data-quality-assurance

“coming soon”: Data Quality Assessment

$600.00

“Not everything that can be counted counts, and not everything that counts can be counted”. Albert Einstein, Physicist

This intermediate-level course describes and explains the importance of data quality assessment of qualitative and quantitative data in the evaluation context.  Systematic collection and analysis of various of quantitative and quantitative data is the cornerstone of program evaluation. It is essential that data be of the highest possible quality. The overall learning goal for this course is to increase attention to data quality in the evaluation practice.

By the end of this course, you should be able to:

  1. define data quality and identify points in the evaluation process where it should be assessed;
  2. identify, prevent and address typical errors and quality issues in primary and secondary data for qualitative and quantitative data;
  3. identify, prevent and address ethics issues that affect data quality;
  4. identify, prevent and address typical errors and quality issues in data triangulation.

Estimated Time to Complete:  5 hours

Prerequisites: Familiarity with basic evaluation concepts plus direct experience conducting or commissioning an evaluation. Prior completion of the CES Essential Skills Series is advised.

Evaluation Competencies addressed:  [X] reflective; [X] technical; [X] situational; [ ] management; [ ] interpersonal.

Category:

Data Quality Assessment

“Not everything that can be counted counts, and not everything that counts can be counted”. Albert Einstein, Physicist

This intermediate-level course describes and explains the importance of data quality assessment of qualitative and quantitative data in the evaluation context.  Systematic collection and analysis of various of quantitative and quantitative data is the cornerstone of program evaluation. It is essential that data be of the highest possible quality. The overall learning goal for this course is to increase attention to data quality in the evaluation practice.

By the end of this course, you should be able to:

  1. define data quality and identify points in the evaluation process where it should be assessed;
  2. identify, prevent and address typical errors and quality issues in primary and secondary data for qualitative and quantitative data;
  3. identify, prevent and address ethics issues that affect data quality;
  4. identify, prevent and address typical errors and quality issues in data triangulation.

Estimated Time to Complete:  5 hours

Prerequisites: Familiarity with basic evaluation concepts plus direct experience conducting or commissioning an evaluation. Prior completion of the CES Essential Skills Series is advised.

Evaluation Competencies addressed:  [X] reflective; [X] technical; [X] situational; [ ] management; [ ] interpersonal.

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