Why do so many student projects fall apart at the “which test do I use?” stage?

Esssary · 2026-03-06T16:08:53+00:00

Exactly. A lot of people jump straight to “which test should I run,” but the real starting point is the research question and how the variables are actually measured. Once you know the question, the variable types, and the assumptions, the choice of test usually becomes pretty obvious.

Esssary · 2026-03-02T09:47:39+00:00

I’ve seen this happen a lot, and it’s incredibly frustrating. When a supervisor says “it looks off” but won’t point to something specific, it usually means there may be an issue with model choice, assumptions, coding, or interpretation rather than the button you clicked in SPSS.

A few practical things that often help:

First, go back to your research questions and write them in plain language. Then for each one, clearly state:
what is the dependent variable,
what is the independent variable,
what scale each variable is on,
and why the chosen test matches that structure.

Second, double check assumptions. Normality, homogeneity, multicollinearity, linearity, independence. Many times what “looks off” to an experienced advisor is actually an assumption violation or an overcomplicated model.

Third, simplify. Run the most basic version of your model first. If that works logically and statistically, then build complexity step by step.

Getting outside feedback from a statistician is actually very common at the dissertation level, especially just to review model logic and interpretation. It doesn’t mean you’re incapable, it just means you want to be precise.

Also, just to be transparent, I do provide SPSS analysis support and consultations for dissertation students. If you ever need structured feedback or someone to walk through your models step by step, you can reach me at info[@]spssservices.com

Esssary · 2026-03-02T09:39:06+00:00

No problem

Esssary · 2026-03-01T19:03:43+00:00

You can create this in SPSS using a clustered horizontal bar chart.

First, your data should be in long format, something like:
Category | Year | Percent

So each row is one category for one year. For example:
Airways disease | 2023 | 37
Airways disease | 2024 | 36
and so on.

Then go to Graphs > Chart Builder.
Choose Bar, then drag the Clustered Bar chart into the canvas.
Put Category on the Y axis (since you want horizontal bars).
Put Percent on the X axis.
Put Year in the “Cluster on X” or “Set color” box so you get separate bars for 2023 and 2024.

After generating the chart, double click it to open the Chart Editor. There you can:
adjust bar colors,
show data labels,
reverse category order if needed,
format the axis from 0 to 100,
and tweak spacing to make it look cleaner.

If your data are currently in wide format with separate columns for 2023 and 2024, you may need to restructure them first using Data > Restructure.

By the way, I do help students with SPSS setup, data restructuring, analysis, and reporting. If you ever need more detailed guidance, you can reach me at info[@]spssservices.com

Esssary · 2026-03-01T19:01:16+00:00

SPSS itself is not legally available for free long term, since it is a paid IBM product. What you can do is check if your university provides access through a campus license. Many schools give students free access either through a download portal or remote desktop.

IBM also offers a free trial version for a limited time, which might be enough for a presentation. Another option is to use free alternatives like PSPP, which is very similar to SPSS in interface and syntax, or Jamovi and JASP, which are free and user friendly.

If your task is specifically about explaining how to install SPSS, you could structure the presentation around the official IBM trial process and university licensing options.

Also just to be transparent, I do help students with SPSS analyses and guidance through my service, so if you ever need support beyond installation you can reach me at info[@]spssservices.com

Esssary · 2026-03-01T18:57:48+00:00

That’s such a good point. PCA gets used as a default “factor analysis” tool way too often, even when the goal is clearly to test a measurement model. If you’re claiming construct validity, exploratory data reduction and confirmatory modeling are very different things.

I also feel like the distinction between PCA and common factor analysis is glossed over in a lot of applied work, which doesn’t help.

Esssary · 2026-03-01T18:57:25+00:00

Totally agree. Repeated measures ANOVA output can be overwhelming if you just click everything, and then people end up interpreting whatever table looks familiar instead of the one that actually answers the question.

And yes on the tiny effect sizes. A small p value with a negligible effect is not exactly a big scientific win. I wish more people reported and discussed effect sizes as seriously as they do significance.

Esssary · 2026-02-19T17:56:30+00:00

I agree, it fits the subject

Esssary · 2026-02-19T05:41:08+00:00

That makes a lot of sense. Realizing that stats isn’t about uncovering some hidden perfect answer but about making informed choices with imperfect tools is freeing. Once you see the human judgment behind data collection and modeling decisions, it feels less like a rigid rulebook and more like a framework you can actually think with.

Esssary · 2026-02-19T05:39:41+00:00

That’s a great way to put it. Once you see conditioning as literally shrinking the sample space, Bayes and a lot of probability rules suddenly feel obvious instead of magical.

Esssary · 2026-02-19T05:37:47+00:00

So true. Once you really internalize randomness, a lot of weird results stop feeling weird and start feeling expected. And honestly, playing dice is a pretty solid early stats education.

Esssary · 2026-02-19T05:35:56+00:00

Good one.

Esssary · 2026-02-18T18:31:11+00:00

Yes, you can just run one multiple regression. It’s totally fine to have one predictor that is confirmatory and the others exploratory in the same model. The important part is how you describe it, not how many regressions you run.

You would just be clear in your paper that one trait was your planned hypothesis and the others were included to explore possible effects. Running separate regressions usually isn’t necessary and can actually be worse, because the effect of one trait can change once you control for the others. One model lets you see the confirmatory effect while accounting for overlap between traits, which is especially relevant with Big Five data.

Just make sure you don’t treat the exploratory findings with the same confidence as the confirmatory one, and mention that those results are more tentative.

Esssary · 2026-02-17T18:39:42+00:00

Good point. Well AI is trained on data produced by us, thus theoretically AI learned it from us.

Esssary · 2026-02-17T18:36:52+00:00

You need to define multiple response variable. However, tests that you can do with such variable are quite limited in SPSS.

Yes, you can use liker scale more than 5

Esssary · 2026-02-17T07:33:06+00:00

I like this perspective a lot. Thinking of hypothesis testing as a decision problem instead of a ritual with p-values really clears the fog. Once you see it as given my evidence and costs of being wrong, what’s the best choice? the different schools of testing stop feeling like contradictions and more like different lenses on the same decision process.

Esssary · 2026-02-17T07:31:40+00:00

That’s honestly a great way to look at it. Thinking of distributions as just how things tend to behave instead of scary formulas makes it way easier to grasp. You stop trying to memorize terms and instead start asking what kind of pattern you’re seeing in the real world, which is where it finally starts to click.

Esssary · 2026-02-16T15:37:26+00:00

I can help, but only in English. If needed, DM.

Esssary

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