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To express the null and alternative hypotheses symbolically, based on the claim that 68% of workers got their job through newspaper ads, we’ll set up the hypotheses as follows:

1. **Null Hypothesis (H₀):** This hypothesis assumes there is no difference from the stated percentage, so we set \( p = 68 \).

2. **Alternative Hypothesis (H₁):** This hypothesis tests if the actual percentage is different from 68%, meaning \( p \neq 68 \).

Therefore, we have:

- \( H_0 : p = 68 \)
- \( H_1 : p \neq 68 \)

Let me know if you'd like further explanation or have any questions.

### Related Questions
1. What would the hypotheses look like if we were testing for a percentage greater than 68%?
2. How can we interpret the p-value in a hypothesis test for this claim?
3. What sample size would be sufficient to test this hypothesis reliably?
4. How does the significance level affect the conclusion of this test?
5. What steps are taken to ensure that the sample is representative of the population?

**Tip:** In hypothesis testing, the null hypothesis always represents a statement of equality (e.g., \( p = \) some value).

68% of workers got their job through newspaper ads. Express the null and alternative hypotheses in symbolic form for this claim (enter as a percentage).

Understand how to express the null and alternative hypotheses for the claim that 68% of workers got their job through newspaper ads. Learn the basics of hypothesis testing, including how to set up H0 and H1 in symbolic form.

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