Variables & Types: Evidence and Measurement

≈ 25 min

Evidence and Measurement

Connect the claim to observable evidence and state what uncertainty or limitation remains.

This extension applies that lens specifically to Variables & Types.

A variable is a name that refers to a value. You create one with =:

age = 15

Now age holds the integer 15. Python has a few core types:

Type	Example	Meaning
`int`	`7`	whole number
`float`	`19.99`	decimal number
`str`	`"Thabo"`	text (in quotes)
`bool`	`True`	true / false

You never declare the type — Python figures it out from the value. type(x) tells you a value's type.

Code practice

Python Foundations — Evidence and Measurement: Assign the integer 7 to a variable called age.

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Code practice

Python Foundations — Evidence and Measurement: Create price holding the float 19.99 and name holding the string "Zanele".

python

Runs in your browser. Charts (matplotlib) are not supported — use print-based output.

Python Foundations — Evidence and Measurement: Which line correctly assigns the text Cape Town to a variable city?

city = Cape Town

city = "Cape Town"

"Cape Town" = city

city == "Cape Town"

Name the original topic being extended by this evidence and measurement lesson.

Which statement is the best evidence-led starting point for Variables & Types: Evidence and Measurement?

A variable is a name that refers to a value. You create one with =: age = 15 Now age holds the integer 15. Python has a few core types: | Type | Example | Meaning | |---|---|---| | int | 7 | whole number | | float | 19.99 | decimal number | | str | "Thabo" | text (in quotes) | | bool | True | true / false | You never declare t

Strings & I/O

Conditionals

A conclusion needs no observations, calculations or stated assumptions.