Rutgers Classifieds>Rutgers Online Courses>Probability and Statistics IV: Confidence Intervals and Hypothesis Tests

Probability and Statistics IV: Confidence Intervals and Hypothesis Tests

About this Course

This course covers two important methodologies in statistics – confidence intervals and hypothesis testing. Confidence intervals are encountered in everyday life, and allow us to make probabilistic statements such as: “Based on the sample of observations we conducted, we are 95% sure that the unknown mean lies between A and B,” and “We are 95% sure that Candidate Smith’s popularity is 52% +/- 3%.” We begin the course by discussing what a confidence interval is and how it is used. We then formulate and interpret confidence intervals for a variety of probability distributions and their parameters. Hypothesis testing allows us to pose hypotheses and test their validity in a statistically rigorous way. For instance, “Does a new drug result in a higher cure rate than the old drug?” or “Is the mean tensile strength of item A greater than that of item B?” The second half the course begins by motivating hypothesis tests and how they are used. We then discuss the types of errors that can occur with hypothesis testing, and how to design tests to mitigate those errors. Finally, we formulate and interpret hypothesis tests for a variety of probability distributions and their parameters.

Created by: The Georgia Institute of Technology

Level: Intermediate


Related Online Courses

Analytical models are key to understanding data, generating predictions, and making business decisions. Without models it’s nearly impossible to gain insights from data. In modeling, it’s ess... more
In this course, you will learn about the Grammar of Graphics, a system for describing and building graphs, and how the ggplot2 data visualization package for R applies this concept to basic bar... more
Do you want to build systems that learn from experience? Or exploit data to create simple predictive models of the world? In this course, part of the Data Science MicroMasters program, you will... more
To become an expert data scientist you need practice and experience. By completing this capstone project you will get an opportunity to apply the knowledge and skills in R data analysis that you... more
Have you wanted to build a TinyML device? In Deploying TinyML, you will learn the software, write the code, and deploy the model to your own tiny microcontroller-based device. Before you know it,... more

CONTINUE SEARCH

FOLLOW COLLEGE PARENT CENTRAL