Statistical Literacy and Critical Thinking
In Exercises 1–4, use the results from a Hankook Tire Gauge Index survey of a simple random sample of 1020 adults. Among the 1020 respondents, 86% rated themselves as above average drivers. We want to test the claim that more than 3/4 of adults rate themselves as above average drivers.


Number and Proportions


c. For the hypothesis test, identify the value used for the population proportion and use the symbol that represents it.

Verified step by step guidance

1. Identify the claim: The claim is that more than 3/4 (or 0.75) of adults rate themselves as above-average drivers. This is a one-tailed test since the claim specifies 'more than.'
2. Define the null hypothesis (H₀) and the alternative hypothesis (H₁): H₀: p ≤ 0.75 (the population proportion is less than or equal to 0.75), and H₁: p > 0.75 (the population proportion is greater than 0.75).
3. Determine the value used for the population proportion: The population proportion is represented by the symbol 'p.' For the null hypothesis, the value of p is 0.75, as this is the value being tested against.
4. Understand the sample proportion: The sample proportion (denoted as p̂) is calculated from the survey data. In this case, 86% of the 1020 respondents rated themselves as above-average drivers, so p̂ = 0.86.
5. Clarify the role of the population proportion: The population proportion (p = 0.75) is the hypothesized value under the null hypothesis, and it will be used in the hypothesis test to compare against the sample proportion (p̂ = 0.86).

Key Concepts

Population Proportion

The population proportion, denoted as 'p', represents the fraction of a population that exhibits a certain characteristic. In this context, it refers to the proportion of adults who rate themselves as above average drivers. Understanding this concept is crucial for hypothesis testing, as it serves as the benchmark against which sample data is compared.

Hypothesis Testing

Hypothesis testing is a statistical method used to make inferences about a population based on sample data. It involves formulating a null hypothesis (H0) and an alternative hypothesis (H1). In this case, the null hypothesis would state that the population proportion of adults who consider themselves above average drivers is 0.75 or less, while the alternative hypothesis would claim it is greater than 0.75.

Simple Random Sample

A simple random sample is a subset of individuals chosen from a larger population, where each individual has an equal chance of being selected. This method helps ensure that the sample is representative of the population, which is essential for the validity of statistical inferences. In the given survey, the sample of 1020 adults was randomly selected to assess their self-perception as drivers.