Full Flashcards for Statistics for the Behavioral Sciences

Statistics

The analysis and evaluation of scientific observations.

Descriptive Statistics

Statistics used to summarize and describe the characteristics of a specific data set.

Inferential Statistics

Statistics used to make generalizations or inferences about a larger population based on a sample.

Datum

A single measurement or observation.

Data

Multiple measurements or observations collected together.

Population

The entire set of individuals, items, or data points of interest in a study.

Population Parameter

A numeric characteristic that describes the entire population.

Sample

A subset of individuals selected from the population.

Sample Statistic

A characteristic that describes the sample data.

Scientific Method

The systematic process of gathering information in research.

Experimental Method

A method designed to demonstrate cause-and-effect relationships by controlling conditions.

Independent Variable (IV)

The variable manipulated by the researcher.

Randomization

The process of assigning participants to groups randomly to control for differences.

Dependent Variable (DV)

The variable that is measured and hypothesized to be affected by the IV.

Operational Definition

A clear description of how a variable is measured or defined in a study.

Quasi-Experimental Method

A method used when researchers lack full control over experimental conditions.

Correlational Method

A technique that measures the extent to which two variables change together.

Nominal Scale

A scale that represents identity or category, providing no information about rank.

Ordinal Scale

A scale that conveys rank or order but not the equal distance between ranks.

Interval Scale

A scale with consistent distances between values, lacking a true zero point.

Ratio Scale

The most informative scale with equidistant points and a true zero point.

Continuous Variable

A variable that can take on an infinite number of values between two points.

Discrete Variable

A variable measured in whole units or categories.

Quantitative Variable

Data representing amounts or counts.

Qualitative Variable

Data that describes labels, categories, or qualities.

SPSS

A statistical package for the social sciences used for data analysis.

Frequency

The number of times a score occurs in a data set.

Simple Frequency Distribution

A summary that organizes the frequency of scores into categories.

Cumulative Frequency (cf)

The sum of frequencies at or below a particular interval.

Relative Frequency (rf)

The proportion of total scores in an interval.

Percentile Point

The raw score value at or below which a specific percentage of scores fall.

Histogram

A bar-style graph used for continuous data, where bars touch and height represents frequency.

Frequency Polygon

A dot-and-line graph connecting midpoints of data intervals.

Bar Chart

A graph similar to a histogram but with non-touching bars to emphasize categories.

Pie Chart

A circular graph showing the proportion of total for each category.

Central Tendency

Describes the center of a distribution using measures such as mean, median, and mode.

Mean (M or μ)

The arithmetic average of a data set.

Median

The middle score in a distribution when ordered.

Mode

The value that occurs most frequently in a data set.

Range

The difference between the largest and smallest values in a data set.

Variance (σ² or s²)

The average squared distance from the mean.

Standard Deviation (σ or SD)

The square root of the variance, indicating how spread out scores are.

Empirical Rule

In a normal distribution, approximately 68% of scores fall within 1 SD of the mean.

Binomial Distribution

A distribution for trials with only two outcomes (Success/Failure).

Expected Value

The mean of a probability distribution.

Null Hypothesis (H₀)

The hypothesis that predicts no effect or relationship.

Alternative Hypothesis (H₁)

The hypothesis that predicts an effect or relationship exists.

Type I Error (α)

Rejecting the null hypothesis when it is actually true.

Type II Error (β)

Failing to reject the null hypothesis when it is false.

Power (1 - β)

The probability of correctly rejecting a false null hypothesis.

t-Test

A statistical test used when the population mean and variance are unknown.

Degrees of Freedom (df)

The number of values in the final calculation of a statistic that are free to vary.

Effect Size

A measure of the magnitude of a phenomenon.

ANOVA

Analysis of variance, used when comparing more than two groups.

Chi-Square Test (χ²)

A test for analyzing categorical data to assess relationships between variables.

Goodness-of-Fit Test

A Chi-Square test that assesses how well observed frequencies match expected frequencies.

Cramer’s V

A measure of effect size associated with the Chi-Square test for independence.

Regression Line

The best-fitting line used in linear regression to predict values.

Meta-Analysis

A statistical analysis that combines the results of multiple scientific studies.

Statistical Significance

A determination that an observed result is unlikely to have occurred by chance.