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DESIGN AND ANALYSIS OF PSYCHOLOGICAL EXPERIMENTS I

PSYCH 610
과목 설명

Reliability, validity, one-sample t-test, independent-samples t-test, simple and multiple regression, effect size indicators, analysis of variance (ANOVA), analysis of covariance (ANCOVA), case analysis, model assumptions, transformations, polynomial regression, simple mediation, and moderated mediation.

선수과목

Consent of instructor

충족 요건
학점

미보고

개설 시기

미보고

평점
3.51

-1.69% 과거 데이터 대비

수료율
100%

1.71% 과거 데이터 대비

A 비율
51.11%

-13.29% 과거 데이터 대비

학급 규모
45

70.53% 과거 데이터 대비

Cumulative Grade Distribution

강사 (2026 Summr)

다음 사이트의 평점순으로 정렬 Rate My Professors

유사 과목

BASIC STATISTICS FOR PSYCHOLOGY

PSYCH 210

Measures of central tendency, variability; probability, sampling distributions; hypothesis testing, confidence intervals; t-tests; Chi-square; regression and correlation (linear) and introduction to analysis of variance (1-way).

DESIGN AND ANALYSIS OF PSYCHOLOGICAL EXPERIMENTS II

PSYCH 710

Statistical power, paired-samples t-test, within-subjects ANOVA, mixed models, mediation in within-subjects designs, contrast analysis (= the analysis of categorical predictors with 3 or more levels), multilevel modeling, linear mixed-effects models, restricted maximum likelihood, signal detection theory, logistic regression, exploratory factor analysis, missing data.

INTRODUCTION TO THE DESIGN OF EDUCATIONAL EXPERIMENTS

EDPSYCH 762

Classical experimental designs and their application to educational research, factorial treatment arrangements, confounding, repeated measures design, and related topics.

DESIGN AND ANALYSIS OF BIOLOGICAL STUDIES

ANSCI 865

Experimental design and proper data analysis are critical processes for scientific research. Planning and performing research studies have statistical implications that influence how results are interpreted. Learn the fundamentals of generalized linear models, experimental design, and data analysis using common examples from biological studies.

STATISTICAL METHODS APPLIED TO EDUCATION II

EDPSYCH 761

Analysis of variance and covariance, multiple linear regression; chi-square and various nonparametric techniques.