Data Analysis & Statistics

Yes — that is included as standard. You should be able to defend every table in your own words, so we write the interpretation for you to learn from, not to copy blindly.

R is the language; RStudio (now Posit) is the editor most people use to write it. You install both. We cover this properly in our R vs RStudio guide.

If your department expects SPSS output and your analysis is standard, SPSS is usually the lower-risk choice. Python wins when the cleaning is heavy or the method is not in SPSS. We will give you a straight recommendation for your specific project.

Not necessarily. In behavioural and social research a modest R² with a well-specified model and significant theoretically-grounded predictors is a normal, reportable result.

Broadly: covariance-based (AMOS, Mplus, lavaan) for theory testing with larger samples and reflective constructs; PLS-SEM (SmartPLS) for prediction, smaller samples, formative constructs or complex models. We will recommend one for your specific model.

We diagnose why — usually a misspecified measurement model, cross-loading items or a missing path. Modification indices are used cautiously and only where theory supports the change.

For under about fifteen interviews, careful manual coding is perfectly defensible and often faster. Software helps most with volume and with demonstrating an audit trail.