interval such as from 3 to 19 does not answer the question asked. |
| Outlier | Meaning: An observation that falls well outside the overall pattern of the data. Detail: Identified by the 1.5 times IQR rule or by lying far from the rest in a display. Watch for: An outlier is not automatically an error and should not be deleted without a reason. |
| Percentile | Meaning: The percentage of observations that fall at or below a given value. Detail: Read from a cumulative relative frequency graph or computed from ranks. Watch for: A percentile is a position, not a score. The 90th percentile is not a score of 90. |
| Effect of adding a constant | Meaning: What happens to a distribution when the same number is added to every value. Detail: Measures of centre and position shift by that number. Measures of spread do not change. Watch for: Adding a constant does not change the shape or the standard deviation. |
| Density curve | Meaning: A smooth curve that describes the overall pattern of a distribution. Detail: It is always on or above the horizontal axis and the total area beneath it equals one. Watch for: Areas give proportions. The height of the curve is not a probability. |
| Normal distribution | Meaning: A symmetric, bell-shaped density curve described by its mean and standard deviation. Detail: The mean locates the centre and the standard deviation locates the inflection points. Watch for: Bell-shaped is not the same as normal. Check the context before assuming normality. |
| Comparing distributions | Meaning: Describing two or more distributions relative to each other. Detail: Compare shape, centre, spread and unusual features, using explicit comparative language. Watch for: Describing each distribution separately is not a comparison and loses credit. |
| Explanatory variable | Meaning: The variable that may help explain or predict changes in another variable. Detail: It is plotted on the horizontal axis of a scatterplot. Watch for: Calling it the explanatory variable does not establish that it causes anything. |
| Correlation | Meaning: A number measuring the strength and direction of a linear relationship. Detail: It lies between negative one and one, and it has no units. Watch for: It measures only linear association. A strong curved relationship can give a correlation near zero. |
| Residual | Meaning: The difference between an observed response and the value predicted by the line. Detail: Computed as observed minus predicted, so a positive residual means the line underpredicted. Watch for: Reversing the order of the subtraction reverses every sign. |
| Influential point | Meaning: An observation that substantially changes the regression line if it is removed. Detail: Points with extreme explanatory values have the greatest influence on the slope. Watch for: An outlier in the response direction may have a large residual yet little influence. |
| Two-way table | Meaning: A table showing counts for the combinations of two categorical variables. Detail: Row and column totals give the marginal distributions. Watch for: Comparing raw counts across rows of different sizes leads to a wrong conclusion. |
| Population | Meaning: The entire group of individuals about which information is wanted. Detail: It must be defined before a sample can be judged representative. Watch for: It is the group of interest, not the group that happens to be available. |
| Simple random sample | Meaning: A sample chosen so that every group of the given size has an equal chance of being selected. Detail: Implemented with a random number generator or a table of random digits. Watch for: Giving every individual an equal chance is not enough. Every possible group must be equally likely. |
| Bias | Meaning: A systematic tendency for a study to favour certain outcomes. Detail: It shifts results in a consistent direction and is not reduced by taking a larger sample. Watch for: Bias is a property of the method, not of any single sample result. |
| Observational study | Meaning: A study that records data without attempting to influence the responses. Detail: It can establish association but not causation. Watch for: Adjusting for known variables does not turn an observational study into an experiment. |
| Statistically significant result | Meaning: A difference too large to be explained plausibly by chance alone. Detail: In an experiment, it supports the conclusion that the treatment caused the difference. Watch for: Significant does not mean large or important in a practical sense. |
| Conditional probability | Meaning: The probability of an event given that another event has occurred. Detail: Found by dividing the probability that both occur by the probability of the given event. Watch for: The order of the two events matters. The two conditional probabilities are generally different. |
| Simulation | Meaning: Imitating a chance process using random digits or a random device. Detail: Used when a probability is hard to compute directly. Watch for: A description must state how digits are assigned, what one trial is, and what is recorded. |
