SPSS & Research Methods Professional Certificate
Every track, start to finish — from your first research question to defending your results.
All levels44 modules1m of video23h 20m to work throughCertificate
44 modules from the SPSS & Research Methods curriculum. One course, start to finish — no piecing together eight separate purchases.
What you'll learn
By the end of this course
- Ask a good research question and match it to the right design and test
- Get real-world data into SPSS and clean it before it ruins your analysis
- Describe any dataset with the right statistics, real charts, and a normality check
- Run and report every major test for comparing groups, from chi-square to ANCOVA
- Use correlation and regression to show how variables relate to and predict each other
- Build a reliable scale, then move into MANOVA and cluster analysis
- Choose the right specialist method for clinical or epidemiological data
- Report your results and defend them under questioning
Curriculum
44 sections · 44 lessons
Section 1
44 modules
Section 1
- What research actually asks of youTwo studies can run the identical test on the identical data and only one of them survives review. The difference is never the arithmetic.Slides~25 min
- From research question to statistical analysisTwo checks. The first asks whether the question is worth doing; the second asks whether it is answerable at all.Slides~30 min
- Research designs and what each one can proveThat is the entire distinction, and it is the only thing that changes what your study can prove.Slides~30 min
- Variables and levels of measurementFifteen minutes, and it is the highest-return quarter of an hour in this course.Slides~25 min
- Hypotheses, p-values, errors and powerThis is the part that feels backwards, and it stays feeling backwards until you notice what it buys you.Slides~30 min
- Sampling and sample sizeThat is the whole distinction, and everything you are allowed to say about a population follows from which side of it you are on.Slides~35 min
- Validity, reliability and the instrumentTwenty minutes, and it will tell you whether you owe anybody anything.Slides~30 min
- The SPSS workspaceSPSS looks like one program. It is really four windows that pass work to each other, and each one saves a different kind of file.Slides~25 min
- Codebook and data entryThe order is the content of this module. Every step is cheap while the ones after it have not happened yet, and expensive once they have.Slides~30 min
- Getting data in: Excel, Forms, Kobo, REDCapEvery import produces a working file, not a finished one. Keeping them separate is what lets you answer “where did this number come from?” a year later.Slides~25 min
- Cleaning data you did not collectDuplicates come first because a duplicated case multiplies every other problem it carries. Outliers come last because you cannot judge an extreme value until the impossible ones are gone.Slides~35 min
- Missing dataYou cannot choose a method before you have a view about the mechanism. Almost every bad decision about missing data is question 3 answered without question 2.Slides~30 min
- Transform: recode, compute, scoreEvery transformation in SPSS is one of these four, and every one of them writes to a new variable and leaves the original alone.Slides~35 min
- Restructure: select, split, merge, long/wideEvery operation in this module answers one of those two questions. The first three are reversible and persistent; the last three change the file itself.Slides~30 min
- Syntax, and why you should never click twiceThis is the whole of Track B, in the order the modules taught it, as five sections of one text file you can re-run from nothing.Slides~30 min
- Descriptive statistics and Table 1Choosing the right summary for each measurement level.Slides~30 min
- Charts that do not look like SPSS chartsChoosing the chart the data justifies.Slides~30 min
- Normality and distribution checksWhat "assumes normality" actually refers to, and the fact that it is usually the residuals and not the raw variable.Slides~30 min
- Chi-square testsChi-square goodness of fit and chi-square test of independence, and which question each answers.Video + slides~35 min
- One-sample and independent-samples t-testWhat question each t-test answers.Slides~30 min
- Paired-samples t-testWhat makes data paired - before/after, matched pairs, two measures on the same person.Slides~25 min
- One-way ANOVA and post hocWhy three t-tests is the wrong answer, with the inflated-error arithmetic on the slide.Slides~35 min
- Two-way and factorial ANOVAMain effects and interaction, explained before any output appears.Slides~35 min
- Repeated measures ANOVAWhen measurements are repeated on the same participants and why that demands a different test.Slides~35 min
- Non-parametric alternativesWhen a non-parametric test is the right answer and when it is an excuse.Slides~40 min
- ANCOVAWhat a covariate does and what "adjusted means" means.Slides~30 min
- CorrelationWhat r measures and what it does not.Slides~30 min
- Simple linear regressionWhat regression adds that correlation does not - a prediction and a unit.Slides~30 min
- Multiple linear regressionWhat "holding the others constant" means and why it is the whole point.Slides~40 min
- Binary logistic regressionWhy a yes/no outcome breaks linear regression.Slides~40 min
- Ordinal and multinomial logistic regressionWhen the outcome has three or more categories, and whether their order matters.Slides~35 min
- Moderation and mediation with PROCESSThe difference between a moderator and a mediator, with a diagram for each and a study where each is the right question.Slides~40 min
- Reliability AnalysisInternal consistency and what Cronbach's alpha actually measures.Slides~30 min
- Exploratory Factor Analysis and PCAWhat factor analysis is for and how PCA differs from common factor analysis.Slides~40 min
- MANOVAWhen several dependent variables belong in one analysis, and when they do not.Slides~30 min
- Cluster AnalysisSegmentation as a research question.Slides~30 min
- Survival analysisTime-to-event data and why it cannot be analysed as a simple outcome.Slides~40 min
- Agreement and reliability between ratersWhy percentage agreement is not enough.Slides~30 min
- Diagnostic accuracy and ROC curvesThe 2x2 diagnostic table.Slides~35 min
- Complex samples and survey weightsWhy multistage survey data cannot be analysed as a simple random sample.Slides~35 min
- Reporting statistics in APA styleThe anatomy of a reported result - statistic, degrees of freedom, value, p, effect size, confidence interval.Slides~30 min
- Tables and figures for journalsWhat belongs in a table and what belongs in the text.Slides~30 min
- Writing the results and discussionThe order results should be presented in, and why it mirrors the objectives.Slides~30 min
- Defending your analysisThe questions examiners and reviewers actually ask, each with a defensible answer - why this test, why this sample size, why these covariates, why did you exclude those cases, is this causal, what if the assumption was violated.Slides~25 min
About this course
This is the whole curriculum in one course: eight tracks running from picking a research question through preparing data, describing it, testing it, and reporting and defending the results. Nothing is left as a separate add-on — including Reporting and defence, which normally sells on its own to everybody as an extra.
Forty-four modules, about 23 hours and 20 minutes total. The tracks build in sequence: research foundations and data preparation come first, describing data and comparing groups follow as the core inferential work, relationships and prediction and scales and multivariate sit at the advanced end, and specialist methods and reporting and defence round it out — the first for clinical and epidemiological work specifically, the second for anyone about to defend their results, regardless of field.
Buy it once and every track's prerequisites are already satisfied in order, so there's no guesswork about what comes next.
Who it's for
- Postgraduates about to collect data, and thesis students or journal authors preparing to defend results
- Anyone handed a messy spreadsheet with no idea where to start
- Clinical and epidemiological researchers who need specialist methods beyond the standard tests
- Questionnaire-based researchers who need a scale that holds up to review
What you'll need
- Nothing going in — Research foundations, the first track, assumes no prior statistics background
- Access to SPSS throughout, including the PROCESS macro for the relationships-and-prediction modules
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