To test the hypothesis, we set up the null and alternative hypotheses as follows:

Null Hypothesis ($H_0$):

The mean time spent by all executives reading and sending e-mails is less than or equal to 60 minutes.
$H_0: \mu \leq 60$

Alternative Hypothesis ($H_a$):

The mean time spent by all executives reading and sending e-mails is greater than 60 minutes.
$H_a: \mu > 60$

This is a one-tailed test since the alternative hypothesis is specifically testing if the mean is greater than 60 minutes.

Would you like to proceed with the hypothesis test calculation or explore further details about any steps?

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Expanding Questions:

1. How do you determine whether to use a one-tailed or two-tailed test in hypothesis testing?
2. What is the significance of the standard deviation in this hypothesis test?
3. Why is the sample mean used to infer about the population mean?
4. How do you calculate the test statistic in this case?
5. What role does the significance level ($\alpha = 0.05$) play in hypothesis testing?

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Tip: In hypothesis testing, clearly identifying the null and alternative hypotheses is the foundation for setting up the correct test.