Ementorhub

What you'll learn

Understand the process of drawing conclusions about populations or scientific truths from data

Describe variability, distributions, limits, and confidence intervals

Use p-values, confidence intervals, and permutation tests

Make informed data analysis decisions

Skills you'll gain

Probability

Data Analysis

Statistical Methods

Statistical Inference

Probability & Statistics

Bayesian Statistics

Probability Distribution

Sampling (Statistics)

Statistical Modeling

Sample Size Determination

Statistical Analysis

Statistical Hypothesis Testing

There are 4 modules in this course

Statistical inference is the process of drawing conclusions about populations or scientific truths from data. There are many modes of performing inference including statistical modeling, data oriented strategies and explicit use of designs and randomization in analyses. Furthermore, there are broad theories (frequentists, Bayesian, likelihood, design based, …) and numerous complexities (missing data, observed and unobserved confounding, biases) for performing inference. A practitioner can often be left in a debilitating maze of techniques, philosophies and nuance. This course presents the fundamentals of inference in a practical approach for getting things done. After taking this course, students will understand the broad directions of statistical inference and use this information for making informed choices in analyzing data.

Week 2: Variability, Distribution, & Asymptotics

Week: Intervals, Testing, & Pvalues

Week 4: Power, Bootstrapping, & Permutation Tests