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Course Description
Use Built-in Statistical Functions
Take your reporting skills to the next level with Tableau’s built-in statistical functions.Perform EDA and Create Regression Models
Using drag and drop analytics, you'll learn how to perform univariate and bivariate exploratory data analysis and create regression models to spot hidden trends.Apply Machine Learning Techniques
Working with real-world datasets, you’ll also use machine learning techniques such as clustering and forecasting. It’s time to dig deeper into your data!Prerequisites
Curriculum
Course outline
1
Univariate exploratory data analysis
Exploratory data analysis, or EDA, is a fundamental step when doing data research. Getting the first insights of your data is easy in Tableau: you’ll be creating and interpreting tables, bar plots, histograms, and box plots in no time!
- Welcome to the course!50 XP
- Interpreting histograms100 XP
- EDA in Tableau: tables and bar plots50 XP
- Superstore data: table100 XP
- Superstore data: bar plot100 XP
- EDA in Tableau: histograms50 XP
- Superstore data: histogram promo100 XP
- Superstore data: histogram bin size100 XP
- Box plots and distribution characteristics50 XP
- Which visualization should you choose?100 XP
- EDA in Tableau: box plots50 XP
- Superstore data: boxplot100 XP
- Superstore data: compare box plots100 XP
2
Measures of spread and confidence intervals
In this more conceptual chapter, you’ll dive deeper into the use of different measures of center and spread, and how they should be used in Tableau. You’ll learn about the use of the summary card, the difference between sample and population, and how variance, standard deviation, and confidence intervals can be calculated and visualized.
3
Bivariate exploratory data analysis
It's time to look at two variables at a time. Describing the relationship between two variables, or regression, is a great way to spot trends in your data. You'll learn how to find the best trend line, describe the trend model, and predict future observations, using dinosaur data!
4
Forecasting and clustering
In this last chapter, you’ll explore two more advanced statistical techniques: forecasting and clustering. Forecasting helps you detect recurring patterns in your time-series data, and can predict how these patterns will change in the future. With clustering, you’re able to detect patterns in unlabeled data, allowing you to slice and dice your dataset to reveal hidden insights.
Statistical Techniques in Tableau
Course
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