Question

Could anyone elaborate on how they determined whether this is a one-tailed, two-tailed, or upper-tailed test? Could you also explain how to determine which section of the graph on a bell curve that gets shaded in?

A company’s call center advertises that they resolve 80% of its customer calls by using automated voice options. A customer who has called in many times and rarely had issues resolved through the automated options believes that 80% is an overstatement. A significance test was done, and a test statistic was calculated. Assume the conditions for inference were met.

H0: p = 0.80
Ha: p < 0.80
p = The true proportion of all customer calls that are resolved by using automated options

Calculate the P-value, given that the resulting test statistic was z = –1.389.

Answer 1

1. State the claim H0 and the alternative, Ha

2. Choose a significance level or use the given one.

3. Draw the sampling distribution based on the assumption that H0 is true, and shade the area

of interest.

4. Check conditions. Calculate the test statistic.

5. Find the p-value.

6. If the p-value is less than the significance level, α, reject the null hypothesis. (There is enough

evidence to reject the claim.)

If the p-value is greater than the significance level, α, do not reject the null hypothesis.

(There is not enough evidence to reject the claim.)

(You can use the p-value to make a statement about the strength of the evidence against H0

without using α, e.g., p>.10 implies “little or no evidence against H0”, .05< p ≤ 10 implies

“some evidence against H0”, .01 < p ≤ .05 implies “good evidence against H0”, .001 < p ≤ .01

implies “strong evidence against H0”, p ≤ .001 implies “very strong evidence against H0”.)

7. Write a statement to interpret the decision in the context of the original claim.

Test statistics: (Step 3)

Hypothesis testing for a mean (σ is known, and the variable is normally distributed in the

population or n > 30 ) z

x

n

=

− µ

σ

0

(TI-83: STAT TESTS 1:Z-Test)

Hypothesis testing for a mean (σ is unknown, and the variable is normally distributed in the

population or n > 30 ) t

x

s

n

=

− µ0

(TI-83: STAT TESTS 2:T-Test)

Hypothesis testing for a proportion (when np and n p 0 0 ≥ 10 1 10 ( ) − ≥

(TI-83: STAT TESTS 5:1-PropZTest)

Explanation:

i think that it?

Answer 2

0.0823

Explanation: