Introduction to Statistics with R

Introduction to Statistics with R, available at $59.99, has an average rating of 3.9, with 59 lectures, 12 quizzes, based on 46 reviews, and has 168 subscribers.

You will learn about Analyze statistical data using R Studio This course is ideal for individuals who are People new to statistics and people who want exposure to R It is particularly useful for People new to statistics and people who want exposure to R.

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Summary

Title: Introduction to Statistics with R

Price: $59.99

Average Rating: 3.9

Number of Lectures: 59

Number of Quizzes: 12

Number of Published Lectures: 59

Number of Published Quizzes: 12

Number of Curriculum Items: 71

Number of Published Curriculum Objects: 71

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Analyze statistical data using R Studio

Who Should Attend

People new to statistics and people who want exposure to R

Target Audiences

People new to statistics and people who want exposure to R

This course provides a basic introduction to statistics and the use of R a popular programming language. During the course we look at many fundamental ideas in statistics within the framework of analysis in R Studio. For students and those who want exposure to statistical analysis this is a course for you.

Course Curriculum

Lecture 1: Overview

Chapter 1: What is Statistics

Lecture 1: Lesson 1.1 What is Statistics?

Lecture 2: Lesson 1.2 Types of Variables

Lecture 3: Lesson 1.3 More on Variables

Lecture 4: Lesson 1.4 Statistical Notation

Lecture 5: Survey Design

Chapter 2: How do You Use R?

Lecture 1: Lesson 2.1 Installing R

Lecture 2: Lesson 2.2 R Basics

Lecture 3: Lesson 2.3 Functions

Lecture 4: Lesson 2.4 Loading Data

Chapter 3: How do You Visualize Numbers?

Lecture 1: Lesson 3.1 Frequency Tables with Categorical Variables

Lecture 2: Lesson 3.2 Frequency Tables with Categorical Variables in R

Lecture 3: Lesson 3.3 Frequency Tables with Continuous Variables

Lecture 4: Lesson 3.4 Scatter Plot & Histogram

Lecture 5: Lesson 3.5 Exporting figures

Chapter 4: What are Measures of Central Tendency?

Lecture 1: Lesson 4.1 Mean, Median, Mode

Lecture 2: Lesson 4.2 Mean, Median, Mode in R

Lecture 3: Lesson 4.3 Mean vs Median vs Mode OPTIONAL

Chapter 5: What are Measures of Dispersion?

Lecture 1: Lesson 5.1 Range and Finding Range in R

Lecture 2: Lesson 5.2 Variance & Standard Deviation

Lecture 3: Lesson 5.3 Find Variance & Standard Deviation in R

Lecture 4: Lesson 5.4 Quartiles

Lecture 5: Lesson 5.5 Find Quartiles and make Box plots in R

Lecture 6: Lesson 5.6 Kurtosis & Skew

Lecture 7: Lesson 5.7 Find Kurtosis and Skew in R

Chapter 6: What is Probability?

Lecture 1: Lesson 6.1-Probability

Lecture 2: Lesson 6-2 Bayesian Probability OPTIONAL

Lecture 3: Lesson 6-3 Review OPTIONAL

Chapter 7: What is Normal Distribution?

Lecture 1: Lesson 7.1 Normal Distribution

Lecture 2: Lesson 7.2 Standard Normal Distribution

Lecture 3: Lesson 7.3 Normal, Standard, & Sampling Distributions OPTIONAL

Chapter 8: What are Confidence Intervals?

Lecture 1: Lesson 8.1 Confidence Intervals Defined

Lecture 2: Lesson 8.2 Finding Confidence Intervals in R

Lecture 3: Lesson 8.3 Confidence Intervals for Proportions

Lecture 4: Lesson 8.4 Finding Confidence Intervals for Proportions in R

Chapter 9: What is Hypothesis Testing?

Lecture 1: Lesson 9.1 Hypotheses

Lecture 2: Lesson 9.2 One Sample t-test

Lecture 3: Lesson 9.3 One Sample t-test in R

Lecture 4: Lesson 9.4 t-test for Proportion

Lecture 5: Lesson 9.5 t-test for Proportion in R

Chapter 10: What is Two Sample Hypothesis Testing?

Lecture 1: Lesson 10.1 T-test for Two Means

Lecture 2: Lesson 10.2 T-test for Two Means in R

Lecture 3: Lesson 10.3 Paired T-Test

Lecture 4: Lesson 10.4 Paired T-Test in R

Lecture 5: Lesson 10.5 Two-Sample Test of Proportions

Lecture 6: Lesson 10.6 Two-Sample Test of Proportions in R

Chapter 11: What is Analysis of Variance?

Lecture 1: Lesson 11.1 ANOVA

Lecture 2: Lesson 11.2 Other Forms of ANOVA OPTIONAL

Lecture 3: Lesson 11.3 ANOVA Under the Hood OPTIONAL

Chapter 12: What is Correlation and Regression?

Lecture 1: Lesson 12.1 Scatter Plots & Correlation

Lecture 2: Lesson 12.2 Find Correlation in R

Lecture 3: Lesson 12.3 Simple Linear Regression

Lecture 4: Lesson 12.4 Calculate Simple Linear Regression in R

Lecture 5: Lesson 12.5 Multiple Regression

Lecture 6: Lesson 12.6 Calculate Multiple Regression in R

Chapter 13: What is Chi-Square?

Lecture 1: Lesson 13.1 Chi Square Goodness of Fit

Lecture 2: Lesson 13.2 Chi-Square Goodness of Fit in R

Lecture 3: Lesson 13.3 Chi-Square Test of Independence in R

Lecture 4: Conclusion

Instructors

Darrin Thomas
Lecturer

Rating Distribution

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2 stars: 4 votes

3 stars: 9 votes

4 stars: 19 votes

5 stars: 14 votes

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