Learn descriptive statistics in R applying your knowledge with mini projects, quizzes, and a final exam

What you'll learn
- How to apply basic statistical knowledge to solve real-world scenarios using R
- How to create, read, and work with CSV files in RStudio
- Fundamental concepts such as population, sample, sampling, bias, data, statistic, and parameter
- How to find and interpret frequency, relative frequency, and cumulative relative frequency
- How to find and interpret the Mean, Median, and Mode
- How to find and interpret Variance and Standard Deviation
- How to find quartiles (Q1, Q2, Q3), the interquartile range (IQR), and outliers
- How to create, read and interpret bar plots, histograms, and box plots

Requirements
- No previous programming experience required.
- Download and install RStudio (Free Open-Source Edition).
- You can work with the R console during the course as well.
- Google Sheets to create CSV files.

Description
Learn statistics using R with mini projects, hands-on practice, and carefully designed visual explanations. Understand how fundamental statistical concepts work behind the scenes and apply your knowledge to new scenarios.

Descriptive Statistics in R is Your First Step Into the In-demand and Powerful World of Statistics and Data Science

Analyze real-world scenarios by identifying key elements such as population, sample, statistic, and parameter.

Measure the center of the data with the mean, median, and mode. Describe their key differences and use cases.

Measure the spread of the data with variance and standard deviation.

Learn how to create and interpret bar plots, histograms and box plots.

Find quartiles and the interquartile range (IQR). Use them to identify potential outliers.

Apply your knowledge in practical mini projects.

Check your knowledge with a final exam that covers all the topics of the course.

Add New Statistical Skills To Your Resume

Statistics is one of the most in-demand skills of our current time. If you want a career in data science, computer science, or mathematics, learning statistics is the first step that you need to take. When you combine theoretical statistical skills with practical R programming skills, you have the perfect skill set that employers around the world are looking for.

This course provides a detailed and engaging introduction to descriptive statistics using the R programming language and RStudio, the main tool used in industry to work with programming for statistical purposes.

No programming experience is required to take this course. Lectures combine the theoretical aspects of statistics with the practical and applied aspects that R programming brings to this amazing field. You will be analyzing small datasets and working on practical mini projects that simulate simplified real-world scenarios.

Learning the fundamentals of statistics is your first step towards mastering a career in data science, computer science, and mathematics.

Content & Overview

With high-quality video lectures that include customized graphics and presentations, you will learn and work with these concepts:

Population

Sample

Sampling

Data

Variable

Statistic

Parameter

Frequency

Relative Frequency

Cumulative Relative Frequency

Bar plots

Mean

Median

Mode

Variance

Standard Deviation

Histograms

Quartiles

Interquartile Range (IQR)

Outliers

Box Plots

.and more.

You will apply your knowledge in practical mini projects throughout the course and you will check your understanding with a final exam that will test your knowledge of all the topics covered in the course.

Learning Material & Resources

Throughout the course, you will find these resources:

Video lectures:carefully designed graphics and explanations.

Mini Projects:apply your knowledge with practical mini projects that represent simplified real-world scenarios.

Solutions:each mini project has its corresponding solution, so you can check your answers immediately.

Coding Sessions:practical lectures cover how to apply your new statistical knowledge in R and RStudio.

PDF Handouts:you will find unique study guides with key aspects of each section.

Quizzes:check your knowledge interactively after each section with short quizzes (unlimited attempts!).

Articles:read complementary articles specifically written for this course to expand your knowledge on various topics.

Discussion Forums:ask questions on the discussion forums and discuss interesting topics with your peers.

Why is this course unique?

This course is unique because of its emphasis on providingvisual and detailed explanationsof how statistics works behind the scenes, so you will not only learn how to find statistical results using R, you will actually understand what they mean and what each line of code does behind the scenes.

During the course, you will apply your knowledge by completingmini projectsthat simulate simplified real-world scenarios such as analyzing Black Friday sales, online learning patterns, waiting times of a taxi company, delivery times of a wood transportation company, light bulb life, and house prices across three different neighborhoods.

By the end of this course, you will be able tocombineyour newtheoretical knowledgeof statistics withpractical R skillsto interpret results.

Unique study materials complement the course experience. You will findPDF handoutsspecifically written for the course with key aspects of each section.

You will check your knowledge with shortquizzesthat provide instant feedback, so you can check the correct answer immediately. These questions were designed to make you think more deeply about the topics presented.

You will receive acertificate of completionthat you can add to your social media profiles to showcase your new skills.

You will also havelifetime accessto the course.

You are very welcome to watch the preview lectures and check out the full course curriculum.

If you are looking for an engaging, visual, and practical course, you've found it.

Add Descriptive Statistics in R to your resume and showcase your new skills!

Who this course is for:
- Students who are new to descriptive statistics and to R programming.
- Learners who want to combine existing statistical knowledge with R programming.
- Professionals who wish to expand their skills with practical statistical knowledge to solve real-world problems.
More Info