Statistics

Introduction to statistics. Will eventually cover all of the major topics in a first-year statistics course.
Instructed by The Khan Academy
  • Lectures 28
  • Video 6 Hours
  • Skill level all level
  • Languages English
  • Includes Lifetime access
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    Available on iOS and Android

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Course Description

Introduction to statistics. Will eventually cover all of the major topics in a first-year statistics course (not there yet!)

What am I going to get from this course?

  • Over 28 lectures and 6 hours of content!

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Not for you? No problem.
30 day money back guarantee

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Lifetime access

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Desktop, iOS and Android

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Certificate of completion

Curriculum

12:35
Introduction to descriptive statistics and central tendency. Ways to measure the average of a set: median, mean, mode
06:42
The difference between the mean of a sample and the mean of a population.
12:23
Variance of a population.
11:18
Using the variance of a sample to estimate the variance of a population
13:07
Review of what we've learned. Introduction to the standard deviation.
12:17
Playing with the formula for variance of a population.
12:04
Introduction to random variables and probability distribution functions.
10:02
Probability density functions for continuous random variables.
12:16
Introduction to the binomial distribution
11:05
More on the binomial distribution
13:26
Basketball binomial distribution
10:46
Using Excel to visualize the basketball binomial distribution
14:53
Expected value of a random variable
16:55
Expected value of a binomial distributed random variable
11:01
Introduction to Poisson Processes and the Poisson Distribution.
12:41
More of the derivation of the Poisson Distribution.
08:59
Introduction to the law of large numbers
26:04
(Long-26 minutes) Presentation on spreadsheet to show that the normal distribution approximates the binomial distribution for a large number of trials.
26:24
Exploring the normal distribution
10:53
Discussion of how "normal" a distribution might be
07:48
Z-score practice
10:25
Using the empirical rule (or 68-95-99.7 rule) to estimate probabilities for normal distributions
08:16
Using the Empirical Rule with a standard normal distribution
05:57
More Empirical Rule and Z-score practice
09:49
Introduction to the central limit theorem and the sampling distribution of the mean
10:52
The central limit theorem and the sampling distribution of the sample mean
13:20
More on the Central Limit Theorem and the Sampling Distribution of the Sample Mean
15:15
Standard Error of the Mean (a.k.a. the standard deviation of the sampling distribution of the sample mean!)

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Reviews

Average Rating
4.3
Details
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    0
    • Sudhir Singh

    Statistics - good

    Course was good and instructor was also good , but some topics are missing like correlation regression and kindly include some real world example to demonstrate topics will be really good

    • Ashok Anbalan

    Excellent Coverage

    The number of topics covered in this course is significant & the examples are clear.

    • Kevin Howard Rader

    The videos are incredible, great detail and in depth explanations, thank you very much you have made learning a joy for me.

    • Sal Dossani

    Statistics

    Good course. Well presented and well explained. Clear and sensible.

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