Khan AcademyFree Video

Statistical Study Design: Free Course

Free Khan Academy video course on Statistical Study Design. Study all 13 source recordings with an on-site lesson list and completion tracking.

Every occurrence follows the published source playlist order; original titles, supplemental clips and literal repeated entries are retained.

Video 1 of 13 2:11

Identifying a sample and population | Study design | AP Statistics | Khan Academy

Before you start

Basic arithmetic and familiarity with tables and graphs are helpful. More advanced probability or inference topics assume the prerequisite methods shown in the recordings.

About this course

Reliable statistical conclusions begin with how observations are collected. This course examines populations, samples, bias, random sampling and the distinction between observation and experiment. Study the complete public source playlist from Khan Academy in English, with all 13 recordings available in the on-site classroom. Lessons retain their original titles and source order, including worked examples, introductions and repeated entries.

Course at a glance

Provider / Teaching team Khan Academy
Platform YouTube · Khan Academy
Access Free Video
Level Beginner
Language English
Videos 13
Video duration 1h 11m · allow extra time for practice
Format Self-paced recorded training
Certificate Not included with video viewing

What you’ll learn

  • Identify the target population and observed sample.
  • Recognize undercoverage and other survey biases.
  • Distinguish random sampling from the design of an experiment.
  • Assess generalization and causal claims using the study design.

Skills you’ll gain

  • Sampling
  • Survey bias
  • Experimental design
  • Causal reasoning

Course Overview

The opening examples identify the population a question concerns and the sample actually observed. Survey coverage and other sources of bias explain why a large dataset can still misrepresent that population. Random-sampling techniques are then considered as deliberate design choices. The course distinguishes observational studies from experiments and uses worked examples to make the difference concrete. Matched-pairs design introduces a way to organize comparisons when observations are related. The final lessons test proposed conclusions: whether a finding can be generalized and whether a causal statement is supported are separate questions. The orbital-speed example and other applications remain in their source positions as practice with study reasoning. Your goal is to explain the relationship between a design choice and the claim it permits, rather than merely attach a study-type label.

How to study the course

  • Videos 1–3: this part of the source list includes “Identifying a sample and population” through “Examples of bias in surveys”. Define the question and the observations. Keep a brief working note, revisit an unclear explanation and test one example before moving to another part of the material.
  • Videos 4–6: this part of the source list includes “Example of under coverage introducing bias” through “Techniques for random sampling and avoiding bias”. Check the assumptions behind a method. Keep a brief working note, revisit an unclear explanation and test one example before moving to another part of the material.
  • Videos 7–9: this part of the source list includes “Types of statistical studies” through “Worked example identifying observational study”. Connect a calculation with a plain-language interpretation. Keep a brief working note, revisit an unclear explanation and test one example before moving to another part of the material.
  • Videos 10–13: this part of the source list includes “Impact of mass on orbital speed” through “Can causality be established from this study?”. Describe uncertainty and limits of a conclusion. Keep a brief working note, revisit an unclear explanation and test one example before moving to another part of the material.

Who is this for?

This course suits students, analysts and readers who want to understand the specific statistical methods in the course. It also provides a recorded reference for revisiting a topic after an earlier lesson or study attempt. Choose examples appropriate to your background and allow time to work through the method instead of judging understanding only by how familiar the terminology sounds.

Before you start

Basic arithmetic and familiarity with tables and graphs are helpful. More advanced probability or inference topics assume the prerequisite methods shown in the recordings.

Put the lessons into practice

Draft a fictional survey question and specify who belongs to its target population, how participants would be selected and who might be missed. Then outline an experiment on a different question, including a comparison and a reason for using matched pairs if appropriate. Write one conclusion each design could support and one stronger conclusion it could not justify.

This optional study activity is provided by WikiFree for independent practice. Keep your working notes and use the relevant classroom recording to check a step, definition or interpretation. It is not an instructor-marked assignment.

Certificate / Assessment

Watching the public videos and using WikiFree completion tracking does not award a certificate, academic credit, an examination voucher or instructor assessment. Use your practice output to review what you can explain and repeat independently. The recorded lessons provide study material; completion tracking records your progress through that material.

Related courses for your next step

Compare course focus, level and study time
Compare the published course outlines. A lower level is a preparation option, not a required prerequisite.
CourseLevelFocusStudy time
This course — Statistical Study Design: Free CourseBeginnerSampling · Survey bias · Experimental design1h 11m of video; practice time is additional
Sampling Distributions: Free CourseIntermediateSampling distributions · Standard error · Central limit theorem1h 42m of video; practice time is additional
Survey Design and Data Interpretation: Free CourseBeginnerData interpretation · Statistical reasoning · Uncertainty1h 32m of video; practice time is additional
Statistical Hypothesis Testing: Free CourseIntermediateHypothesis tests · P-values · Statistical power2h 3m of video; practice time is additional
Free Simplilearn Course: Minitab and Statistical Quality AnalysisBeginnerStatistical Tools · Data Graphics · Quality Analysis2h 3m of video; practice time is additional

Frequently asked questions

Is this course free to watch?

Yes. The public source videos are available in the WikiFree classroom. Video viewing does not include separately priced tools, hardware, memberships or a credential.

How long does the course take?

The 13 source video occurrences total approximately 1h 11m. Allow additional time for pausing, notes, practice and revisiting an explanation.

What background do I need?

Basic arithmetic and familiarity with tables and graphs are helpful. More advanced probability or inference topics assume the prerequisite methods shown in the recordings.

Does completing the videos award a certificate?

No. Video viewing and WikiFree progress tracking do not award a certificate, academic credit or an exam voucher.

Can I study on a phone?

Yes. The classroom supports a responsive player and searchable lesson list. A larger screen or a suitable practice environment can help with detailed calculations, diagrams and software examples.

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Provider: Khan Academy. Videos play from the Khan Academy channel on YouTube.

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