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Cleaning, sorting and merging data
It is important that data with which you are working to analyse results and draw conclusions is ‘clean.’ This means that it is consistent, accurate and complete.
You should be alert to any anomalies, either within the numerical data itself or the demographic information attached to it. For example, a student number may be missing, or a cell has no information, or a year level for one student is incorrect. Making sure that data is clean before you start to work with it will help prevent misinterpretations, or having to repeat the process if you discover problems later.
Consistency
It is essential that each data record is consistent with others. If you are downloading information from more than one source, it must be in exactly the same format. Be sure to check before you combine data (for example, records for more than one class) that the format is the same.
Data that shows progress over time should always be matched so that the same students are represented in both sets of figures.
Accuracy
The data must be accurate. Scan all data for anomalies – are you sure you have the right student records, the right test results? If the data is entered manually, data entry should be double-checked for accuracy.
Completeness
Each data record should be complete. Make sure that there are no student records that have no result against them. Although it’s important to find out why some students do not have assessment results, their records for the purposes of immediate analysis should be deleted. This is particularly important when calculating medians and means, as empty records can skew the data.
To learn how you can use Excel to sort and merge assessment data, view this video tutorial: Cleaning sorting and merging data.