Steply

Samples of 36 from mean 30, sd 9: P(sample mean < 32)

Step by step, with the reason for every step · Sample means and the central limit theorem · University Statistics

Step by step

The question

Question: samples of 36 are taken from numbers with mean 30 and SD 9: what is the probability that the sample mean is less than 32?

P(x̄ < 32): μ = 30, σ = 9, n = 36

x̄, x bar, is the mean of one sample.

x̄ = the mean of one sample

1 The sample means

The central limit theorem: the means of many samples make a bell.

Its middle is the mean, 30.

Its SD is smaller: σ divided by the square root of n.

many samples of 36: their means make a bell
middle: μ = 30
SD of the means: σ ÷ √n

The square root of 36 is 6.

9 divided by 6 is 1.5.

σx̄ = σ√n = 9√36 = 96 = 1.5

Careful!

The sample means have SD 1.5, not 9.

So we divide by 1.5.

Careful: not z = 32 − 309 ✗

2 Find z

z counts how many SDs the sample mean is from the mean: x̄ minus the mean, over the SD.

z = x̄ − μσx̄

32 minus 30 is 2.

Divided by 1.5, that is about 1.33.

z = 32 − 301.5 = 21.5 ≈ 1.33

3 Draw and shade

The bell: the mean, 30, in the middle.

32 is right of it.

We want the sample mean less than 32.

We shade that part.

4 Read the table

The z-table gives the area to the left of z.

Row 1.3, column .03.

For z = 1.33: the row 1.3 and the column .03 meet at 0.9082.

5 The area we want

Less than: the area to the left.

That is just the table number, 0.9082.

P(x̄ < 32) = 0.9082

6 Check

Let's check another way.

The bell is the same on both sides.

So the area left of 1.33 is the area right of −1.33.

left of 1.33 = right of −1.33

1 minus the table at −1.33: 1 minus 0.0918 is 0.9082.

The same!

So it is right!

1 − table at −1.33: 1 − 0.0918 = 0.9082

Let's look back.

First: the sample means.

Then: find z.

Then: draw and shade.

Then: read the table.

Then: the area we want.

Last: check.

Answer
P(x̄ < 32) = 0.9082

Your turn

Try this one yourself, then check:

Find P(x̄ < 51): μ = 45, σ = 27, n = 36
Show the answer
P(x̄ < 51) = 0.9082

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