Statistics & Probability from Zero: Real-Life Examples

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Statistics & Probability from Zero: Real-Life Examples
Published 9/2026
Created by Omar Koryakin
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English + subtitle | Duration: 48 Lectures ( 9h 15m ) | Size: 10.7 GB

Read ratings, salaries, medical tests and polls with confidence. Statistics by hand, one picture at a time, no code.

What you'll learn
⚡ Judge a star rating or review score by reading it together with how many reviews are behind it
⚡ See through an "average salary" or "average house price" by working out the median and spotting outliers
⚡ Calculate the mean, median, mode, range and standard deviation by hand, and know which one answers your question
⚡ Use a z-score to say how unusual a test result, a sales day or a card payment really is
⚡ Work out the real chance of combined events with a dice grid, a Venn diagram and a tree diagram
⚡ Explain what a positive medical test really means when the illness is rare, and why base rates matter
⚡ Read a poll's "plus or minus 3 points" and tell when a race is too close to call
⚡ Build a 95% confidence interval and run a full hypothesis test, with a plain-English conclusion
⚡ Spot a correlation that isn't a cause, fit a simple prediction line, and question a "hot streak"
⚡ Catch misleading charts and headlines, like a cropped bar chart axis or a "most X were Y" story

Requirements
❗ Everyday arithmetic: adding, subtracting, multiplying, dividing and working out a percentage
❗ A basic calculator (the one on your phone is fine) and some paper and a pen for the practice exercises
❗ No previous statistics, algebra or software experience is needed; every word and symbol is explained from scratch
❗ Willingness to pause the video and try each short exercise before watching the answer

Description
This course contains the use of artificial intelligence.

Have you ever looked at a number in a report, a news story or a doctor's letter and felt your mind go blank? This course is for that moment. We start from zero, and by the end you'll be able to look at almost any number someone shows you and ask the three questions that matter: how many values are behind it, how spread out they are, and how likely it is to be luck.

We begin with real life, not formulas. You'll work out why a restaurant with 4.9 stars from 12 reviews is less trustworthy than one with 4.6 stars from 3,100. You'll see why an "average salary" in a job advert can be a number that almost nobody earns, and why the median tells you more. You'll count 1,000 people through a simple tree and find out that a positive result on a "90% accurate" test for a rare illness means only about an 8% chance you're actually ill. And you'll read a poll that says 52%, plus or minus 3 points, and know whether the race is really decided.

The teaching is slow and patient on purpose. Every lesson starts with a situation you'll recognise, explains the reason before the rule, and then walks through a worked example step by step with a picture you can see building on screen. After that it's your turn: you pause, try a short exercise yourself, and then we check the answer together. Each lesson also shows where you'll meet the idea at work or at home, and the classic mistake people make with it, so you don't fall into it.

All you need is everyday arithmetic: adding, subtracting, multiplying, dividing and percentages on a calculator. There's no software to install, no code and no algebra beyond "put the numbers in and work it out". Every new word and symbol is explained the first time it appears, and we reuse the same small set of examples (a restaurant, a class of 20 students, a coffee shop, a small studio's salaries) so you can focus on the idea instead of learning a new story each time.

Here's the path. We start with data, tables and honest bar charts, then the mean, median and mode, then spread and the standard deviation. You'll learn percentiles and z-scores to say how unusual a value is, then probability by counting dice, tree diagrams, conditional probability and base rates. After that comes the normal curve and reading a z-table, then samples, margin of error and your first 95% confidence interval. Next you'll run a full hypothesis test and write a conclusion that doesn't overclaim. We finish with correlation, a line of best fit, and two real-life case studies: is a basketball player really on a hot streak, and are your trading returns as calm as the bell curve suggests?

This course is a good fit if you're switching careers into data, reading dashboards at work, studying for a statistics module, helping your children with school maths, or simply tired of feeling fooled by numbers in the news. If you've tried statistics before and it went too fast, this one won't.

Who this course is for
⭐ Complete beginners who freeze when a report, a news story or a doctor throws numbers at them
⭐ Career switchers heading into data analysis or data science who want solid foundations before learning the tools
⭐ Office staff and managers who read dashboards, sales reports or survey results and want to question them properly
⭐ Students taking an introductory statistics module in school, college or university who need it explained slowly
⭐ Parents who want to understand school reports, percentiles and test scores, and help their children with maths
⭐ Traders, investors and curious readers who want to understand risk, averages, probability and "significant" results

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