Prepare the Data for Analysis

By Barry Sweeny, 2010


1. Assemble all the data that are relevant to the success of participants in the program. Put similar or related data in folders together. Try to use:

  • At least 3 to 5 years of trend data. Since your program may be just beginning and only have this year’s baseline data, the trend data mentioned above may only be what are called “found data“. That is data someone else collected for other reasons, but which you can use for your purposes.
  • Hard data (such as attendance, demographics, test scores, etc.)
  • Soft data (opinion data such as from surveys, observations, focus groups, or interviews).
  • Data which address program goals and objectives
  • Participant growth
  • Program and activity mplementation, etc.
  • Data which describe both mentor and protege knowledge and behaviors on relevant topics

Clear label each data set with a permanent title describing the date it was collected, the data source, what it includes, etc.

2. Display these data so that any trends or contrasts are apparent and summarized in a chart.

Use one page per topic if possible. Data must be displayed so it reveals patterns because the data has no inherent meaning by itself. It is only if a pattern can be found in the data that meaning can be assigned, and then only those like the staff can appropriately assign the meaning since only they know what may have contributed to making the pattern. Of course, this is best done by a computer if you can input the data into a spread sheet.

3. Data come in many different forms, such as percentiles, quartiles, lists of statements, and meets/exceeds/does not meet. Convert the form each of the data are in to ONE common form. I recommend using the “meets¬† /exceeds ¬† /does not meet” form. Here is how to do this conversion.

Regardless of the original form of the data…

  • If the score or data level is “satisfactory”, write it as “meets” our expectations (M).
  • If the score or data level is “not satisfactory”, write it as “does not meet” our expectations. (DNM)
  • If the score or data level is significantly “better than satisfactory”, write it as “exceeds” our expectations (E).

4. Make a “Hard & Soft Data Comparison Chart” to collect the converted data (M / E / DNM) on a single page if possible. Write a title at the top, topics along one side and data sources along the other. Enter the M/E/DNM in the right places. where the appropriate columns and rows intersect.