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Introduction to Statistics

BeginnerSkill Level

4.8+

Updated 05/2025

Learn the fundamentals of statistics, including measures of center and spread, probability distributions, and hypothesis testing with no coding involved!

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TheoryProbability & Statistics4 hours16 videos56 Exercises3,450 XP103,409Statement of Accomplishment

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Course Description

Statistics are all around us, from marketing to sales to healthcare. The ability to collect, analyze, and draw conclusions from data is not only extremely valuable, but it is also becoming commonplace to expect roles that are not traditionally analytical to understand the fundamental concepts of statistics. This course will equip you with the necessary skills to feel confident in working with analyzing data to draw insights. You'll be introduced to common methods used for summarizing and describing data, learn how probability can be applied to commercial scenarios, and discover how experiments are conducted to understand relationships and patterns. You'll work with real-world datasets including crime data in London, England, and sales data from an online retail company!

Prerequisites

There are no prerequisites for this course

1

Summary Statistics

What is statistics?

Using statistics in the real-world

Identifying data types

Descriptive vs. Inferential statistics

Measures of center

Typical number of robberies per London Borough

Choosing a measure

London Boroughs with most frequent crimes

Measures of spread

Defining measures of spread

Box plots for measuring spread

Which crime has the larger standard deviation

2

Probability and distributions

What are the chances?

What is more likely?

Chances of the next sale being more than the mean

Conditional probability

Dependent vs. Independent events

Orders of more than 10 basket products

Discrete distributions

Identifying distributions

Sample mean vs. Theoretical mean

Continuous distributions

Discrete vs. Continuous distributions

Finding the normal distribution

Probability with a uniform distribution

3

More Distributions and the Central Limit Theorem

The binomial distribution

Recognizing a binomial distribution

How probability affects the binomial distribution

Identifying n and p

The normal distribution

Recognizing the normal distribution

What makes the normal distribution special?

Identifying skewness

Describing distributions using kurtosis

The central limit theorem

Visualizing sampling distributions

The CLT vs. The law of large numbers

When to use the central limit theorem

The Poisson distribution

Identifying Poisson processes

Recognizing lambda in the Poisson distribution

4

Correlation and Hypothesis Testing

Hypothesis testing

Sunshine and sleep

The hypothesis testing workflow

Independent and dependent variables

Experiments

Recognizing controlled trials

Why use randomization?

Correlation

Identifying correlation between variables

What can correlation tell you?

Confounding variables

Interpreting hypothesis test results

Significance levels vs. p-values

Type I and type II errors

Congratulations!

Introduction to Statistics

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