Hypotheses
Argue each hypothesis as a statement whose opposite data results can falsify
Explanatory research restates the RQ as hypotheses, which are abstract statements whose opposite the research results can falsify, e. g. the RQ: "Do subjects prefer polite software?" allows the hypothesis "Subjects will use polite more than impolite software". This is not actually proven, but its "null" hypothesis opposite, that "Subjects will respond to polite and impolite software the same" can be disproved. The null hypothesis assumes a random data distribution, so one can estimate statistically if the data supports it or not. The null hypothesis is usually considered unlikely if its probability of occurring is less than 5% or 1 chance in 20 (stated as p < 0.05), and very unlikely if the probability is less than 1% (P<0.01). In these cases the null hypothesis is rejected, and so the hypothesis is "supported". Otherwise the hypothesis is "not supported".
Tags: Logical, Quantitative, Literature Review
Example(s)
(Use a descriptive name, e. g. "ITExample". Or click on an existing collection and edit it.)
