Psychological Statistics: Introduction and Basic Concepts

Flashcards covering the pioneers of psychological statistics, definitions of statistical processes, goals of psychology, and the distinctions between descriptive and inferential statistics.

Wilhelm Wundt

Known as the father of experimental psychology, he established the first psychology lab in Leipzig in $1879$, laying the foundations for controlled measurement.

James McKeen Cattell

A student of Wundt who introduced the term “mental tests” and founded major journals like Science and The Psychological Review.

Sir Francis Galton

An innovator in psychometrics, correlation, and regression whose work on human differences is the basis of modern quantitative psychology.

Ronald Fisher

He developed key inferential methods and p-values used in psychological research methodologies.

Karl Pearson

A pioneer who introduced correlation and chi-square statistical methods.

Jerzy Neyman

He created confidence intervals and formal hypothesis testing.

Lewis Thurstone

Known as the father of factor analysis, his method underpins the Big Five trait model for identifying underlying structure in personality and cognitive data.

Anne Anastasi

A pioneer in modern test theory and author of the foundational book Psychological Testing; honored with the National Medal of Science.

Lee Cronbach

Developed Cronbach’s alpha to assess internal consistency reliability and championed Generalizability Theory.

Jacob Cohen

Created effect-size measures like Cohen's d and Cohen’s kappa, while advocating for interpretation beyond p-values.

Dorothy C. Adkins

The first female president of the Psychometric Society and a leader in psychometrics and achievement testing.

Psychological Statistics

The application of statistical methods to analyze data from psychological research to understand and draw conclusions about human behavior, cognition, and emotions.

Statistics

A branch of mathematics dealing with the collection, organization, presentation, analysis, and interpretation of numerical data for making effective decisions.

Collection of Data

The process of gathering numerical information through interviews, questionnaires, experiments, observation, or documentary analysis.

Presentation of Data

The exposition and arrangement of data in appropriate tables and graphs such as bar graphs, frequency polygons, or pie graphs.

Analysis of Data

Describing the properties, characteristics, behavior, or possible correlations of variables within the gathered data.

Interpretation of Data

Explaining the meaning of statistical findings to form valid conclusions and inferences, often involving testing the significance of results.

Descriptive Statistics

A branch of statistics focused on summarizing and organizing data through numerical measures and graphical methods without making generalizations.

Mean

The average of a data set, calculated by summing all values and dividing by the number of values ($n$).

Median

The middle value when data is ordered from least to greatest; if the number of observations is even, it is the average of the two middle values.

Mode

The most frequently occurring value in a data set.

Range

The difference between the maximum and minimum values in a data set.

Variance

The average of the squared differences from the mean, indicating how much the values in the data set vary.

Standard Deviation

The square root of the variance, providing a measure of the average distance of each data point from the mean.

Frequency Distributions

A table that displays the frequency of various outcomes in a sample, often used to summarize categorical data.

Inferential Statistics

The branch of statistics that uses probability theory and data samples to make predictions, estimates, or generalizations about a larger population.