Data, 11–13 years — 20 topics · MyLeoNes™ Kuks
20 data topics written for 11–13 years — not a older text simplified. In teaching order, each a deck of five cards: the idea, why it exists, a worked example, the common trap and where you meet it.
Data · 11–13 years
Samples that answer a question
A survey is useful only when its questions and its group of people fit the thing you want to know.
Frequency tables and charts
Counting repeated answers turns a messy list into a pattern that can be read and compared.
Averages describe a data set
Mean, median, mode and range answer different questions about a collection of numbers.
When a graph misleads
A graph can use true numbers and still give a false impression if its scale, labels or design hide the comparison.
The median finds the middle
The median is the middle value after the data has been put in order. It can describe a typical result without being pulled strongly by one unusually large or small value.
How spread out data is
Two data sets can have the same average but very different amounts of variation. The range, found by subtracting the smallest value from the largest, gives a quick first measure of spread.
Outliers need a closer look
An outlier is a value far from the rest. It may be a mistake, a rare event, or a real clue, so good data work investigates it instead of deleting it automatically.
Correlation is not causation
When two measurements change together, they are correlated. That pattern can be useful, but it does not by itself prove that one measurement causes the other.
Percentages make groups comparable
A percentage tells how large a part is when the whole is treated as 100. This makes fairer comparisons between groups of different sizes.
Two-way tables show two features together
A two-way table sorts data by two questions at once. Reading rows, columns and totals can reveal patterns that one list would hide.
Probability can be estimated from data
Repeated trials give an experimental estimate of how often something happens. More trials usually make the estimate steadier, but chance can still cause short runs to vary.
Data over time shows change and variation
A time series records the same kind of measurement at different moments. Looking in order helps distinguish a general trend from short-term ups and downs.
Different kinds of data
Data is not always a row of numbers. Knowing whether data describes a group, a number or a measurement helps you choose a sensible way to record and compare it.
Measurements have uncertainty
A measurement is an estimate made with a tool, not a perfect window onto reality. Its scale, the object and the person measuring all limit how exact the result can be.
A sample can be unfair
A sample may be easy to collect but still fail to represent the larger group. Looking at who was included, who was missed and how people were chosen helps reveal sampling bias.
A fair comparison changes one thing
To learn whether one thing makes a difference, keep the other important conditions alike.
Data can reveal a person
Data about a person can become identifying when separate details are joined. Learning to minimise, protect and anonymise data is part of using information responsibly.
Clean data before trusting it
Blank answers, typing errors and mixed units can quietly change a conclusion.
Samples vary by chance
Two fair samples from the same group can give different results, even when nobody made a mistake.
Predictions have limits
Past data can guide a prediction, but it cannot promise what will happen next.
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