Chapter 12 Tests of a Single Mean When σ is Unknown.

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Chapter 12 Tests of a Single Mean When σ is Unknown

Transcript of Chapter 12 Tests of a Single Mean When σ is Unknown.

Page 1: Chapter 12 Tests of a Single Mean When σ is Unknown.

Chapter 12

Tests of a Single Mean When σ is Unknown

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A Research QuestionChildren’s growth is stunted by a

number of chemicals (lead, arsenic, mercury)

The tap water in the local community contains a bit of each of these chemicals

Are children in this town smaller than other children their age?

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A Research Project16 (n = 16) 6-yr old children are

randomly selected from around townEach child’s height is measured In the US the average height of 6-yr

olds is 42” (μ = 42)The variance of 6-yr-old’s height,

however is not known

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The Data

The 16 kid’s heights were:44, 38, 42, 37, 35, 41, 46, 39,

40, 42, 34, 39, 41, 42, 45, 35

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Hypothesis Test

1.State and Check AssumptionsHeights normally distributed ? -

probably (n = 16 large enough)

Interval level data

Random Sample

Population variance unknown

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Hypothesis Test

2. Null and Alternative Hypotheses

HO : μ = 42 (6-yr old’s height is 42”)

HA : μ < 42 (6 yr-old’s height is less than 42”)

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Hypothesis Test

3.Choose Test StatisticParameter of interest - μ

Number of Groups - 1

Independent Sample

Normally distributed - probably

Variance - unknown

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What do we do?z-test requires that we know the

population standard deviation (σ) Can we use s as a substitute for σ?Not with a z statistic, but…We can use s with a t statistic

(Student’s t) and a t sampling distribution

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Single Sample t statistic

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Back to the Hypothesis Test

3.Choose the test statisticParameter of interest - μ

Number of Groups - 1

Independent Samples

Normally distributed - probably

Variance - unknown

One Sample t-test

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Hypothesis Test

4.Set significance levelα = .05critical value is found in table C

What’s a df?

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Degrees of Freedom (df)Degrees of Freedom (df) - the number

of components in a statistic’s calculation that are free to vary

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df Explained If you have a M = 10 obtained from 5 scores,

what are the scores? Let’s say the first four are 15, 10, 11, and 5

– in this case the last score has to be 9, in order to have a mean of 10

As a second example, let’s say the first four are 8, 14, 3, and 11– the last score has to be 14 in order to have a

mean of 10

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df Explained Therefore, the first 4 scores can vary, the

fifth score is not free to vary - it must take on some value (in order to maintain the mean of 10)

In our example, there are 4 degrees of freedom

The first four scores can take on any value (they are free to vary), but that last one is fixed in order to maintain the mean

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One Sample t test In a one sample t test the degrees of

freedom are always equal to n - 1– df = n -1

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Back to the Hypothesis test

4.Set significance level and make decision ruleα = .05df = n -1 = 16 - 1 = 15critical value at .05 of t(15) = 1.753(read: “critical value at .05 of a t test with 15 degrees of freedom is 1.753”)

But, since we have a directional hypothesis (< 42), then the critical value is -1.753

Thus, if our computed t ≤ -1.753, we reject HO

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Or… If we compute the p-value associated

with our t, with 15 df, we can state the decision rule as:– If p ≤ α, Reject the HO

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Hypothesis Test

5.Compute test statistic

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Hypothesis Test

6. Draw conclusionsSince our obtained t (-2.236) is less than the critical t (-1.753) we,

Reject HO, and concludeThat our town’s 6-yr olds are smaller, on average, than 6-yr olds in the US

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Careful…a warning

We have rejected the HO and concluded that our town’s 6-yr-olds are smaller, on average, than 6-yr-olds in the US

But, we are not allowed, in this case, to conclude that it is because of chemicals in the water, or any other cause

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Alternative Explanations There are likely many causes for children’s

small stature, not limited to:– Genetics– Diet– Environmental contaminants– Chemicals in ground water– Etc.

The hypothesis test allows us to conclude that these children are smaller, on average, but does not allow us to say why

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Before we move on…Although we already rejected the null

hypothesis,We can determine the actual

probability of our results if the null hypothesis were true (p-value)

We know that it is less than .05, but how much less?

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Ugghh!!!

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Excel recognizes onlypositive values fora t distribution, but because the t is symmetrical, use the absoute value function (ABS) to find the p-value

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