Behavioral Research & Statistics for Psychology Beginners

Name: Behavioral Research & Statistics for Psychology Beginners
Rating: 4.6 (11 reviews)

For the “not-a-math person” and visual learners - Ideas before equations -

Created byKeith Gissubel

Last updated 5/2026

English

What you'll learn

Understand and apply research and statistical terminology in the behavioral sciences.
Calculate and interpret measures of central tendency, variability, and Z-score.
Grasp the fundamental principles of behavioral research and statistics.
Describe key research methods, including experiments, case studies, and surveys.
Analyze data using visual tools like histograms, scatterplots, and frequency distributions.
Identify and address biases in research design, such as sampling and experimenter bias.
Evaluate the strength and limitations of research methods and statistical findings.
Design a simple experiment with clearly defined variables and operational definitions

Course content

5 sections • 23 lectures • 2h 18m total length

Welcome!3:34
Taking This Course with Maximum Impact5:05
Build foundational skills in behavioral research and statistics with clear term explanations, practical calculations, and downloadable practice sheets that reinforce learning through spaced learning.
What We Cover & The Scientific Attitude9:47
Master behavioral research and statistics essentials, including mean, median, mode, normal distribution, correlation versus causation. Develop a scientific attitude with curiosity, skepticism, and humility to evaluate research design and data.

What is Behavioral Research? Overview of Methods4:28
Learn three descriptive research methods—survey, case study, and naturalistic observation—through real-world examples and note that experiments alone reveal cause‑and‑effect, with the next video designing one.
Experiments - Basic Components8:31
Explore basic experiment components, including the manipulated variable, the independent and dependent variables, control groups, and random assignment, plus hypotheses, operational definitions, and replication.
Confounding Variables8:20
Identify and control confounding variables to ensure the dependent variable reflects the manipulated temperature, and explore single and double blind designs and the placebo effect.
Samples and Populations8:23
Explore how samples relate to the population, why random sampling reduces bias and false consensus effect, and when stratified or convenience sampling affects generalizability in behavioral research.

Collecting Data3:21
Classify data as nominal, ordinal, interval, or ratio to guide analysis, using zero meaning, and examples like color, gender, temperature, and money, with SPSS and RStudio in mind.
Design Your Own Experiment!
Measures of Central Tendency7:08
Explore the center of data with mean, median, and mode, and learn to compute them for a data set and interpret an example mean of 10.2.
Measures of Variability9:10
Explore measures of variability—range, variance, and standard deviation—and learn how standard deviation reflects how individual scores deviate from the mean, using a step-by-step example with sum of squares.
Standard Deviation, The Raw-Score Formula5:25
Apply raw score formula for standard deviation using sum of squared x's, sum of x, and n; include a needs table. Know it's the average distance from the mean.
Mean and Standard Deviation
Visualizing the Standard Deviation1:53
The Normal Curve8:44
Explore how the normal curve, or bell curve, reveals where most people fall, and compare mean, median, and mode while examining standard deviation and the raw score formula.
Create a Histogram
Z-Score Introduction9:43
Z-Scores pt. 28:15
Master z-scores in psychology by calculating how many standard deviations a score is from the mean and reversing the formula to recover scores from z values on the normal curve.
Z-Score pt.2
Z-Scores
Skewed Distribution4:47
Explore skewed distributions, including left and right skew, and how they shift the mean, median, and the mode within a frequency distribution.

What are Inferential Statistics?2:41
Correlation and Causation9:02
Examine well-known correlations and why correlation is not causation, and learn to interpret scatter plots using Pearson's r to gauge positive and negative relationships.
Spurious and Illusory Correlations2:26
Explore spurious correlations, apparent links between unrelated variables, and illusory correlations, perceived patterns in randomness that people mistake for real relationships.
Normal Curves and Z-Scores9:31

Designing Your First Experiment1:42
Reverse engineer a study from the reported results, identifying hypothesis direction, variables, research method, confounds, sampling, operational definitions, and p value for instrumental music and memory.
My Reversed Experiment4:05
Next Steps and Course 2 Teaser2:40
Learn to reverse engineer study designs, spot bogus claims, and distinguish correlational findings from causality, with a teaser for course 2 on professional research, statistics, and papers.

Requirements

No prior course work in psychology, research, or statistics required.

Description

This course is designed to give psychology students peace of mind when statistics start to feel overwhelming or confusing.

We do calculations in this course, of course, but we begin with the ideas first. You’ll learn what these statistics mean, why they exist, and how to work through them step by step, rather than memorizing procedures without understanding.

What you’ll learn:

How behavioral research is designed and conducted
How to think clearly about variables, samples, and experiments
What standard deviation and variability actually represent
How z-scores and the normal curve work (and why they matter)
How to interpret statistical results without panic or guesswork

This course is for you if:

You’re a psychology student who struggles with statistics
You consider yourself “not a math person”
You learn best through explanations, visuals, and examples
You want understanding before equations

This course is not for you if:

You’re looking for advanced inferential statistics
You want heavy math, proofs, or abstract theory
You already feel very confident in statistics

This course is meant to be taken slowly and thoughtfully. Pause, rewind, and rewatch when needed --- the goal is understanding, not speed.

I was in your shoes. I declared psychology as a major and suddenly found myself sitting in a statistics course thinking, “But I’m not a math person… this is going to suck.”

Because I couldn’t rely on memorizing formulas the way some classmates could, I had to translate everything into clear, visual concepts instead. That shift didn’t just help me survive, it moved me to the top of my class. The following semester, my statistics professor asked me to be her teaching assistant.

More than 20 years later, I’ve taught research methods and statistics to thousands of students, from complete beginners to PhD-level analysis.If you want statistics explained like a human being teaches it -ideas before equations- you’re in the right place.

Who this course is for:

Psychology students, high school to master's level, eager to master behavioral research and statistics.

Behavioral Research & Statistics for Psychology Beginners

What you'll learn

Explore related topics

Course content

Welcome and Foundations3 lectures • 18min

Research Basics4 lectures • 30min

Descriptive Statistics9 lectures • 58min

Inferential Statistics4 lectures • 24min

Applying What You've Learned3 lectures • 8min

Requirements

Description

Who this course is for: