Statistics in Psychology: Central Tendency, Correlation, and Distribution

Central tendency, measure of

Ways to describe the "center" of a data set. Includes mean, median, and mode.

Correlation

A statistical relationship between two variables. Can be positive, negative, or none.

Correlation coefficient (r)

Number between -1.00 and +1.00 that shows strength/direction of a correlation. Closer to ±1 = stronger relationship. Closer to 0 = weaker relationship.

Descriptive statistics

Numbers that summarize and organize data (e.g., mean, median, mode, range).

Frequency distribution

Table/graph showing how often each value occurs in a data set.

Histogram

Bar graph of a frequency distribution.

Inferential statistics

Methods that allow researchers to make conclusions or generalizations about a population from sample data (e.g., t-test, p-values).

Mean

Average score (add all, divide by number). Sensitive to extreme scores.

Median

Middle score in an ordered data set. Less affected by outliers/skewed data.

Mode

Most frequently occurring score.

Negative correlation

One variable increases while the other decreases (inverse relationship).

Positive correlation

Both variables increase or decrease together (direct relationship).

Range

Difference between highest and lowest scores. A measure of variability.

Scatter diagram (scatter plot)

Graph showing individual data points for two variables; reveals correlation visually.

Skewed distribution

Distribution that is not symmetrical. Positively skewed = tail to the right (few high scores). Negatively skewed = tail to the left (few low scores).

Standard deviation (SD)

Measure of spread; shows average distance of scores from the mean. Larger SD = more variability.

Standard normal curve (normal distribution)

Bell-shaped, symmetrical curve where most scores cluster around the mean.

Statistics

Mathematical methods for analyzing data (includes descriptive and inferential).

Symmetrical distribution

Data balanced around the mean (e.g., normal curve).

t-test

Inferential test comparing the means of two groups to see if differences are statistically significant.

Type I error

False positive - saying a result is significant when it's not (rejecting a true null hypothesis).

Type II error

False negative - failing to find a real effect (accepting a false null hypothesis).

Variability, measure of

Ways of describing spread in data (range, variance, standard deviation).

z-score

Number that describes how far a data point is from the mean, measured in standard deviations.