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# Unit: Modeling data distributions

AP Stats:
UNC (BI)
,
UNC‑1 (EU)
,
VAR (BI)
,
VAR‑2 (EU)

#### 0

Possible mastery points

## Percentiles (cumulative relative frequency)

AP Stats:
UNC (BI)
,
UNC‑1 (EU)
,
UNC‑1.G (LO)
,
UNC‑1.G.4 (EK)
,
UNC‑1.I (LO)
,
UNC‑1.I.5 (EK)
Practice
Calculating percentilesGet 3 of 4 questions to level up!

## Z-scores

AP Stats:
VAR (BI)
,
VAR‑2 (EU)
,
VAR‑2.B (LO)
,
VAR‑2.B.1 (EK)
,
VAR‑2.B.2 (EK)
,
VAR‑2.C (LO)
,
VAR‑2.C.1 (EK)
Practice
Calculating z-scoresGet 3 of 4 questions to level up!
Comparing with z-scoresGet 3 of 4 questions to level up!

## Effects of linear transformations

AP Stats:
UNC (BI)
,
UNC‑1 (EU)
,
UNC‑1.J (LO)
,
UNC‑1.J.4 (EK)
Practice
Transforming dataGet 3 of 4 questions to level up!

#### Quiz 1

Level up on the above skills and collect up to 400 Mastery points

## Density curves

AP Stats:
UNC (BI)
,
UNC‑1.F (LO)
,
UNC‑1.F.2 (EK)
,
UNC‑1.M (LO)
,
UNC‑1.M.2 (EK)
,
VAR‑6.A.1 (EK)
Practice
Properties of density curvesGet 3 of 4 questions to level up!
Area under density curvesGet 3 of 4 questions to level up!

## Normal distributions and the empirical rule

AP Stats:
VAR (BI)
,
VAR‑2 (EU)
,
VAR‑2.A (LO)
,
VAR‑2.A.2 (EK)
,
VAR‑2.A.3 (EK)
,
VAR‑2.A.4 (EK)
Practice
Empirical ruleGet 3 of 4 questions to level up!

## Normal distribution calculations

AP Stats:
VAR (BI)
,
VAR‑2 (EU)
,
VAR‑2.B (LO)
,
VAR‑2.B.3 (EK)
,
VAR‑2.B.4 (EK)
Practice
Normal distribution: Area above or below a pointGet 3 of 4 questions to level up!
Normal distribution: Area between two pointsGet 3 of 4 questions to level up!
Normal calculations in reverseGet 3 of 4 questions to level up!

#### Quiz 2

Level up on the above skills and collect up to 600 Mastery points
Up next for you:

#### Unit test

Level up on all the skills in this unit and collect up to 1000 Mastery points!

### About this unit

This unit takes our understanding of distributions to the next level. We'll measure the position of data within a distribution using percentiles and z-scores, we'll learn what happens when we transform data, we'll study how to model distributions with density curves, and we'll look at one of the most important families of distributions called Normal distributions.
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