To conduct the hypothesis test, we begin by stating the null and alternative hypotheses, identifying the claim, and determining the type of test.

Hypotheses:

• Null Hypothesis (H₀): μ = 2.8 (The mean number of calls made per day has not increased.)
• Alternative Hypothesis (H₁): μ > 2.8 (The mean number of calls made per day is greater than 2.8.)

Claim:

The researcher's claim is that the mean number of calls made per day today is higher than 2.8. Thus, the claim corresponds to the alternative hypothesis (H₁).

Type of Test:

Since the alternative hypothesis uses a "greater than" sign (μ > 2.8), this is a right-tailed test.

Would you like to proceed with calculating the test statistic and determining the critical value? Let me know if you need any clarifications or further details.

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Five Related Questions:

1. What formula is used to compute the test statistic for this hypothesis test?
2. How do we determine the critical value for a one-tailed test at α = 0.01?
3. Why is it necessary to assume the variable is normally distributed for this test?
4. What does rejecting the null hypothesis signify in this context?
5. How would the conclusion change if the sample mean were exactly 2.8?

Tip: When performing hypothesis testing, always clearly label each step and check the assumptions (e.g., normality, sample size) to ensure accuracy.