Foundations of Inference

DataCamp

(3)

Course Features

Duration

4 hours

Delivery Method

Online

Available on

Limited Access

Accessibility

Mobile, Desktop, Laptop

Language

English

Subtitles

English

Level

Intermediate

Teaching Type

Self Paced

Video Content

4 hours

Course Description

Inference is an essential aspect of statistical analysis. Inference is the process of drawing conclusions out of data in order to draw conclusions about a larger population. This is a common practice, even though it might seem counterintuitive. We could conclude that the same treatment will lead to equal survival rates to show that it is superior in medicine. This assumption will be disproved by the data. A "p-value" is the agreement level between the data and the hypothesis. We also discuss confidence intervals, which can be used to measure the effect. Which treatment is more effective?

Highlights

Pedagogy

Top 5 Percentile

Hands on training

Top 20 Percentile

Parameters

Pedagogy

Acquire all major Statistics skills in this course for seamless integration into your daily life. Develop a versatile skill set, allowing you to confidently apply what you've learned in various practical scenarios, enhancing your daily experiences and overall proficiency. An exceptional course in Statistics, this stands out for its Self Paced learning approach. Learners have the flexibility to progress at their own speed, tailoring the experience to their individual needs.

Hands on training

This course stands out as one of the top 20 percentile options in Statistics, offering unparalleled hands-on training. Learners gain practical experience and skills through immersive learning, preparing them for real-world challenges. It features Hands on training complemented by Virtual Labs, ensuring comprehensive skill development. This enhances its value, making it an excellent choice for individuals seeking a well-rounded education in Statistics.

Course Overview

Virtual Labs

International Faculty

Post Course Interactions

Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Introduction to Regression in R

Hypothesis Testing in R

What You Will Learn

In this chapter, you will investigate how repeated samples taken from a population can vary. It is the variability in samples that allow you to make claims about the population of interest

In this chapter, however, the focus will be on different errors (type I and type II), how they are made, when one is worse than another, and how things like sample size and effect size impact the error rates

In this chapter, you will gain the tools and knowledge to complete a full hypothesis test

Course Content

Expand all sections

Module 1: Introduction to ideas of inference

Module 2: Completing a randomization test: gender discrimination

Module 3: Hypothesis testing errors: opportunity cost

Module 4: Confidence intervals

Course Instructors

Jo Hardin

Professor at Pomona College

Jo Hardin is a professor of mathematics and statistics at Pomona College. Her statistical research focuses on developing new robust methods for high throughput data. Recently, she has also worked clo...

Course Reviews

Average Rating Based on 3 reviews

5.0

100%