People Analytics Deconstructed
Are you responsible for understanding an employees’ experience? Have you tried to incorporate people analytics in your organization but have struggled? Have you ever wondered what it means to have a data culture? Would you like to make more data-driven decisions? These are the kinds of discussions you can expect to hear on People Analytics Deconstructed. Co-hosts Ron Landis and Jennifer Miller are co-founders of Millan Chicago, a data science consulting company dedicated to helping organizations make the most out of their data. Each week, they will ‘deconstruct’ modern and contemporary topics in the People Analytics space.
People Analytics Deconstructed
When Simple Statistics Have Big Impact
•
Millan Chicago
•
Season 1
•
Episode 17
In this episode, Ron Landis and Jennifer Miller deconstruct the importance of utilizing descriptive statistics as the foundation of starting the data analytic process. As many advanced statistical techniques are built on descriptives such as the mean and standard deviation, it is imperative to understand the characteristics of the data set being analyzed.
In this episode, they have conservations around the following questions:
- What are the various ways in which central tendency is used to understand the nature of a data set?
- What are the advantages and disadvantages of using different measures of central tendency?
- What are the different measures of dispersion?
- What are some contexts in which certain measures of dispersion should be used?
Links