We want to know what proportion (percentage) of California will be voting for Mr. Lewis in the next election. We call 50 random numbers in California and ask, "Are you planning on voting for Lewis in the next election?" Match the following descriptions with their appropriate key term. c ~wis The proportion of the 50 random numbers who said they are voting for Mr. b The proportion of all voters in California who are voting for Mr. Lewis Key Terms The responses of all voters in California a. parameter b. population c. statistic d. sample

Let's match the descriptions with their appropriate key terms: 1. **The proportion of the 50 random numbers who said they are voting for Mr. Lewis**: This refers to a specific measurement taken from a subset of the population, which is known as a **statistic**. Therefore, this corresponds to **c. statistic**. 2. **The proportion of all voters in California who are voting for Mr. Lewis**: This refers to the true value we want to estimate for the entire population, which is known as a **parameter**. Therefore, this corresponds to **a. parameter**. 3. **The responses of all voters in California**: This refers to the entire group we are interested in studying, which is known as the **population**. Therefore, this corresponds to **b. population**. 4. **The 50 random numbers we called**: This refers to the subset of the population from which we collected data, which is known as a **sample**. Therefore, this corresponds to **d. sample**. In summary: - c. statistic: The proportion of the 50 random numbers who said they are voting for Mr. Lewis. - a. parameter: The proportion of all voters in California who are voting for Mr. Lewis. - b. population: The responses of all voters in California. - d. sample: The 50 random numbers we called.