Research Guides

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• PhD Research Support Where doctoral research actually stalls, what genuinely helps at each stage, and how to tell which kind of help you need.

Literature Review

Why chapters get sent back, the difference between summarising and synthesising, and how to make a gap out of a pile of reading.

• Systematic Literature Review What makes a review systematic, the work people underestimate, and when a different type of review is the better choice.

Mixed Methods Research

When combining strands is genuinely justified, the four designs worth knowing, and why integration is the whole point.

• Convergent & Embedded Designs Running both strands at once, comparing them honestly, and treating disagreement as a finding rather than a problem.
• Explanatory Sequential Design Numbers first, then the explanation — and the participant-selection decision that decides whether the design was worth running.
• Exploratory Sequential Design Exploring first, then measuring — and why the step in the middle is a whole project people forget to budget for.
• Mixed Methods Integration The part that makes a study mixed methods rather than two studies — where integration happens, how to show it, and how it is judged.

PhD Data Analysis

Why analysis takes longer than anyone plans for, how to match it to the design you already have, and the difference between output and findings.

• Mixed Methods Research When combining strands is genuinely justified, the four designs worth knowing, and why integration is the whole point.
• Qualitative Research What qualitative research is for, which design answers which kind of question, and how to defend a small sample properly.
• Quantitative Research How the design decides what you are allowed to conclude, why measurement matters more than the model, and where quantitative theses come apart.
• Thesis Data Analysis Support What analysis support actually involves, what you receive, and how to tell whether you need it.

PhD Research Methodology

What a methodology chapter actually has to establish, why philosophy is in there at all, and how to choose a design your question can carry.

• Conceptual & Theoretical Framework What each one is, why the difference matters, and how to build a framework that does work rather than decorating the proposal.
• Research Methodology Consulting A design reviewed before you collect anything — the cheapest hour in a doctorate, and the one most people skip.
• Research Methods The practical ways to collect data, what each one costs in time and access, and how to choose between them without wasting a year finding out.
• Research Questions & Hypotheses How to know when a question is finished, the difference between aims, objectives and questions, and when a hypothesis is required at all.

PhD Research Support

Where doctoral research actually stalls, what genuinely helps at each stage, and how to tell which kind of help you need.

• Literature Review Why chapters get sent back, the difference between summarising and synthesising, and how to make a gap out of a pile of reading.
• Our Research Expertise Who does the work, how people are matched to problems, and the standards the work is held to.
• PhD Data Analysis Why analysis takes longer than anyone plans for, how to match it to the design you already have, and the difference between output and findings.
• The PhD Research Journey What happens at each stage of a doctorate, where the time actually goes, and the decisions that are expensive to reverse.
• PhD Research Methodology What a methodology chapter actually has to establish, why philosophy is in there at all, and how to choose a design your question can carry.
• Research Mentoring & Academic Careers The conversations that are hard to have inside your own department, with someone who has been through it.
• Research Proposal What a proposal has to persuade a panel of, why most rejected ones fail in the first page, and the feasibility question nobody prepares for.
• Technical & R&D Consulting Independent technical judgement for companies — the questions an internal team is too close to answer, addressed by someone who has done the research.
• Thesis & Dissertation Support What each chapter has to establish, why the discussion is where most theses are weakest, and how to prepare for the viva.

Qualitative Data Analysis

What to actually do with transcripts: coding, the step from codes to themes, choosing an approach, and what the software will and will not do for you.

• Content Analysis Building a coding frame that holds, when counting is legitimate, and how content analysis differs from thematic analysis.
• Interview & Focus Group Analysis Transcription decisions that shape what you can claim, what focus group data demands that interview data does not, and the gap between what people say and what they do.
• NVivo For Qualitative Analysis What NVivo genuinely does for a thesis, what it cannot do for you, and why “analysed using NVivo” reads badly to an examiner.
• Qualitative Coding What a code actually is, the types worth knowing, building a codebook that holds, and staying consistent across a long dataset.
• Thematic Analysis The six phases as they are actually meant to be used, why themes do not emerge, and the difference between the versions examiners expect you to name.

