(cache)Online Statistics Course

What You Learn

Understand the fundamentals of statistics
Gain strong quantitative skills that will help you learn advanced concepts
Distinguish between the diverse types of data and levels of measurement
Calculate confidence intervals and make informed decisions
Deliver definitive answers to business questions with hypothesis testing

Top Choice of Leading Companies Worldwide

Industry leaders and professionals globally rely on this top-rated course to enhance their skills.

Course Description

Statistics puts the “scientist” in data scientist. It is the driving force in any quantitative career, providing the foundational skills necessary for data analysis. This is the perfect statistics course that will help you understand how to design statistical tests and analyse data using modern software packages and programming languages. We start from the very basics and gradually build your statistical thinking. This foundational knowledge prepares you to tackle increasingly complex topics as you advance in your data journey. Don’t spend hundreds of hours reading textbooks and trying to learn statistics on your own. It doesn’t get any better if you rely on statistics tutorials from YouTube. Our course is the perfect tool to acquire invaluable knowledge that will make statistics easy for you. The step-by-step tutorials we have prepared alongside interactive exercises with statistical formulas and symbols will help you master statistics in several hours. This Statistics course stands out because it gives easy to understand practical examples and allows you to test what you have learned after each lesson. This formula has proven extremely successful as hundreds of thousands of users around the world have chosen this course to learn statistics and have expressed their satisfaction. This statistics course is suitable for university students who need statistics for their studies. It is also highly recommended for graduates and young professionals who want to improve their quantitative skills. Even if you lack any quantitative skills and haven’t learned statistics before, don’t worry. This intro to statistics course is designed to guide you from the ground up. There are hundreds of Statistics courses on the internet, but this is one of the most popular ones. The course instructor Iliya Valchanov teaches statistics for data science and business in a friendly way that is easy to understand and the interactive exercises throughout the course allow you to reinforce what you have learned. At the end of all major sections of the Statistics course, the author will solve a practical case study alongside you, helping you understand how to apply in practice the concepts you have just learned in the lessons. Join us on a journey that will introduce you to the different types of data, the measures of central tendency, and data variability. Gain the quant skills to use inferential statistics and work with the normal distribution. Calculate confidence intervals and perform hypothesis tests to get an introduction to the core principles of data-driven decision-making. How is this online Statistics course different than the rest? 1. Content quality Experience structured learning with a step-by-step approach. Our key strength lies in making complex topics accessible and easy to understand. It can’t be overstated how important is to make the course lectures and your entire learning journey fun and exciting. The instructor does not simply introduce you to statistics theory and rules, they effectively demonstrate how to apply statistics in practical scenarios. By leveraging compelling storytelling and drawing on real-world experiences, they ensure that you gain a solid understanding of the subject. 2. One of the most popular Statistics courses online This statistics training is a definite bestseller in the field and has been taken by hundreds of thousands of students around the world. This means that if you choose to learn with us, you will be in good hands. 3. Downloadable materials Gain access to valuable statistics templates you can use as a reference at any point of your career. In addition, the course comes with a full set of downloadable materials – complete statistics course notes, flashcards with key terms, practice exercises, course exams – everything is included inside. 4. Certificate of achievement If you compete the Statistics course and pass successfully its course exam, you will be awarded a verifiable certificate of achievement, which is a testament to your dedication and hard work. Click the ‘Buy now’ button and start this amazing learning journey today! Make an investment to acquire quant skills that could change your entire career.

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1.1 What does the course cover

3 min

1.2 Population vs sample

4 min

2.1 Types of data and levels of measurement

5 min

2.2 Levels of measurement

4 min

2.4 Categorical Variables. Visualization techniques

5 min

2.5 Numerical Variables. Frequency distribution table

3 min

Interactive Exercises
Practice what you've learned with coding tasks, flashcards, fill in the blanks, multiple choice, and other fun exercises.

Practice what you've learned with coding tasks, flashcards, fill in the blanks, multiple choice, and other fun exercises.

Curriculum

1. Introduction

2 Lessons 7 Min

In this part of the course, we will discuss why you need to learn statistics, and which are the key skills you will acquire by taking the course.

