To conduct a hypothesis test for the given problem, we'll follow these steps:

Step 1: Define the Hypotheses

We are testing if the percentage of businesses that receive orders via the Internet has increased from the previous 43.8%. Therefore, the hypotheses are:

• Null Hypothesis (H₀): The percentage has not increased, meaning it is still 43.8%.
  $H_0: \pi = 0.438$

• Alternative Hypothesis (H₁): The percentage has increased.
  $H_1: \pi > 0.438$ This is a right-tailed test, as we are interested in whether the proportion has increased.

Step 2: State the significance level

The significance level given is $\alpha = 0.10$.

Next steps involve calculating the test statistic using the sample proportion ($p$) and the hypothesized proportion ($\pi_0 = 0.438$).

Would you like me to continue with the calculation, or do you have any specific questions so far?

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Here are 5 related questions:

1. How do you calculate the sample proportion $p$ from the data provided?
2. What is the formula for the test statistic $z$ in a proportion hypothesis test?
3. How do you find the critical value for a right-tailed test at a 0.10 significance level?
4. What are Type I and Type II errors in hypothesis testing?
5. How would you interpret a p-value in the context of this hypothesis test?

Tip: Always ensure to clearly state your null and alternative hypotheses before starting a hypothesis test.