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+## Basic population definition
+
+You specify the patients you want to include in your dataset using the
+`define_population()` method. For example, to include all patients born
+in 1950 you would write something like this:
+```ehrql
+from ehrql import create_dataset
+from ehrql.tables.core import patients
+
+dataset = create_dataset()
+dataset.define_population(patients.date_of_birth.year == 1950)
+```
+
+
+## Combining multiple inclusion criteria
+
+You can combine multiple inclusion criteria using the [logical operators](../reference/language.md#BoolPatientSeries.and):
+
+ * `&` (and)
+ * `|` (or)
+ * `~` (not)
+
+For example, to include just men born in 1950 you could use the `&`
+operator. This says that patients must match the date of birth criterion
+**and** the sex criterion.
+```python
+dataset.define_population(
+    (patients.date_of_birth.year == 1950) & (patients.sex == "male")
+)
+```
+
+And, similarly you could include just women born in 1960 using:
+```python
+dataset.define_population(
+    (patients.date_of_birth.year == 1960) & (patients.sex == "female")
+)
+```
+
+To combine these populations together and include both men born in 1950
+and women born in 1960 you could use the `|` operator. This says that
+patients must match **either** the first condition **or** the second:
+```python
+dataset.define_population(
+    ((patients.date_of_birth.year == 1950) & (patients.sex == "male"))
+    | ((patients.date_of_birth.year == 1960) & (patients.sex == "female"))
+)
+```
+
+!!! note "What's with all the parentheses?"
+
+    ehrQL requires more parentheses around logical operators than you
+    may be used to from other languages. This is a side-effect of the
+    way the Python language (in which ehrQL is implemented) happens to
+    work, but it is good practice in any case to be explicit about how
+    you expect logical operations to be grouped together. If you miss
+    out any required parentheses ehrQL should give you an error message
+    explaining how to fix your code.
+
+
+## Excluding patients from your dataset
+
+To exclude patients matching a certain condition from your dataset you
+can use the "and not" pattern. That is, you can write your population
+definition in the form:
+
+    inclusion_criteria & ~exclusion_criteria
+
+For example, to include patients born in 1950 and exclude patients
+who died before 2020 you could write:
+```python
+dataset.define_population(
+    (patients.date_of_birth.year == 1950) & ~(patients.date_of_death.year < 2020)
+)
+```