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Here are a couple of exercises to practice calculating descriptive stats and using these to gain some insight about our data.

Bank Churn Exercise

Use the bank churn dataset - click here for description and download.

This has several numeric columns such as:

• Age
• Tenure (years of being bank’s customer)
• Account balance
• Estimated salary

For one or more of these columns, calculate the summary descriptive statistics (mean, median, min, max, standard deviation). Do these stats tells us anything about the distribution of the values in each column?

Use whichever software suits you best. Excel is always a good choice.

London Bike Hire Exercise

Transport for London (TfL) introduced bike hire in 2010. This dataset has the number of bikes hired every day from 30th July 2010 to this year.

The London Bike Hire Dataset page has some details and a link to download the data.

Tasks

Analyse the data with Excel, Power BI or any tool that you prefer. The following questions below serve to start your analysis but feel free to ask other questions.

• How many observations? What are the start & end dates? Is this a continuous dataset with values for every date between the start and end date or are there any gaps?
• Get some descriptive stats on this dataset: e.g., min, max, median, mean, standard deviation
• Visualise the data:
  • the entire series as bar / line chart
  • by day of week and by year as a box-whisker chart (or matrix)
  • as a histogram
• What does each chart tell us about the data?