Standard deviation is a measure of variability that tells you how far scores in a data set typically fall from the mean; a small standard deviation means scores cluster tightly around the average, while a large one means scores are widely spread out.
Standard deviation is the go-to statistic for describing variability, which is how spread out a set of scores is. The mean tells you where the center of the data sits. Standard deviation tells you how far, on average, individual scores wander from that center. Two classes can both average 80% on a test, but if one class has a standard deviation of 3 points and the other has a standard deviation of 15, those are very different classes. The first is tightly packed around 80; the second has students scoring all over the place.
In AP Psychology, standard deviation does its heaviest lifting with the normal distribution. In a normal (bell-shaped) curve, about 68% of scores fall within one standard deviation of the mean and about 95% fall within two. That is exactly how IQ scores work in Topic 5.10. Most intelligence tests have a mean of 100 and a standard deviation of 15, so a score of 130 is two standard deviations above average. Standard deviation is the ruler that turns a raw score into a meaningful position on the curve.
Standard deviation anchors Topic 1.5 (Statistical Analysis in Psychology) in Unit 1, where descriptive statistics like mean, median, and measures of variability are core essential knowledge. It then comes back in Topic 5.10 (Psychometric Principles and Intelligence Testing) in Unit 5, because you cannot interpret an IQ score, define intellectual giftedness, or talk about the normal distribution of intelligence without it. It's also the foundation for z-scores and percentile interpretation. The revised AP Psych exam is heavy on data interpretation, especially in the Article Analysis Question (AAQ) and Evidence-Based Question (EBQ), so being able to read a standard deviation in a results table and say what it means about the data is a skill you'll actually use on test day.
Keep studying AP Psychology Unit 1
Mean (Unit 1)
Standard deviation is meaningless without the mean, because it literally measures average distance from the mean. The mean tells you the center; standard deviation tells you the spread. You need both to actually describe a data set.
Normal Distribution (Units 1 & 5)
The normal curve is carved up in standard deviation units. About 68% of scores fall within one SD of the mean and about 95% within two. This is why IQ scores (mean 100, SD 15) are so easy to interpret once you know the rule.
Z-Score (Unit 1)
A z-score is just a score expressed in standard deviation units. A z-score of +1 means one standard deviation above the mean. If you can compute a standard deviation, the z-score is one small step away.
Correlation Coefficient (Unit 1)
Both are descriptive statistics, but they answer different questions. Standard deviation describes spread within one variable, while a correlation coefficient describes the relationship between two variables. MCQs love swapping these in answer choices.
On multiple choice, standard deviation shows up in straightforward stems like "what does standard deviation measure?" or "what does a high standard deviation indicate about a data set?" The answer they want is always about variability or spread around the mean, with high SD meaning scores are widely dispersed. The trickier MCQs give you two distributions with the same mean and different SDs and ask you to compare them. On the free-response side, the AAQ (like the 2025 question on misinformation and memory) hands you a real study with a results section, and you may need to interpret means and measures of variability using appropriate psychological terminology. The EBQ can do the same with multiple sources. The move that earns points is interpretation, not calculation. You won't compute a standard deviation by hand, but you do need to say what a given SD tells you about the participants' scores.
Both measure variability, but range only uses two numbers (highest score minus lowest score), so one extreme outlier can blow it up. Standard deviation uses every score in the data set, measuring how far scores typically fall from the mean, which makes it a much more stable and informative picture of spread. If an AP question asks for the measure of how scores vary around the mean, the answer is standard deviation, not range.
Standard deviation measures variability, meaning how far scores in a data set typically fall from the mean.
A small standard deviation means scores cluster tightly around the mean, while a large standard deviation means scores are spread widely.
In a normal distribution, about 68% of scores fall within one standard deviation of the mean and about 95% fall within two.
IQ tests typically have a mean of 100 and a standard deviation of 15, so a score of 130 is two standard deviations above average.
Two data sets can have identical means but very different standard deviations, so always report both center and spread.
On the AAQ and EBQ, you interpret standard deviations from a results table rather than calculate them.
Standard deviation is a descriptive statistic that measures how much scores in a data set vary around the mean. It appears in Topic 1.5 (Statistical Analysis) and again in Topic 5.10, where it's used to interpret IQ scores on the normal distribution.
No. The exam tests interpretation, not computation. You need to explain what a given standard deviation says about a data set, like recognizing that a high SD means scores are widely spread, especially on the AAQ and EBQ free-response questions.
It means the scores are spread far from the mean, so the data is more variable and the mean is less representative of a typical score. A low standard deviation means scores are bunched close to the average.
Standard deviation describes the spread of an entire data set, while a z-score locates one individual score in standard deviation units. An IQ of 115 has a z-score of +1 because it sits exactly one standard deviation (15 points) above the mean of 100.
Intelligence test scores form a normal distribution with a mean of 100 and a standard deviation of 15, so standard deviation is what makes any individual score interpretable. It tells you whether a score is typical (within one SD) or unusual (two or more SDs from the mean).