Читать книгу Statistics in Nutrition and Dietetics - Michael Nelson - Страница 33

The Dodecahedron: ‘If you want sense, you’ll have to make it yourself’.

Every statistical test will produce a number (the test statistic) which you then need to interpret. This is the last stage and often the most difficult part of statistical analysis. The final emphasis in every chapter that deals with statistical tests will be on how to interpret the test statistic. We will also look at the SPSS output to verify that the right set of values has been entered for statistical analysis.

Two concepts deserve mention here: ‘Inference’ and ‘Acceptance’. ‘Inference’ implies greater or lesser strength of fact. It is usually expressed as a probability of a given result being observed. If there is a high probability that the result which you have observed is associated with the hypothesis being true, we talk about ‘strong’ evidence. If the observed outcome is little different from what we would expect to see if the null hypothesis were true, we talk about ‘weak’ or ‘no’ evidence.

At some point, we need to make a decision about whether to accept or reject the null hypothesis, that is, to make a statement about whether or not we believe that the hypothesis is true. ‘Acceptance’ implies a cut‐off point upon which action will be taken. We will discuss cut‐off points in Chapter 5. It is important not to confuse political expediency (acceptance) with scientific validity (inference).