Learn Statistics for Psychology: 40 Flashcards from Standard Deviation to Factor Analysis
Master psychology statistics with deck YS4685: 40 flashcards on z-scores, t-tests, ANOVA, effect size, power, regression and the central limit theorem.
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Research Methods Study Guide: Variables, Validity and Experimental Design in 59 Flashcards
Study research methods with 59 flashcards: independent and dependent variables, confounds, validity, Type I/II errors, p-hacking, preregistration and research ethics.
Most psychology students do not fail statistics because the maths is hard. They fail because forty terms arrive in three weeks and half of them sound alike — variance and standard deviation, alpha and p, standard deviation and standard error. Deck YS4685 — Statistics for Psychology (40 cards on Flip It) is deliberately definition-first for that reason: no formulas to grind, just the vocabulary you need before a formula means anything.
Study this deck: Statistics for Psychology
1 / 10Descriptive statistics
Tap the card for the answer · swipe right if you knew it, left if not
The whole deck in one sweep
Descriptive side: descriptive vs inferential statistics, mean, median, mode, range, variance, standard deviation, normal distribution, skewness, z-scores, the 68-95-99.7 rule, scatterplots. Inference: t-tests (independent and paired samples), ANOVA, chi-square, p-values, significance level, confidence intervals, one-tailed vs two-tailed tests, parametric vs non-parametric tests. Magnitude and design: effect size, Cohen's d, statistical power and what raises it. Relationships: correlation coefficient (Pearson's r) with the +1, -1 and 0 cases spelled out on their own cards, simple linear regression, multiple regression, R², factor analysis. Sampling theory: the central limit theorem, sampling distributions, standard error.
Ten cards that carry the rest
| Front | Back |
|---|---|
| Standard deviation | The square root of variance; the average distance of data points from the mean |
| Z-score | A standardised score showing how many standard deviations a value is from the mean; allows comparison across scales |
| 68-95-99.7 rule | About 68% of data within 1 SD of the mean, 95% within 2 SDs, 99.7% within 3 SDs |
| Paired samples t-test | Compares means of the same group at two times or under two conditions |
| ANOVA | Compares the means of three or more groups simultaneously |
| Cohen's d | Effect size for the difference between two means, expressed in standard deviation units |
| Statistical power | Probability a test detects an effect when a true effect exists; conventionally set at 0.80 |
| Coefficient of determination (R²) | How much variance in the dependent variable is explained by the independent variable(s); ranges 0 to 1 |
| Central limit theorem | The distribution of sample means approaches normal as sample size grows, whatever the population distribution |
| Standard error | The standard deviation of the sampling distribution; it measures the precision of a sample estimate |
Rewrite the p-value card before you memorise it
The deck defines the p-value as the probability that the observed results occurred by chance. That is the single most common misstatement in undergraduate statistics, and examiners hunt for it. The p-value is the probability of obtaining results at least as extreme as the observed ones, assuming the null hypothesis is true. It says nothing about the probability that chance produced your data, and nothing about the probability the null is true. Edit the back of that card now — you will meet the correct version again in every methods paper you read.
While you are in there, look at the power card. It lists a higher alpha as a way to increase power, which is arithmetically true and practically a trap: raising alpha buys power by accepting more false positives. Add that clause yourself.
Sequence it in three blocks
Do not shuffle all forty. Learn the eight descriptive cards to fluency first, because z-scores, effect sizes and standard error are all restatements of the standard deviation. Then take the inference block (t-test, ANOVA, chi-square, p, alpha, confidence interval) and for each one write down what data type it takes — that single column is what exam questions actually test. Correlation, regression and factor analysis come last: by then R² reads as a variance idea you already own rather than a new symbol.
For the design vocabulary that sits under these tests — independent variables, validity, confounds — pair this deck with the research methods deck.
Deck code: YS4685, in the Research Methods category on Flip It.
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