#### Objective

- Understand the different tools available in a WIDE for developing data science projects.
- Recall basic concepts of Descriptive Statistics and apply them to data exploration tasks.

#### Material

#### ToDo

- Create a project on azure notebooks devoted to work for this lecture with the material available on github.
- Have a look at the notebook that implements the analysis for Understanding the Gender Divide at Work
- Going through the notebook while executing it, have a look at the use of descriptive analytics concepts for exploring data.
- Explain the use of statistical measures for understanding data collections.
- Explain the importance of computing data distributions for the attributes of the data sets.
- Explain why is it important to observe outliers in the analysis. How do you technically observe outliers?
- Which is the strategy to measure the relative risk of early promotion? How did you processed the data to evaluate this risk?

#### To Hand In

- Use the notebook that you analyse and add at the end of the document using MarkDown a section where you explain the use of descriptive analytics in data exploration
- Create a figure of the pipeline you extracted and add it to your notebook
- Send the modified notebook to genoveva.vargas@gmail.com

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