| Standard error | Meaning: An estimate of the standard deviation of a statistic, computed from sample data. Detail: It is used when the population parameter needed for the exact formula is unknown. Watch for: It estimates variability in the statistic, not variability in the data. |
| Sampling distribution of a difference of proportions | Meaning: The distribution of the difference between two independent sample proportions. Detail: Its mean is the difference of the population proportions. Watch for: Variances add even though the means subtract. |
| Independence condition | Meaning: The requirement that observations do not influence each other. Detail: Met by random sampling with replacement, or approximately under the 10 percent condition. Watch for: It also requires the two samples to be independent when groups are compared. |
| t distribution | Meaning: A family of distributions used when the population standard deviation is unknown. Detail: It is symmetric about zero with heavier tails than the normal distribution. Watch for: Its shape depends on the degrees of freedom, so a single table row is not enough. |
| Type I error | Meaning: Rejecting a null hypothesis that is actually true. Detail: Its probability equals the significance level. Watch for: It is the error of finding an effect that is not there. |
| Chi-square goodness of fit test | Meaning: A test comparing observed counts in one categorical variable with a claimed distribution. Detail: Degrees of freedom equal one less than the number of categories. Watch for: It uses counts, not percentages. Converting to percentages first invalidates the test. |
| Inference for the slope | Meaning: Testing or estimating the slope of a population regression line. Detail: Uses a t distribution with degrees of freedom equal to the sample size minus two. Watch for: Rejecting the null hypothesis of zero slope does not establish causation. |
About this deck
A student who can state the central limit theorem still loses the point if they apply it to the data instead of to the sample mean. The same is true of the two standard errors for a proportion: the interval uses the sample value and the test uses the hypothesised one, and using the wrong one quietly changes the answer. Statistics is not short on definitions. It is short on students who can say which condition a procedure needs and why. This deck is 250 cards, one term per card, with the back cut into three fixed lines. "Meaning" defines the term in a sentence. "Detail" gives the formula in words, the condition it needs, or what it is used for. "Watch for" names the confusion that costs the point. The sections follow the shape of the course: exploring data, relationships, collecting data, probability, sampling distributions, and inference. No worked arithmetic appears anywhere. Procedures are described in words, because on the free-response section the credit sits in naming the procedure, checking its conditions and stating the conclusion in context, and a calculator handles the rest. Once the deck is on a spaced-repetition schedule, the terms you can already place stop coming back and the pairs you keep reversing return until they stop being a coin flip.
Frequently asked
- What is in each section of the deck?
- Exploring data has 45 cards, relationships 40, collecting data 40, probability 45, sampling distributions 35, and inference 45, for 250 in total. Every card carries section and subtopic tags, so you can drill only the sampling distributions, only the study designs, or only the chi-square procedures.
- Does it help with the free-response section?
- It covers the parts of a free-response answer that are pure recall: which procedure applies, which conditions it needs, and how a conclusion must be worded in context. It does not replace writing full answers, because the marks for organisation and communication only come from practice on paper.
- Is a calculator needed alongside the deck?
- Not for the cards themselves, which contain no arithmetic. You will still need one for actual problems, and knowing which calculator function corresponds to which procedure is worth practising separately. The deck tells you which procedure to reach for and what has to be checked first.
- Can I import the whole deck on the free plan?
- Yes. Importing a saved deck runs no new AI generation and spends no AI credits, so the free plan imports all 250 cards. You can study, edit and delete them afterwards.
- Will importing it twice create duplicates?
- No. Cards you already have are skipped and only cards added in a revision come through. Including re-imports after deleting it, one official deck can be imported three times per account.
- Can I use it on the web and in the mobile app?
- Yes. The deck is added to your account rather than to a device, so the same cards and the same progress are there on the web, on iOS and on Android.
- Can I edit the cards after importing?
- Yes. Imported cards are yours: you can edit both sides, delete cards you do not need, change tags, and move cards to another deck.
No official exam questions are reproduced. Every card was written for this deck.Advanced Placement is a trademark of College Board. This deck is not produced, endorsed or approved by College Board.Editorial reference date 2026-08-31.