1. Day 2: introduction

2. Objectives Learn different tests to asses data quality
Day 2: introduction
Objectives
Learn different tests to asses data quality
Practice the tests
Understand the challenges of each test

3. Evaluating data quality
Day 2: introduction
Evaluating data quality
Numerical summaries are useful for checking that data are within an expected range
Graphical methods are often more informative than numerical summaries
A key graphical method for examining the distribution of a variable is the histogram

4. Debate what tests do you know on data quality? Do you use them often?
5 min
Debate
what tests do you know on data quality? Do you use them often?
Start the day by asking participants what tests do they know on data quality? What is it testing (sampling? measurement errors?) And see which ones are going to be reviewed during day 2.

5. Data files CSV files (Comma Separated Value) Day 2: introduction
The CSV format has been used because it is easy to use with different data analysis systems. It can be read as a simple text file too
It can be open in Excel. If you have an Excel that uses the comma (“,”) to separate the decimal points, make sure to indicate to excel that your file is using the comma as a tab. This happens with Spanish users or computers in Spanish

6. Software The NIPN data quality toolkit Who Anthro Data Survey Analyser
Day 2: introduction
Software
The NIPN data quality toolkit
Who Anthro Data Survey Analyser
Excel
STATA
SPSS
Online calculators
We can use any of these!

7. Software Who Anthro Data Survey Analyser
Day 2: introduction
Software
Who Anthro Data Survey Analyser
New version coming soon
This can be a quick solution for today´s excercises but you can also use Excel and a couple of online calculators

8. Exercise : preparing your data
Day 2: introduction
Exercise : preparing your data
Open the file ex01.csv using Excel or other software
The file ex01.csv is a comma-separated-value (CSV) file containing anthropometry data from a SMART survey in Angola.
How many variables the file has? What are they?
What are the problems with the sex variable?
Amend the sex variable until it cab be read by WHO anthro
Build an histogram in Excel for any variable you want
Make sure participants can open this file with Excel and WHO Anthro (or ENA, SPPS or R)