Lecture Details :
(Long-26 minutes) Presentation on spreadsheet to show that the normal distribution approximates the binomial distribution for a large number of trials.
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Course Description :
Statistics: The average | Descriptive statistics,Sample vs. Population Mean,Variance of a population,Sample variance,Standard -deviation,Alternate variance formulas - Introduction to Random Variables - Probability density functions - Binomial Distribution - Expected Value: E(X) - Expected value of binomial distribution - Poisson process - Law of large numbers - Normal distribution excel exercise - Introduction to the normal distribution - ck12.org normal distribution problems: Qualitative sense of normal distributions - ck12.org normal distribution problems: z-score - ck12.org normal distribution problems: Empirical rule - k12.org exercise: Standard normal distribution and the empirical - ck12.org: More empirical rule and z-score practice - Central limit theorem - Sampling distribution of the sample mean - Standard error of the mean - Sampling distribution example problem - Confidence interval - Mean and variance of Bernoulli distribution example - Bernoulli distribution mean and variance formulas - Margin of error - Confidence interval example - Small sample size confidence intervals - Hypothesis testing and p-values - One-tailed and two-tailed tests - Z-statistics vs. T-statistics - Small sample hypothesis test - T-statistic confidence interval - Large sample proportion hypothesis testing - Variance of differences of random variables - Difference of sample means distribution - Confidence interval of difference of means - Clarification of confidence interval of difference of means - Hypothesis test for difference of means - Comparing population proportions
Other Resources :
Other Mathematics Courses
- Mathematical Methods for Engineers II by MIT
- Introduction to Geometry by Other
- Engineering Mathematics by The University of New South Wales
- ACT 460 / STA 2502 - Stochastic Methods for Actuarial Science by University of Toronto
- Statistical Inference by IIT Kharagpur
- Linear Algebra I by IIT Madras
- Stochastic Processes by IIT Delhi
- Computational Science and Engineering I by MIT
- Algebra I Worked Examples by Khan Academy
- Combinatorics by IISc Bangalore
» check out the complete list of Mathematics lectures