# Statistics

with Iliya Valchanov
4.8/5
(4,197)

Start your data analysis journey by laying a solid foundation: learn statistics and harness the power of data-driven decision-making

5 hours of content 85550 students

\$99.00

14-Day Money-Back Guarantee

What you get:

• 5 hours of content
• Interactive exercises
• World-class instructor
• Closed captions
• Q&A support
• Course exam
• Certificate of achievement

# Statistics

A course by Iliya Valchanov

\$99.00

14-Day Money-Back Guarantee

What you get:

• 5 hours of content
• Interactive exercises
• World-class instructor
• Closed captions
• Q&A support
• Course exam
• Certificate of achievement

\$99.00

14-Day Money-Back Guarantee

What you get:

• 5 hours of content
• Interactive exercises
• World-class instructor
• Closed captions
• Q&A support
• Course exam
• Certificate of achievement

## What You Learn

• Understand the fundamentals of statistics
• Distinguish between the diverse types of data and levels of measurement
• Calculate confidence intervals and make informed decisions

## Top Choice of Leading Companies Worldwide

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

## Course Description

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

2.3 Categorical Variables. Visualization techniques

5 min

2.4 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.

## 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 54 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
1 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

## 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

## Exams and Certification

Iliya Valchanov

Co-founder at 365 Data Science

7 Courses

20627 Reviews

351519 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.

## What Our Learners Say

18.09.2024
Everything is greatly explained with just enough detail and attention to the practical applications with examples and case scenarios.
17.09.2024
15.09.2024

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