Descriptive Statistics, First Steps
Summarise any set of numbers honestly with averages, spread and shape
A taste of a lesson
Five people earn 30, 32, 35, 38 and 250 thousand. The mean is 77. Is it fair to say the average person earns 77k?
Technically 77 is the mean, but it describes nobody in the group. Four of the five earn between 30 and 38, and one high earner pulls the mean up. The median, the middle value when sorted, is 35, which is much closer to a typical person. For skewed data like salaries, report the median and mention the spread. A fair sentence: 'Of five people, the median salary is 35k; one person earns far more, at 250k.' Now try: what is the median if the 250 were 40 instead?
Written by the teacher as an example. In your lesson the tutor answers your own questions, and like any AI it can be wrong.
What you will be able to do
- Choose between mean, median and mode for a given dataset
- Describe spread with range, interquartile range and standard deviation
- Recognise skew and outliers and explain their effect
- Read box plots, histograms and percentiles
- Write a clear one sentence summary of any small dataset
Lesson plan
- 1 Three kinds of average Calculate and choose between mean, median and mode. Start
- 2 How spread out are the numbers? Measure spread with range and interquartile range. Start
- 3 Standard deviation without fear Understand standard deviation as a typical distance from the mean. Start
- 4 Shape, skew and outliers Describe the shape of data and decide what to do with outliers. Start
- 5 Pictures of data Read histograms, box plots and percentiles. Start
- 6 Writing an honest summary Summarise a dataset in one clear, accurate sentence. Start
Try asking
About this tutor
A free beginner tutor for anyone who works with numbers in reports, spreadsheets or the news and wants to describe them properly. You will learn when to use the mean, median or mode, how to describe spread with range, interquartile range and standard deviation, and how skew and outliers change the story. Lessons use small, familiar datasets like salaries, commute times and test scores, and every lesson ends with you writing a one sentence summary of a dataset that a colleague could understand. No formulas are needed beyond simple arithmetic.
Reviews
4.7
3 ratingsSample
- Paulo R.Sample
Free and genuinely helpful for my monthly reports. I now use median and IQR for delivery times.
- Siobhan K.Sample
Lovely pace. I would have liked one more lesson on percentiles, but I got what I needed.
- Joyce M.Sample
I was always scared of statistics. Calculating before naming the idea took the fear away. The salary example will stay with me.
About the teacher
Statistics in plain language, from averages to Bayesian reasoning
9 tutors 350 lessons taught Sample
I teach statistics to people who were put off by it the first time. My approach is to start from a question someone actually has, simulate or count our way to an answer, and only then name the formula. I have worked as an analyst on survey and health research projects, so I have a soft spot for messy samples,...
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