Course
Statistical Techniques in Tableau
IntermediateSkill Level
Updated 10/2024TableauProbability & Statistics4 hr18 videos52 Exercises4,300 XP14,452Statement of Accomplishment
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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
Introduction to Tableau1
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!
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
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FAQs
Do I need statistics knowledge before taking this Tableau course?
No. The course teaches statistical concepts alongside Tableau techniques. You only need introductory Tableau experience to follow along with the drag-and-drop analytics.
What statistical methods can I perform directly in Tableau after this course?
You will be able to create regression models, build confidence intervals, perform clustering analysis, generate forecasts, and conduct both univariate and bivariate exploratory data analysis.
Does the course use machine learning techniques in Tableau?
Yes. The final chapter covers clustering and forecasting within Tableau, showing how to apply these machine learning techniques without writing any code.
What visualizations will I build to explore data statistically?
You will create histograms, box plots, bar plots, scatter plots with trend lines, and summary tables, all using Tableau's built-in statistical functions and analytics pane.
Is this course useful for business analysts who do not code?
Absolutely. All statistical analysis is done through Tableau's visual interface, making it ideal for analysts who want statistical insights without programming.
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