Random variables
A random variable is some outcome from a chance process, like how many heads will occur in a series of 20 flips (a discrete random variable), or how many seconds it took someone to read this sentence (a continuous random variable). We calculate probabilities of random variables, calculate expected value, and look what happens when we transform and combine random variables.
This course contains 7 segments:
Discrete random variables
Discrete random variables occur in situations where we can list every possible outcome of a process, and assign each outcome a probability in a probability model. For example, how many heads will we get in three flips? We'll learn how to make a probability distribution, find some probabilities, and calculate the mean (or expected value), variance, and standard deviation of a random variable.
Continuous random variables
Continuous random variables arise from situations where we measure some attribute on a scale — like height, weight, volume, temperature, or time. We'll learn how to identify a continuous random variable and calculate probabilities using area under density curves.
Transforming random variables
Transforming random variables produces predictable changes in the expected value and variance of the outcomes. Let's look at how changing units impacts the distribution of a discrete random variable.
Combining random variables
Combining random variables leads to some predictable and some less predictable distributions. Let's look at how adding and subtracting random variables can produce new distributions that help us solve some pretty interesting probability problems.
Binomial random variables
Binomial random variables are a special type of variable that comes up we repeat a process for a set number of independent trials, with each trial having the same probability of success, and we count how many successes we get at the end of the trials. For example, how many free-throws will a basketball player make in a series of 10 shots? Learn to identify these variables, use them to find probability, and calculate their mean and standard deviation.
Binomial mean and standard deviation formulas
Let's use what we've learned about combining random variables to create the mean and standard deviation formulas for a binomial random variable.
Geometric random variables
Geometric variables are similar but different from binomial variables. The key difference is that with a geometric variable, we count the number of trials it takes to get our first success. For example, how many attempts will it take me to make my first free-throw? Learn to calculate probabilities and the mean (expected value) for these variables.
Get a Reminder
Rating | Not enough ratings |
---|---|
Length | 7 segments |
Starts | On Demand (Start anytime) |
Cost | Free |
From | Khan Academy |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Mathematics |
Tags | Math |
Get a Reminder
Similar Courses
Careers
An overview of related careers and their average salaries in the US. Bars indicate income percentile.
Polysom Technician Sleep Disorder Center Per Diem Variable $45k
INTAKE COORD Psych Baptist Health System PRN Variable $52k
Financial Services - Variable Products Call Center Manager $56k
Variable Insurance Analyst $62k
Respiratory Care Practitioner 12AWS-PD, Variable $64k
Fixed and Variable Annuity Modeling Analyst $76k
Many different sales & marketing positions $80k
Many various sales positions Manager $81k
Many Positions $82k
Special Projects Managing Editor, Random House Childrens Books $89k
Regional Manager - Variable Product Accounting $137k
Senior Variable Annuity Product Management Consultant $152k
Write a review
Your opinion matters. Tell us what you think.
Please login to leave a review
Rating | Not enough ratings |
---|---|
Length | 7 segments |
Starts | On Demand (Start anytime) |
Cost | Free |
From | Khan Academy |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Mathematics |
Tags | Math |
Similar Courses
Sorted by relevance
Like this course?
Here's what to do next:
- Save this course for later
- Get more details from the course provider
- Enroll in this course