⭐ EFIKO Original · Free micro-certificate
Statistics for Research
A Beginner's Guide to Understanding and Applying Data in Your Research
Start this free courseThis practical, mobile-friendly course introduces the core statistical concepts every researcher needs to collect, summarise, and interpret data with confidence. Designed for beginners with no prior statistics background, it moves step by step from describing data to drawing sound conclusions, always grounded in real research examples relevant to African contexts. By the end you will be able to read statistical results critically, choose appropriate methods for your questions, and avoid common mistakes that undermine research quality. No expensive software is required; examples work with free tools and simple calculations.
What you'll learn
- Explain foundational statistical concepts including populations, samples, variables, and levels of measurement.
- Apply descriptive statistics to summarise datasets using measures of central tendency and spread.
- Interpret probability, distributions, and the logic of sampling in research.
- Conduct basic hypothesis testing and interpret p-values and confidence intervals correctly.
- Select appropriate statistical tests based on research questions and data types.
- Evaluate statistical results critically and communicate findings clearly and ethically.
Course sessions
- Foundations: Why Statistics Matters in Research. Statistics turns limited data into credible claims; understanding population, sample, variable, data, and the four levels of measurement is…
- Describing Your Data: Descriptive Statistics. Descriptive statistics summarise data using a measure of centre (mean, median, mode) and a measure of spread (range, variance, standard dev…
- Probability and Distributions. Probability quantifies uncertainty and lets us infer about populations from samples, while the normal distribution and z-scores describe ho…
- Sampling and the Logic of Inference. Random probability sampling plus the Central Limit Theorem let researchers use a small sample to make trustworthy, quantified claims about…
- Hypothesis Testing and Confidence Intervals. Hypothesis testing pits a null against an alternative, using p-values and confidence intervals to judge evidence while honestly acknowledgi…
- Choosing the Right Test and Communicating Results. Match your test to your data type and question — t-test for comparing two means, chi-square for linked categories, correlation for two nume…
Sample lesson: Foundations: Why Statistics Matters in Research
Statistics is the science of collecting, organising and interpreting data so we can make trustworthy claims from limited information. Start with four core terms. A POPULATION is every unit you care about (for example, all students at your university). A SAMPLE is the smaller group you actually measure (say, 300 random…
Competencies you'll gain
- Summarising and visualising research data using descriptive statistics
- Interpreting probability, distributions, and sampling in research contexts
- Conducting and correctly interpreting basic hypothesis tests and confidence intervals
- Selecting appropriate statistical tests for given research questions and data types
- Communicating statistical findings clearly, critically, and ethically
Frequently asked questions
Is the Statistics for Research course free?
Yes. Statistics for Research is a free EFIKO Original micro-certificate course — you can learn it at no cost and earn a verifiable certificate on completion.
Do I get a certificate for Statistics for Research?
Yes. Pass the final assessment and you earn a verifiable EFIKO certificate with a QR code and public verification link, listing the competencies you achieved.
How long does Statistics for Research take?
About 6 hours across 6 short sessions, each with a lesson, quiz and flashcards. You can learn at your own pace, even offline.
Who is Statistics for Research for?
It is designed for university students and early-career researchers across all disciplines, at a beginner level. No prior experience is assumed.