Learn about bootstrapping; sampling with replacement; simulating Gaussian mixture, and truncated distribution.
- [Instructor] A year after Mayor Green is elected,…she embarks on a series of very contentious reforms.…There are doubts as to the level of support…that the citizen have in her.…In your job at the newspaper, you're still covering…politics, so you prepare to do another poll.…This time, you ask the people you interview…to give the mayor a grade between zero and ten.…You're feeling lazy, so you take only 100 samples.…Then we import packages, and load the data.…
It seems the citizens gave you the grades…with great precision.…We're wrong with this.…So we look at the histogram, and this cribda sample…with summary statistics.…The histogram has no recognizable simple form,…but the mean for the sample is 5.5.…What can we say about the true mean value?…This time we cannot build a confidence interval…by simulating the sampling distribution…because we do not know how to describe it.…
And, indeed, given the observed histogram it is unlikely…that it has a simple form such as a no amount distribution.…However, we can still use computing by adopting…
- Installing and setting up Python
- Importing and cleaning data
- Visualizing data
- Describing distributions and categorical variables
- Using basic statistical inference and modeling techniques
- Bayesian inference
Skill Level Intermediate
R Statistics Essential Trainingwith Barton Poulson5h 59m Intermediate
SPSS Statistics Essential Trainingwith Barton Poulson4h 57m Beginner
1. Installation and Setup
2. Importing and Cleaning Data
3. Visualizing and Describing Data
4. Introduction to Statistical Inference
5. Introduction to Statistical Modeling
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