Statistics
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# Statistics

Introduction to statistics. Will eventually cover all of the major topics in a first-year statistics course.
4.3 (15 ratings)
2,305 students enrolled
Published 7/2010
English
Price: Free
Includes:
• Access on mobile and TV
Description
Introduction to statistics. Will eventually cover all of the major topics in a first-year statistics course (not there yet!)
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Curriculum For This Course
28 Lectures
00:00
+
Statistics: The Average
28 Lectures 00:00
Introduction to descriptive statistics and central tendency. Ways to measure the average of a set: median, mean, mode
Statistics: The Average
ImportContent

The difference between the mean of a sample and the mean of a population.
Statistics: Sample vs. Population Mean
ImportContent

Variance of a population.
Statistics: Variance of a Population
ImportContent

Using the variance of a sample to estimate the variance of a population
Statistics: Sample Variance
ImportContent

Review of what we've learned. Introduction to the standard deviation.
Statistics: Standard Deviation
ImportContent

Playing with the formula for variance of a population.
Statistics: Alternate Variance Formulas
ImportContent

Introduction to random variables and probability distribution functions.
Introduction to Random Variables
ImportContent

Probability density functions for continuous random variables.
Probability Density Functions
ImportContent

Introduction to the binomial distribution
Binomial Distribution 1
ImportContent

More on the binomial distribution
Binomial Distribution 2
ImportContent

Binomial Distribution 3
ImportContent

Using Excel to visualize the basketball binomial distribution
Binomial Distribution 4
ImportContent

Expected value of a random variable
Expected Value: E(X)
ImportContent

Expected value of a binomial distributed random variable
Expected Value of Binomial Distribution
ImportContent

Introduction to Poisson Processes and the Poisson Distribution.
Poisson Process 1
ImportContent

More of the derivation of the Poisson Distribution.
Poisson Process 2
ImportContent

Introduction to the law of large numbers
Law of Large Numbers
ImportContent

(Long-26 minutes) Presentation on spreadsheet to show that the normal distribution approximates the binomial distribution for a large number of trials.
Normal Distribution Excel Exercise
ImportContent

Exploring the normal distribution
Introduction to the Normal Distribution
ImportContent

Discussion of how "normal" a distribution might be
ck12.org Normal Distribution Problems: Qualitative sense of normal distributions
ImportContent

Z-score practice
ck12.org Normal Distribution Problems: z-score
ImportContent

Using the empirical rule (or 68-95-99.7 rule) to estimate probabilities for normal distributions
ck12.org Normal Distribution Problems: Empirical Rule
ImportContent

Using the Empirical Rule with a standard normal distribution
ck12.org Exercise: Standard Normal Distribution and the Empirical Rule
ImportContent

More Empirical Rule and Z-score practice
ck12.org: More Empirical Rule and Z-score practice
ImportContent

Introduction to the central limit theorem and the sampling distribution of the mean
Central Limit Theorem
ImportContent

The central limit theorem and the sampling distribution of the sample mean
Sampling Distribution of the Sample Mean
ImportContent

More on the Central Limit Theorem and the Sampling Distribution of the Sample Mean
Sampling Distribution of the Sample Mean 2
ImportContent

Standard Error of the Mean (a.k.a. the standard deviation of the sampling distribution of the sample mean!)
Standard Error of the Mean
ImportContent