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Descriptive Statistics Course

Descriptive Statistics Course
flexible workload of 4 to 360h
valid certificate in your country

What will I learn?

Gain expertise in essential descriptive statistics methods to prepare real-world data, calculate vital metrics, and analyse channel performance effectively. This focused course covers computing measures of central tendency and dispersion, identifying and documenting outliers, creating informative tables and charts, and applying these techniques using Excel, Google Sheets, Python, and R for quick and accurate results.

Elevify advantages

Develop skills

  • Channel analysis: assess averages, dispersion, and select top-performing channels quickly.
  • Outlier management: identify, rationalise, and document data exclusions logically.
  • Data preparation: tidy, check, and normalise business data using Excel, R, or Python.
  • Core statistics: calculate and explain measures of central tendency, spread, skewness, and kurtosis.
  • Reporting skills: transform statistical findings into clear, compelling business recommendations.

Suggested summary

Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.
Workload: between 4 and 360 hours

What our students say

Your classes are perfect. I purchased the one-year package and finally have the opportunity to follow various topics of my interest without needing to change platforms... I thank you for everything you do, I've already recommended you to other people...
Giulio Carlo
Giulio CarloDigital Marketing Student
I like how the lessons are straight to the point and how I can change chapters and skip content that I don't need.
Mariana Ferres
Mariana FerresPhotography Student
I like the content and the way of presentation and video transcription, which speeds up the process!
Luciana Alvarenga
Luciana AlvarengaNail Design Student
The platform is fast, simple to use. The diversity of content and complementary videos help a lot in learning.
André Felipe
André FelipePrompt Engineering Student

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