If SPSS feels overwhelming, start here
If you have just opened SPSS for the first time and your dissertation deadline is sitting somewhere on the horizon, take a breath. You are in exactly the right place.
I am Faryal, and for ten years I have helped students make sense of their data — one dataset, one confusing output table at a time. This page is the map of everything we teach on Results Chapter. You do not need to read it all. Just find where you are, and start there.
How to use this page: the tutorials below are arranged in the order most students actually need them — from opening your first dataset to writing up results your supervisor will love. Every tutorial comes with real practice data you can download, so you learn by doing, not just reading.
Stage 1: Getting comfortable with SPSS
New to SPSS? Start here. These three tutorials take you from “what is this window” to confidently describing your data.
- SPSS for Beginners: Opening Your First Dataset — a gentle first walkthrough (coming November 20)
- Cleaning Data in SPSS: Missing Values, Outliers and Recoding — the unglamorous step everyone skips and everyone regrets skipping (coming November 13)
- Descriptive Statistics in SPSS: Means, Medians and What They Actually Tell You — understand your data before you test anything (coming November 27)
Stage 2: Comparing groups
The most common question in student research: is there a real difference between these groups? These tutorials answer it, step by step.
- Independent Samples T-Test in SPSS — comparing two different groups, e.g. traditional vs workshop teaching (coming November 3)
- Paired Samples T-Test in SPSS — comparing the same people twice, e.g. before and after training (coming November 6)
- One-Way ANOVA in SPSS — comparing three or more groups
- Two-Way ANOVA in SPSS — when two factors might both matter
- Repeated Measures ANOVA in SPSS — tracking change in the same people over time (coming December 15)
Stage 3: Relationships and predictions
When your question is about how variables move together — or whether one can predict another — this is your stage.
- Correlation in SPSS: Pearson, Step by Step — including when to use Spearman instead (coming November 10)
- Simple Linear Regression in SPSS — predicting scores from study hours, with a real case study (coming November 13)
- Multiple Regression in SPSS — when several variables matter at once, and how to tell which ones really do (coming November 27)
Stage 4: Surveys and questionnaires
Working with survey data? Likert scales, categorical answers, reliability checks — it all lives here.
- Chi-Square Test in SPSS — a survey-data case study (coming December 1)
- Reliability Analysis in SPSS: Cronbach’s Alpha — is your questionnaire actually trustworthy? (coming December 4)
- Factor Analysis in SPSS — finding hidden patterns in survey responses (coming December 8)
- Non-Parametric Tests in SPSS — what to do when your data is not normal (coming December 11)
Stage 5: Writing it up (the part your supervisor actually reads)
Running the test is half the job. Reporting it clearly — in APA style, with tables that make sense — is the other half.
- How to Report SPSS Results in APA Style — tables your supervisor will love (coming December 18)
- Common SPSS Mistakes Students Make — and how to fix them calmly (coming December 22)
- Writing Your Results Chapter: From SPSS Output to Academic Prose (coming March 16)
- APA 7 Tables and Figures: A Formatting Checklist (coming March 19)
- How to Discuss Non-Significant Results Without Panic (coming March 23)
- Assumption Checks Your Examiner Will Ask About (coming March 26)
- Turning Your Dissertation Analysis into a Journal Article (coming March 30)
- Responding to Reviewer Comments on Your Statistics (coming April 2)
Stage 6: Beyond SPSS
Different courses need different tools. We cover those too — same calm, step-by-step style:
- EViews & Time Series — from your first workfile to ARIMA forecasting and Granger causality (December–January)
- NVivo & Qualitative Analysis — coding interviews and thematic analysis, plus mixing NVivo with SPSS (January–February)
- SmartPLS & AMOS — structural equation modelling, reliability and validity checks (February)
- R, Python, Stata & Minitab — including an honest guide to choosing the right tool for your project (January–March)
- G*Power: How Many Participants Do You Actually Need? (March 12) and Your 30-Day Dissertation Data Plan (April 9)
Not sure which test you need?
That is the single most common question students ask me. I made you something free for exactly this moment: our SPSS Dissertation Workbook walks you through choosing the right test for your research question, with a simple decision flow and space to plan your own analysis.
Want help with your own data?
Tutorials can take you far, but sometimes you just want someone experienced to look at your dataset with you. I offer free initial guidance on WhatsApp — send me your question, and we will figure out the next step together.
Frequently asked questions
I am a complete beginner. Where do I actually start?
Start with Stage 1 above, in order: opening your first dataset, then cleaning data, then descriptive statistics. Do not jump to ANOVA on day one — the foundations make everything after them easier.
How do I know which statistical test to use?
Match the test to your research question: comparing groups means t-tests or ANOVA; relationships between variables mean correlation or regression; survey reliability means Cronbach’s alpha. Our free workbook walks you through this decision step by step.
Do I need to learn every test on this page?
No — and please do not try. Most dissertations need only two or three tests. Learn what your research questions require, and bookmark the rest for later.
Can you help me with my own dissertation data?
Yes. I offer free initial guidance on WhatsApp, and 1-to-1 help if you need someone to work through the analysis with you.
Also from us: if the thought of defending all this in your viva makes your stomach flip, visit Confident Viva — our calm corner for viva preparation.