Statistical analysis

What it is

Statistical analysis in an academic context means processing collected data — from questionnaires, experiments, public databases, or administrative records — with appropriate tools, and interpreting the results in relation to the hypotheses and research questions formulated in the thesis.

Our service covers the full empirical workflow: from dataset preparation (cleaning, coding, checking for missing values) through running the analyses themselves to writing the interpretation in the academic language of your field. We work with SPSS, R, Python (pandas, scipy, statsmodels), and EViews — you choose the platform, or we decide together based on the type of analysis and your faculty’s requirements.

The emphasis is on understanding, not just numbers. The tables and figures we deliver are accompanied by a written interpretation that you can incorporate directly into your empirical chapter and defend before the examination committee.

How it works

1. You send the data and context. Upload the dataset (Excel, SPSS .sav, CSV, or another format) along with a brief description: which hypotheses you want to test, which variables you have, the scale of measurement, and any specific requirement from your supervisor.

2. We agree on the analysis plan. Based on your data and hypotheses, we propose the appropriate tests and methods — regression, ANOVA, t-test, factor analysis, Pearson/Spearman correlations, time series, or others. You confirm the plan before we proceed.

3. We prepare the dataset. We check distributions, outliers, missing values, and variable coding. If there are issues that affect the validity of the analyses, we flag them before continuing.

4. We run the analyses and export the output. We generate the complete output in the chosen platform and prepare the tables and figures in the format needed for insertion into a Word or LaTeX document.

5. Preparation session for the defence. We go through the results together — what each indicator means, how to respond if a committee member asks about the choice of test or about the method’s limitations.

Frequently asked questions

Do I need to know statistics to use this service?

An advanced level is not required. The service is designed precisely to help you understand what was analysed and why, not just to deliver numbers. The preparation session for the defence is specifically structured for that stage.

What if my data has problems — many missing values or a small sample?

Imperfect data is common in academic research. We will communicate clearly what limitations the data imposes and which methods are appropriate under those conditions. We do not run analyses that are not methodologically justified given the data you have.

Can you work with secondary data — Eurostat, INS, World Bank databases?

Yes. If you have already identified the source and know which variables you need, send us the downloaded dataset. If you need help extracting the data, mention that when placing the order.

Can the written interpretation be integrated directly into the thesis?

The interpretation we deliver is written in your thesis’s language and can be integrated and adapted by you in the empirical chapter. It is the starting point for your text, not a finished passage to be copied without understanding.