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
Density curves turn the shape of a distribution into a probability model. This course develops normal distributions, percentiles, standardized scores and areas under curves. Study the complete public source playlist from Khan Academy in English, with all 14 recordings in the on-site classroom. Original lesson titles, source order and repeated entries are preserved.
Course at a glance
| Provider / Teaching team | Khan Academy |
|---|---|
| Platform | YouTube · Khan Academy |
| Access | Free Video |
| Level | Beginner |
| Language | English |
| Videos | 14 |
| Video duration | 1h 25m · allow extra time for practice |
| Format | Self-paced recorded training |
| Certificate | Not included with video viewing |
What you’ll learn
- Interpret area under a density curve.
- Relate percentiles to cumulative relative frequency.
- Calculate and compare z-scores.
- Use a normal table to find proportions and cutoffs.
Skills you’ll gain
- Normal distribution
- Density curves
- Percentiles
- Z-scores
Course Overview
The source combines qualitative normal-distribution reasoning with calculations using the standard normal table. Density-curve examples distinguish area from height and connect the positions of the mean and median with skewness. Percentiles and cumulative relative-frequency graphs express location within a distribution. Standardizing with a z-score then permits comparisons measured in standard-deviation units. Both lower-tail and upper-tail table examples are included, alongside inverse questions that ask for a cutoff corresponding to a percentile. Treat the normal distribution as a model whose suitability matters; an arbitrary dataset does not become normal simply because a standardized score can be calculated.
How to study the course
- Videos 1–3: this part of the source list includes “ck12.org normal distribution problems: Qualitative sense of normal distributions” through “Median, mean and skew from density curves”. 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 “Calculating percentile” through “Density Curves”. 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 8–10: this part of the source list includes “Finding z-score for a percentile” through “Analyzing a cumulative relative frequency graph”. 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 11–14: this part of the source list includes “ck12.org normal distribution problems: z-score” through “Threshold for low percentile”. 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
Choose a fictional normal model with a stated mean and standard deviation. Standardize two observations, find a lower-tail proportion and solve for a percentile cutoff. Sketch the corresponding shaded regions before using a table. Explain the difference between the height of the curve at a point and the probability represented by an interval.
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
- Explore a higher-level optionSampling Distributions: Free Course
Focus: Sampling distributions · Standard error
Intermediate - Compare another approachHigh School Statistics: Free Course
Focus: Descriptive statistics · Probability
Beginner - Explore a higher-level optionRandom Variables: AP Statistics: Free Course
Focus: Expected value · Random variables
Intermediate
Compare course focus, level and study time
| Course | Level | Focus | Study time |
|---|---|---|---|
| This course — Modeling Data Distributions: Free Course | Beginner | Normal distribution · Density curves · Percentiles | 1h 25m of video; practice time is additional |
| Sampling Distributions: Free Course | Intermediate | Sampling distributions · Standard error · Central limit theorem | 1h 42m of video; practice time is additional |
| High School Statistics: Free Course | Beginner | Descriptive statistics · Probability · Study design | 6h 19m of video; practice time is additional |
| Random Variables: AP Statistics: Free Course | Intermediate | Expected value · Random variables · Binomial models | 3h 7m 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 14 source video occurrences total approximately 1h 25m. 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.
Provider: Khan Academy. Videos play from the Khan Academy channel on YouTube.
Report a correction
Questions & discussion
Share a useful question or correction. Comments appear after moderation. Please avoid personal or sensitive information.