Question
Background Unplanned absences can be costly to organizations. Especially when activities must occur at a specific time, processes have to be stopped, or other employees
Background
Unplanned absences can be costly to organizations. Especially when activities must occur at a specific time, processes have to be stopped, or other employees then have to perform the work of the absent employees. The COO of your company, Burdock Industries (BI), recently reviewed the People Operations dashboard you set up for senior management in your organization. She is very concerned about a rising trend in unplanned absences this year and that this may be negatively impacting the business. She has asked the CHRO if the People Analytics team could conduct some research to try and uncover what might be driving* the increases in unplanned absences at BI and share recommendations on how to address this alarming trend.
After conducting interviews with leaders, frontline managers and even some employees, as well as reading the latest research on drivers and consequences of absenteeism, you have identified some potential factors associated with unplanned absences that you would like to include in your quantitative analysis. These include the number of OT hours worked, commute time and turnover intention.
Questions:
- What numbers should I use below to build a scatterplot to identify the relationship between 3 variables (OT hours, commute time, and TO intention) with outcome variable (unplanned absences)?
- How or what does those number tells me about the correlation?
- I'm unclear how to or which number to look at to make analysis
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