ESDU 91017 uses a flowchart to guide its user in the application of statistical techniques to the analysis of performance data from which all but random variability has been removed@ that is they have been reduced to standard conditions. After introducing the concept of hypothesis testing@ the possibility of combining small samples in a larger sample@ so improving the accuracy of predictions@ is considered. Fisher's Variance Ratio F test is used to decide with a certain confidence whether the samples are from the same population@ and Student's t test determines the significance between sample means. Larger samples@ exceeding 30 points@ either from combined smaller samples or as measured@ are treated using Normal distribution statistics provided the Chi Squared Test for normality with a chosen confidence is met. If the test fails@ a transformation of the data (for example@ taking the logarithm) may provide a Normal distribution. The use of probability graph paper as a means of analysing data to the Normal distribution is explained. Bartlett's test for the consistency of variances calculated from three or more samples is introduced. Regression is considered because@ although not a statistical technique@ the results are analysed statistically. The manual calculation of linear two variable regression is discussed@ and determination of variance about the regression line@ the significance of the regression relationship@ regression confidence intervals@ and the correlation coefficient and its significance are treated. Multiple linear regression is briefly considered. Tables present the statistics of the Normal distribution@ Student's t distribution@ the Chi Squared distribution and the F distribution. Examples on the use of the methods are found in ESDU 91018 to 91020@ 92021 and 92022@ 93023 and 96024.