Survey Design and Data Interpretation: Free Course

About this course

Study Survey Design and Data Interpretation in this free English video course from Khan Academy. The classroom preserves all 15 published source recordings, totaling approximately 1h 32m, with their original lesson titles and sequence. The selected curriculum focuses on data interpretation, uncertainty and defensible conclusions. Use the videos to follow an explanation, examine an example and develop a study output you can check independently. The course title describes this recorded subject or learning track; your study can extend beyond watching through the practical activities below.

Course at a glance

What you’ll learn

• Follow the explanation and worked reasoning in “Measuring public opinion”, then describe the main idea in your own words.
• Follow the explanation and worked reasoning in “Generalizabilty of survey results example”, then describe the main idea in your own words.
• Follow the explanation and worked reasoning in “Techniques for random sampling and avoiding bias”, then describe the main idea in your own words.
• Follow the explanation and worked reasoning in “Can causality be established from this study?”, then describe the main idea in your own words.
• Connect examples across Survey Design and Data Interpretation by identifying the terms, assumptions and methods they use.
• Create a small independent practice output and check it against the relevant teaching explanation.

Skills you’ll gain

• Data interpretation
• Statistical reasoning
• Uncertainty
• Evidence

Course Overview

The source curriculum is presented as a complete recorded video edition of Survey Design and Data Interpretation. Representative lessons include “Measuring public opinion”, “Techniques for random sampling and avoiding bias” and “Data to justify experimental claims examples”. These recordings give concrete examples to revisit while building data interpretation, uncertainty and defensible conclusions. Their place in the lesson list is preserved, so you can return to a particular explanation without losing its source position. Introductions, demonstrations, examples, reviews and compilations remain included whenever they appear in the original playlist. Reading a lesson title is useful for locating a topic; working through its reasoning and checking a practice attempt is what makes the recording valuable for learning.

How to study the course

• Videos 1–3: this part of the source list includes “Measuring public opinion” through “Identifying a sample and population”. 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 4–7: this part of the source list includes “Generalizabilty of survey results example” 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 8–11: this part of the source list includes “Types of statistical studies” through “Correlation and causality”. 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 12–15: this part of the source list includes “Ways to represent data” through “Data to justify experimental claims examples”. 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

Create a small fictional dataset or study description suited to a method in the lessons. Define the question, describe how observations would be collected and apply the demonstrated technique. Explain the result without claiming more than the data support. Change one assumption, sample feature or data value and compare the conclusions. Record possible sources of bias or uncertainty. Finish with a short explanation of which statements are supported, which depend on assumptions and which would need additional evidence.

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.

Frequently asked questions

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