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Statistics - Khan Academy

Statistics - Khan Academy

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

Probability and statistics on Khan Academy: We dare you to go through a day in which you never consider or use probability. Did you check the weather forecast? Busted! Did you decide to go through the drive through lane vs walk in? Busted again! We are constantly creating hypotheses, making predictions, testing, and analyzing. Our lives are full of probabilities! Statistics is related to probability because much of the data we use when determining probable outcomes comes from our understanding of statistics. In these tutorials, we will cover a range of topics, some which include: independent events, dependent probability, combinatorics, hypothesis testing, descriptive statistics, random variables, probability distributions, regression, and inferential statistics. So buckle up and hop on for a wild ride. We bet you're going to be challenged AND love it!

About Khan Academy: Khan Academy offers practice exercises, instructional videos, and a personalized learning dashboard that empower learners to study at their own pace in and outside of the classroom. We tackle math, science, computer programming, history, art history, economics, and more. Our math missions guide learners from kindergarten to calculus using state-of-the-art, adaptive technology that identifies strengths and learning gaps. We've also partnered with institutions like NASA, The Museum of Modern Art, The California Academy of Sciences, and MIT to offer specialized content.

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Lessons hide description

Introduction to descriptive statistics and central tendency. Ways to measure the average of a set: median, mean, mode

The difference between the mean of a sample and the mean of a population.

Review of what we've learned. Introduction to the standard deviation. Practice this lesson yourself on KhanAcademy.org right now: https://www.khanacademy.org/math/proba ...

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

Discussion of how "normal" a distribution might be Practice this lesson yourself on KhanAcademy.org right now: https://www.khanacademy.org/math/proba ...

Z-score practice Practice this lesson yourself on KhanAcademy.org right now: https://www.khanacademy.org/math/proba ...

Using the empirical rule (or 68-95-99.7 rule) to estimate probabilities for normal distributions Practice this lesson yourself on KhanAcademy.org right now: https://www.khanacademy.org/math/proba ...

Using the Empirical Rule with a standard normal distribution Practice this lesson yourself on KhanAcademy.org right now: https://www.khanacademy.org/math/proba ...

Using the Empirical Rule with a standard normal distribution Practice this lesson yourself on KhanAcademy.org right now: https://www.khanacademy.org/math/proba ...

Introduction to the central limit theorem and the sampling distribution of the mean

The central limit theorem and the sampling distribution of the sample mean

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

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

Figuring out the probability of running out of water on a camping trip

Estimating the probability that the true population mean lies within a range around a sample mean.

Finding the 95% confidence interval for the proportion of a population voting for a candidate.

Finding the 95% confidence interval for the proportion of a population voting for a candidate.

Constructing small sample size confidence intervals using t-distributions

Introduction to the idea that one can find a line that minimizes the squared distances to the points

Calculating R-Squared to see how well a regression line fits data

Analysis of Variance 2 - Calculating SSW and SSB (Total Sum of Squares Within and Between).avi

Understanding why correlation does not imply causality (even though many in the press and some researchers often imply otherwise)
 

 

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