Statistics

Introduction to statistics. Will eventually cover all of the major topics in a first-year statistics course.
6 reviews
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Statistics

Introduction to statistics. Will eventually cover all of the major topics in a first-year statistics course.
6 reviews

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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!)
    • Over 28 lectures and 6 hours of content!

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CURRICULUM

  • 1
    Statistics: The Average
    12:35
    Introduction to descriptive statistics and central tendency. Ways to measure the average of a set: median, mean, mode
  • 2
    Statistics: Sample vs. Population Mean
    06:42
    The difference between the mean of a sample and the mean of a population.
  • 3
    Statistics: Variance of a Population
    12:23
    Variance of a population.
  • 4
    Statistics: Sample Variance
    11:18
    Using the variance of a sample to estimate the variance of a population
  • 5
    Statistics: Standard Deviation
    13:07
    Review of what we've learned. Introduction to the standard deviation.
  • 6
    Statistics: Alternate Variance Formulas
    12:17
    Playing with the formula for variance of a population.
  • 7
    Introduction to Random Variables
    12:04
    Introduction to random variables and probability distribution functions.
  • 8
    Probability Density Functions
    10:02
    Probability density functions for continuous random variables.
  • 9
    Binomial Distribution 1
    12:16
    Introduction to the binomial distribution
  • 10
    Binomial Distribution 2
    11:05
    More on the binomial distribution
  • 11
    Binomial Distribution 3
    13:26
    Basketball binomial distribution
  • 12
    Binomial Distribution 4
    10:46
    Using Excel to visualize the basketball binomial distribution
  • 13
    Expected Value: E(X)
    14:53
    Expected value of a random variable
  • 14
    Expected Value of Binomial Distribution
    16:55
    Expected value of a binomial distributed random variable
  • 15
    Poisson Process 1
    11:01
    Introduction to Poisson Processes and the Poisson Distribution.
  • 16
    Poisson Process 2
    12:41
    More of the derivation of the Poisson Distribution.
  • 17
    Law of Large Numbers
    08:59
    Introduction to the law of large numbers
  • 18
    Normal Distribution Excel Exercise
    26:04
    (Long-26 minutes) Presentation on spreadsheet to show that the normal distribution approximates the binomial distribution for a large number of trials.
  • 19
    Introduction to the Normal Distribution
    26:24
    Exploring the normal distribution
  • 20
    ck12.org Normal Distribution Problems: Qualitative sense of normal distributions
    10:53
    Discussion of how "normal" a distribution might be
  • 21
    ck12.org Normal Distribution Problems: z-score
    07:48
    Z-score practice
  • 22
    ck12.org Normal Distribution Problems: Empirical Rule
    10:25
    Using the empirical rule (or 68-95-99.7 rule) to estimate probabilities for normal distributions
  • 23
    ck12.org Exercise: Standard Normal Distribution and the Empirical Rule
    08:16
    Using the Empirical Rule with a standard normal distribution
  • 24
    ck12.org: More Empirical Rule and Z-score practice
    05:57
    More Empirical Rule and Z-score practice
  • 25
    Central Limit Theorem
    09:49
    Introduction to the central limit theorem and the sampling distribution of the mean
  • 26
    Sampling Distribution of the Sample Mean
    10:52
    The central limit theorem and the sampling distribution of the sample mean
  • 27
    Sampling Distribution of the Sample Mean 2
    13:20
    More on the Central Limit Theorem and the Sampling Distribution of the Sample Mean
  • 28
    Standard Error of the 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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RATING

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AVERAGE RATING
NUMBER OF RATINGS
6

REVIEWS

  • 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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