Data Summarization First, we need to have our database in good shape before going into final analysis Preliminary analysis, however, helps us detect unsuspected.

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Presentation transcript:

Data Summarization First, we need to have our database in good shape before going into final analysis Preliminary analysis, however, helps us detect unsuspected problems Check to see if sample sizes match up with what you expect Check to see if averages, minima and maxima seem reasonable

Data Summaries in Access We’ve already done this a little bit Summary Query Crosstab Query

Data Summaries using “Regular” Query Exercises using Barrier database Copy database onto your own AFS space with new name so you can save your work Get mean length for each fish species Get mean length for each fish species, for each stream, for above and below positions Get count of number of fish species for each stream, for above and below positions

Data Summaries using Crosstab Query Exercises using Barrier database Crosstab of particle size distribution for each stream and position. If have time, try filling in blanks with zeros (use iif example from fish count)

Data Summaries using Query with Builder Exercises using Barrier database Create query that reports mean fish length by stream and position. Also report sample size and standard deviation. Try to also add in standard error of the mean (which equals the standard deviation divided by the square root of n. Hint – you may need to do this in two steps).