After doing these courses, I feel confident creating professional visualizations and dashboards
Shoebur RahmanProcurement Specialist, Giz Bangladesh
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!The videos contain live transcripts you can reveal by clicking "Show transcript" at the bottom left of the videos.
The course glossary can be found on the right in the resources section.
To obtain CPE credits you need to complete the course and reach a score of 70% on the qualified assessment. You can navigate to the assessment by clicking on the CPE credits callout on the right.
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Start Course for FreeWhat you'll learn
- Assess hypothesis-testing results by interpreting p-values, significance levels, Type I and Type II errors, and correlation coefficients to determine statistical significance and relationship strength between variables.
- Differentiate between measures of center (mean, median, mode) and measures of spread (range, variance, standard deviation, interquartile range) based on data symmetry and presence of outliers
- Evaluate probabilities for independent and dependent events, including conditional scenarios, by applying fundamental probability formulas and the law of large numbers
- Identify numeric and categorical data types and match each with suitable summary visualizations such as histograms, scatter plots, and box plots
- Recognize appropriate applications and parameter impacts of key probability distributions—discrete uniform, binomial, Poisson, continuous uniform, and normal—while applying expected value concepts and the 68-95-99.7 rule
Prerequisites
There are no prerequisites for this course
Curriculum
Course outline
1
Summary Statistics
Summary statistics gives you the tools you need to describe your data. In this chapter, you'll explore summary statistics including mean, median, and standard deviation, and learn how to accurately interpret them. You'll also develop your critical thinking skills, allowing you to choose the best summary statistics for your data.
- What is statistics?50 XP
- Using statistics in the real-world50 XP
- Identifying data types100 XP
- Descriptive vs. Inferential statistics100 XP
- Measures of center50 XP
- Typical number of robberies per London Borough50 XP
- Choosing a measure50 XP
- London Boroughs with most frequent crimes50 XP
- Measures of spread50 XP
- Defining measures of spread100 XP
- Box plots for measuring spread50 XP
- Which crime has the larger standard deviation50 XP
2
Probability and distributions
Probability underpins a large part of statistics, where it is used to calculate the chance of events occurring. You'll work with real-world sales data and learn how data with different values can be interpreted as a probability distribution. You'll find out about discrete and continuous probability distributions, including the discovery of the normal distribution and how it occurs frequently in natural events!
3
More Distributions and the Central Limit Theorem
It's time to explore more probability distributions. You'll learn about the binomial distribution for visualizing the probability of binary outcomes, and one of the most important distributions in statistics, the normal distribution. You'll see how distributions can be described by their shape, along with discovering the Poisson distribution and its role in calculating the probabilities of events occuring over time. You'll also gain an understanding of the central limit theorem!
4
Correlation and Hypothesis Testing
In the final chapter, you'll be introduced to hypothesis testing and how it can be used to accurately draw conclusions about a population. You'll discover correlation and how it can be used to quantify a linear relationship between two variables. You'll find out about experimental design techniques such as randomization and blinding. You'll also learn about concepts used to minimize the risk of drawing the wrong conclusion about the results of hypothesis tests!
R
Introduction to Statistics
Course
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