Preparing with free material before a paid programme is one of the smartest things you can do. It de-risks the decision, shortens the painful first weeks, and tells you whether you actually enjoy the subject. Here is a sensible plan and an honest account of where free resources run out.
What to cover before you start, in order
1. Arithmetic and algebra confidence (a week). Fractions, percentages, rearranging simple equations, reading exponents. This is the real prerequisite, and shaky basics here cause most of the distress later.
2. Descriptive statistics (a week). Mean, median, mode, range, variance, standard deviation. Learn to compute each by hand once, then in a spreadsheet.
3. Spreadsheet skills (a week). AVERAGE, MEDIAN, STDEV, COUNTIF, SUMIF, pivot tables, charts. Practical spreadsheet fluency saves more time on a statistics course than any amount of theory.
4. Basic probability (a week). Independent versus dependent events, simple probability rules, what a distribution is.
5. Reading charts critically (ongoing). Look at charts in the news and ask what is missing - the axis start, the sample, the comparison period.
Where to find good free material
- University open courseware - many institutions publish full introductory statistics modules with problem sets
- Khan Academy's statistics and probability track - free, well-sequenced, ideal for the first three items above
- Major MOOC platforms - most introductory statistics courses can be audited free; you pay only for the certificate
- Official statistics agencies - the UK's Office for National Statistics publishes real datasets and explainers, which are excellent practice material
- Spreadsheet vendors' own tutorials - free and directly applicable
Where free resources genuinely stop working
Three gaps that free material rarely fills:
- Feedback on your reasoning. Free courses mark your arithmetic. They cannot tell you that your interpretation of a p-value is subtly wrong, which is the mistake that matters.
- Structure and accountability. Completion rates for free online courses are notoriously low. A cohort and a deadline are worth paying for.
- Application to your context. Generic examples about coin flips do not transfer to your business. Applied teaching does.
A realistic six-week self-study plan
Weeks 1-2: numeracy refresher plus descriptive statistics. Weeks 3-4: spreadsheet work on a real dataset of your own. Week 5: probability basics. Week 6: read three published analyses and write down what you would question about each. If you enjoyed that, you will do well on a formal course. If you hated it, you have saved yourself a large fee - and that is a successful outcome too.
After the prep
When you are ready for structured, applied teaching with feedback, the Statistics for Business course at London School of Business UK picks up exactly where self-study plateaus. Enquire about the next intake.