By Henry Griffiths
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19 Logarithmic transformation of positively skewed data. 8329 • The mean calculated using log-transformed data is known as the geometric mean. 5108 ... ... 4586 21 Handling data DESCRIBING THE DISTRIBUTION OF ONE GROUP INTERVAL, RATIO ORDINAL NOMINAL NON-GAUSSIAN DISTRIBUTION CENTRAL TENDENCY: mode Data transformation CENTRAL TENDENCY: percentiles (including the median) SPREAD: inter-quartile range GAUSSIAN DISTRIBUTION CENTRAL TENDENCY: mean SPREAD: standard deviation Fig. 20 Choosing the correct summary measure.
HINTS AND TIPS It is impossible to log-transform negative values and the log of 0 is –1. If there are negative values in your data, it is possible to add a small constant to each value prior to transforming the data. Following backtransformation of your results, this constant needs to be subtracted from the final value. For example, if you add 4 units to each value prior to log-transforming your data, you must remember to minus 4 units from the calculated geometric mean. Calculating the anti-log • As any base can be used to log-transform your data, it is important that you understand some basic rules when working with logs.
Alternative hypothesis (HA): There is an association between simvastatin and the risk of stroke in individuals with a high risk of cardiovascular disease. The second step is to collect the data (Fig. 5) and determine what statistical test is appropriate for data analysis (discussed in Chapter 15). • As we are comparing nominal data in two unpaired groups, with n > 5 in each cell (Fig. 5), the statistical test most appropriate for analysing these data is the chi-squared test (please refer to Fig.
A handbook of veterinary parasitology : domestic animals of North America by Henry Griffiths