Statistics Basics: online course with internship agreement
Statistics Basics teaches you to summarise survey data in a spreadsheet, judge how unusual a value is, build confidence intervals, test whether a difference is real and report findings clearly. It also introduces SQL, R and Python. It suits newcomers to data and survey work. Study 100 % online for 180 days at your own pace, with an internship agreement included, for €200.
- 180 days of access
- 100 % online, at your own pace
- Level: beginner · No prior statistics experience required
- Assessment: 10 quizzes (50 questions) and a final project
- Internship agreement included
- Certificate with a verifiable QR code
- Languages: Spanish, English, French
- Price: €200
Who it is for
- Graduates from non-numerical subjects starting in research or data roles
- Staff who must turn survey spreadsheets into headline figures
- People who write short reports or briefings based on data
- Spreadsheet users who are considering a move to R or Python
What do you need to start?
Prior knowledge
- No prior knowledge of statistics needed: the course starts from the mean and the standard deviation
- Comfortable with basic arithmetic such as subtraction, division and percentages
- Able to open a spreadsheet and enter simple formulas
Software and equipment
- A computer with an internet connection
- A spreadsheet program for the formula work (no licence provided)
- Optional: R or Python, both free to install, for the final module
What you'll be able to do
- Summarise a survey dataset with mean, median and standard deviation in a spreadsheet
- Calculate and interpret z-scores, and convert them into proportions with a spreadsheet function
- Build a 95% confidence interval and explain correctly what '95% confidence' means
- State null and alternative hypotheses and apply the 5% significance threshold to a group comparison
- Distinguish statistical significance from practical importance before recommending action
- Interpret a correlation coefficient and make predictions from a regression line without unreliable extrapolation
- Write a headline-first briefing with uncertainty and choose a chart that does not mislead
- Pull a relevant slice of data from a relational database with basic SQL
Skills you will practise
- Mean, median, standard deviation
- Z-scores
- Normal distribution
- Sampling and survey design
- Confidence intervals
- Hypothesis testing and p-values
- Correlation and linear regression
- Data cleaning and validation
- Charts and short reports
- Introductory SQL
Syllabus
- Descriptive statistics with spreadsheets — Reduce hundreds of survey responses to a typical value and a measure of spread, using mean, median and standard deviation.
- Probability and the normal distribution — Use relative frequency, the 68-95-99.7 rule and z-scores to judge precisely how unusual a single data point is.
- Sampling methods and survey design — Decide who to ask and how many people to survey before any data is collected or analysed.
- Confidence intervals — Move from a sample mean to an honest claim about the whole population, and judge whether an interval is narrow enough.
- Hypothesis testing basics — Test whether a gap between two groups is real or just noise, using p-values and the 5% threshold.
- Correlation vs causation, and simple linear regression — Measure how strongly two variables move together, predict from a regression line and avoid unwarranted causal claims.
- Data cleaning and validation — Check and clean a raw data file before calculating anything, so that the figures you report can be trusted.
- Communicating statistical results — Write headline-first briefings for non-specialists and choose charts that inform rather than mislead.
- A light introduction to SQL — Retrieve exactly the rows and columns you need from linked tables in a relational database.
- Moving to R or Python — Recognise when repeated, scheduled analysis outgrows spreadsheets and what switching to free R or Python involves.
Internship agreement
An intern who has taken this course could support a research, survey or analysis team by cleaning raw survey files, producing summary statistics and confidence intervals, and checking whether differences between groups are statistically significant. Other suitable tasks include drafting short briefings and charts for non-technical readers, and extracting data from a database with simple SQL queries.
The internship can run at the same time as the course, within the 180 days of access.
Frequently asked questions
What kind of work does Statistics Basics prepare me for?
Statistics Basics covers the core tasks of entry-level statistical and survey work: designing who to sample, cleaning raw data, summarising it, estimating population figures with confidence intervals, testing differences between groups, and reporting results to decision-makers. These are the duties found in assistant statistician and research analyst roles, which typically combine survey design and questionnaire development with data analysis and acquiring data from primary or secondary sources.
Do I need a maths or statistics degree to start working with statistics?
No. The course is built for people who arrive from other subjects, for example a graduate who took a single compulsory statistics module and nothing more. Each method is presented as a step-by-step recipe applied to realistic survey data, such as subtracting the mean and dividing by the standard deviation to obtain a z-score, together with the mistakes beginners commonly make with it.
Which tools and methods does the course actually cover?
Most of the work is done in a spreadsheet with a few formulas: mean, median, standard deviation and the normal-distribution function. Methods include the empirical rule, z-scores, 95% confidence intervals, null and alternative hypotheses, p-values, correlation coefficients and simple linear regression. A short module introduces SQL for relational databases, and the final module explains when to move to R or Python, both free to install.
What could I do during the internship, and who finds the company?
You find the host company yourself; the school then issues the internship agreement and its annex, which the company signs electronically, usually within one to two working days. Suitable tasks for a Statistics Basics learner include cleaning and validating survey data, calculating summaries and confidence intervals, comparing groups, preparing charts and short briefings, and pulling data with basic SQL for a research or analysis team.
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Content updated: 07/10/2026