Qualitative Research

What qualitative research is for, which design answers which kind of question, and how to defend a small sample properly.

• Case Study Research Defining the case and its boundary, choosing between the main traditions, and answering the generalisation question before it is asked.
• Grounded Theory What grounded theory actually commits you to, the three versions you must choose between, and why most theses claiming it are doing something else.
• Phenomenological Research Descriptive or interpretative, what bracketing asks of you, and why most studies calling themselves phenomenology are not.
• Qualitative Data Analysis What to actually do with transcripts: coding, the step from codes to themes, choosing an approach, and what the software will and will not do for you.
• Trustworthiness In Qualitative Research The four criteria, the techniques that actually evidence them, and why member checking is not the safe bet it looks like.

Quantitative Research

How the design decides what you are allowed to conclude, why measurement matters more than the model, and where quantitative theses come apart.

• Research Statistics How to choose a test from your question and your data, what a p-value does and does not tell you, and why effect size matters more than significance.
• Validity & Reliability The four kinds of validity examiners distinguish, the threats that undermine each, and why consistency is not accuracy.

Research Methods

The practical ways to collect data, what each one costs in time and access, and how to choose between them without wasting a year finding out.

• Questionnaire Design Writing items that measure what you intended, the faults that quietly ruin data, and why piloting is the cheapest thing you will ever do.
• Research Ethics What committees actually assess, why applications come back, and the ethical decisions that arrive after approval.
• Sampling Methods Which sampling logic applies to your study, how to choose a method, and how to defend the sample you could actually get.

Research Statistics

How to choose a test from your question and your data, what a p-value does and does not tell you, and why effect size matters more than significance.

• ANOVA & T-Tests Comparing groups without inflating your error rate, which variant fits which design, and the effect sizes examiners now expect.
• Correlation & Regression Which coefficient for which data, what regression coefficients actually mean, and the causal language that quietly gets theses into trouble.
• Descriptive Statistics Choosing the right summary for your distribution, why the mean is often the wrong answer, and how to present results so a reader can check them.
• Effect Size & Confidence Intervals Which effect size for which test, how to interpret one honestly, and the precise wording of a confidence interval that examiners listen for.
• Factor Analysis & Reliability Exploratory or confirmatory, how many factors to retain, and what Cronbach’s alpha does and does not tell you.
• Non-Parametric Tests What they actually assume, when they are the right choice, and why the Mann–Whitney test is not simply a comparison of medians.
• Python For Research Where Python beats the statistics packages, where it does not, and the questions an ethics committee will ask about scraped data.
• R For Research When R is worth the learning curve, what reproducibility actually buys you, and the honest cost of switching mid-doctorate.
• Sample Size & Power Analysis How the calculation actually works, why the hard part is deciding what effect would matter, and why post hoc power answers nothing.
• SPSS For Thesis Analysis The data preparation decisions that quietly corrupt results, why syntax matters more than menus, and what the output will never warn you about.
• Stata For Research Why whole fields standardised on it, where it genuinely outperforms the alternatives, and the one habit that makes it worth using.
• Statistical Assumptions What each test actually assumes, why the software will never tell you, and what to do when a condition genuinely fails.
• Structural Equation Modelling Measurement model before structural model, mediation done the current way, and the causal claim cross-sectional SEM cannot support.

Structural Equation Modelling

Measurement model before structural model, mediation done the current way, and the causal claim cross-sectional SEM cannot support.

• AMOS For SEM The two-step sequence, what the fit indices do and do not settle, and why modification indices are the fastest route to an indefensible model.
• SmartPLS & PLS-SEM The assessment sequence a PLS study is judged on, reflective versus formative measurement, and the fit indices you should not be reporting.

Thesis & Dissertation Support

What each chapter has to establish, why the discussion is where most theses are weakest, and how to prepare for the viva.

• Academic Writing Why academic prose is hard to read, the paragraph habit that fixes most of it, and how to write when you do not feel ready.
• Viva Preparation What examiners are actually doing, the questions that come up in almost every viva, and why a mock is worth more than another read of the thesis.