First, add labels and value labels where missing and adjust decimals to zero in data sheet (i.e., prepare sheet carefully).
The descriptive statistics section reports personal characteristics in text .
One option is to expand this section by adding an Item and scales subsection.
Report each of the sub-scales in turn, either via a table or a graph of the mean values (labels important here).
The graph makes it easier for the reader to compare items so has some advantages.
Report the items to which participants responded positively vs. those to which they responded negatively.
Also, with each sub-scale, report the Cronbach’s Alpha statistic .
At end of this section, include a correlation matrix of bivariate correlations for the scales scores.
The following section is entitled Inferential statistics.
In it, outline intention of testing a series of hypotheses, in the main by using linear and stepwise regression (and possibly also hierarchical regression to test moderating influences).
Note that are transforming categorical IVs (personal characteristics such as gender and type of user) into dummy variables to facilitate these regressions.
It might be worth starting the inferential section by listing the hypotheses, together with relevant IVs and DVs.
This organisational strategy should help one to think about which IVs and DVs best test a specific hypothesis.
It would also prevent one from using the same list to test differing hypotheses (not that I’m suggesting you do).
When obtain a significant outcome, especially one involved a categorical (dummy) or ordinal level IV, then graph the outcomes.
I use stepwise regression because it selects the most powerful IVs more clearly.
It might be worthwhile using SEM procedures to model the more complex relationships between IVs and DVs.