What does the course cover
3 min
Population vs sample
4 min
2. Descriptive Statistics Fundamentals

13 Lessons 64 Min

Here, you will learn how to distinguish between the different types of data and levels of measurement. This will help you when calculating the measures of central tendency (mean, median, and mode) and dispersion indicators such as variance and standard deviation, as well as measures of the relationship between variables like covariance and correlation. To reinforce what you have learned, we will wrap up this section with a hands-on practical example.

Types of data and levels of measurement
5 min
Levels of measurement
4 min
Categorical Variables. Visualization techniques
5 min
Numerical Variables. Frequency distribution table
3 min
The histogram
2 min
Cross table and scatter plot
5 min
Mean, median, mode
4 min
Skewness
3 min
Variance
6 min
Standard deviation and coefficient of variation
5 min
Covariance
3 min
Correlation
3 min
Practical Example - Descriptive Statistics
16 min
3. Inferential Statistics Fundamentals

7 Lessons 22 Min

In this section, you will learn what a distribution is and what characterizes the normal distribution. We will introduce you to the central limit theorem and to the concept of standard error.

Introduction
1 min
What is a distribution
5 min
The Normal Distribution
4 min
The Standard Normal Distribution
4 min
Central limit theorem
4 min
Standard error
1 min
Estimators and estimates
3 min
4. Confidence Intervals

11 Lessons 55 Min

Here, you will learn how to calculate confidence intervals with known population and variance. We will introduce the Student T distribution, and you will learn how to work with smaller samples, as well as differences between two means (with dependent and independent samples). These tools are fundamental later on when we start applying each of these concepts to large datasets and use coding languages like Python and R. To reinforce what you have learned, we will wrap up this section with an easy-to-understand practical example.

Definition of confidence intervals
3 min
Population variance known, z-score
8 min
Confidence Interval Clarifications
5 min
Student's T Distribution
3 min
Population variance unknown, t-score
5 min
Margin of error
5 min
Confidence intervals. Two means. Dependent samples
6 min
Confidence intervals. Two means. Independent samples (Part1)
5 min
Confidence intervals. Two means. Independent samples (Part2)
4 min
Confidence intervals. Two means. Independent Samples (Part 3)
1 min
Practical Example - Confidence Intervals
10 min
5. Hypothesis testing

11 Lessons 55 Min

In this section, you will learn how to perform hypothesis testing, as well as the difference between a null and alternative hypothesis. We will discuss rejection and significance levels, and type I and type II errors. The lessons will teach you how to test for the mean when the population variance is known and unknown, as well as how to test for the mean when you are dealing with dependent and independent samples. You will also become familiar with the p-value. To consolidate the new knowledge, we will conclude with a practical example.

Null vs Alternative
6 min
Further Reading on Null and Alternative Hypothesis Read now
2 min
Rejection region and significance level
7 min
Type I error vs type II error
4 min
Test for the mean. Population variance known
7 min
p-value
4 min
Test for the mean. Population variance unknown
5 min
Test for the mean. Dependent samples
5 min
Test for the mean. Independent Samples (Part 1)
4 min
Test for the mean. Independent Samples (Part 2)
4 min
Practical Example - Hypothesis Testing
7 min

Topics

Theorydata analysisExcel

Tools & Technologies

Course Requirements

No prior experience or knowledge is required. We will start from the basics and gradually build your understanding. Everything you need is included in the course

Who Should Take This Course?

Level of difficulty: Beginner

People who want to improve their quantitative skills
Aspiring data analysts, data scientists, business analysts
Graduate students who need statistics for their studies
Business executives who are passionate about data-driven decision-making

Exams and Certification

A 365 Data Science Course Certificate is an excellent addition to your LinkedIn profile—demonstrating your expertise and willingness to go the extra mile to accomplish your goals.

Meet Your Instructor

Iliya Valchanov

Co-founder at

7 Courses

27036 Reviews

423065 Students

Iliya Valchanov is a co-founder of 365 Data Science and 3veta. He is a Finance graduate with a wide range of expertise in the fields of mathematics, statistics, programming, machine learning, and deep learning. In his courses, Iliya shares his extensive experience in predictive modeling, complex analysis techniques, and optimization algorithms. He has a BA in International Economics, Management and Finance from Bocconi University, where he was Founder and President of the Bocconi Students Mathematics and Logics Association. In 2016, he created his first online course (Statistics) and realized he enjoyed the process of content creation so much that he co-founded 365 Data Science together with a group of friends from university.