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Rule #3: Write the conclusion in plain English so that the reader can understand

it even if that reader has never taken a statistics course.

Let’s practice these rules using the Chevy Impala Excel spreadsheet that you

created earlier in this chapter, but ﬁrst we need to state the hypotheses for that car.

If General Motors wants to claim that the Chevy Impala gets 28 miles per gallon

on a billboard ad, the hypotheses would be:

H
0
:

m
═

28 mpg

H
1
:

m
6¼

28 mpg

You will remember that the reference value of 28 mpg was inside the 95%

conﬁdence interval about the mean for your data, so we would accept H
0
for the

Chevy Impala that the car does get 28 mpg.

Objective
: To state the result when you accept H
0

Result: Since the reference value of 28 mpg is inside the conﬁdence interval,

we accept the null hypothesis, H
0

Let’s try our three rules now:

Objective
: To write the conclusion when you accept H
0

Rule #1:

Since the reference value was inside the conﬁdence interval, we cannot

use the word “signiﬁcantly” in the conclusion. This is a basic rule we

are using in this chapter for every problem.

Rule #2:

The key terms in the conclusion would be:

– Chevy Impala

– reference value of 28 mpg

Rule #3:

The Chevy Impala did get 28 mpg.

The process of writing the conclusion when you accept H
0
is relatively

straightforward since you put into words what you said when you wrote the null hypothesis.

However, the process of stating the conclusion when you reject H
0
and accept H
1

is more difﬁcult, so let’s practice writing that type of conclusion with three practice

case examples:

Objective
: To write the result and conclusion when you reject H
0

CASE #1:

Suppose that an ad in
The Wall Street Journal
claimed that the Honda

Accord Sedan gets 34 miles per gallon. The hypotheses would be:

m
═

H
0
:

34 mpg

m
6¼

H
1
:

34 mpg

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