Evaluation Analysis

How does Evaluation Analysis work?

At the end of 2021, I observed around 400 days' worth of recorded data. Various analyses could be performed with such data and wanted to test the relationships among the variables. For example, I wanted to know how meditation affected my lifestyle and other variables, such as screen time or the total percentage of the day. By finding various cause-and-effect relationships among variables, I was able to derive meaningful insights about my lifestyle. 

Monthly Evaluation

At the end of every month, an evaluation is done to analyze my lifestyle. These are all of the past assessments beginning from February to November of 2021. As shown above, one can observe improvements in the wake-up time and total percentage as time progresses.

learn more about the graph

November Evaluation

As a sample, I will analyze the month of November. The analysis process includes the following. 

  1. Data comparison with the previous month
  2. Test correlation changes with the previous month
  3. Test correlation changes with accumulated data
  4. Further analysis when an interesting observation found

1. Data Comparison

  • The above code compares specified months written in the format shown above. This output is helpful since it provides a numerical comparison between any given months. Also, note that these lines of code will work with any particular month within all data set.