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Course Description
Statistics is the study of how to collect, analyze, and draw conclusions from data. It’s a hugely valuable tool that you can use to bring the future into focus and infer the answer to tons of questions. For example, what is the likelihood of someone purchasing your product, how many calls will your support team receive, and how many jeans sizes should you manufacture to fit 95% of the population? In this course, you'll discover how to answer questions like these as you grow your statistical skills and learn how to calculate averages, use scatterplots to show the relationship between numeric values, and calculate correlation. You'll also tackle probability, the backbone of statistical reasoning, and learn how to use Python to conduct a well-designed study to draw your own conclusions from data.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
- Apply probability concepts and sampling principles to real-world problems.
- Examine relationships between variables using correlation and experimental design.
- Interpret and apply the normal distribution and the central limit theorem.
- Summarize data using appropriate measures of center and spread.
- Use discrete and continuous probability distributions to model real situations.
Prerequisites
Curriculum
Course outline
1
Summary Statistics
Summary statistics gives you the tools you need to boil down massive datasets to reveal the highlights. 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
- Descriptive and inferential statistics100 XP
- Data type classification100 XP
- Measures of center50 XP
- Calculating mean and median100 XP
- Mean, median, and distribution shape100 XP
- Measures of spread50 XP
- Variance and standard deviation100 XP
- Quartiles, quantiles, and quintiles100 XP
- Finding outliers using IQR100 XP
2
Random Numbers and Probability
In this chapter, you'll learn how to generate random samples and measure chance using probability. You'll work with real-world sales data to calculate the probability of a salesperson being successful. Finally, you’ll use the binomial distribution to model events with binary outcomes.
3
More Distributions and the Central Limit Theorem
It’s time to explore one of the most important probability distributions in statistics, normal distribution. You’ll create histograms to plot normal distributions and gain an understanding of the central limit theorem, before expanding your knowledge of statistical functions by adding the Poisson, exponential, and t-distributions to your repertoire.
4
Correlation and Experimental Design
In this chapter, you'll learn how to quantify the strength of a linear relationship between two variables, and explore how confounding variables can affect the relationship between two other variables. You'll also see how a study’s design can influence its results, change how the data should be analyzed, and potentially affect the reliability of your conclusions.
Introduction to Statistics in Python
Course
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