CareerBuilder.com conducted a survey to learn about the...

CareerBuilder.com conducted a survey to learn about the proportion of employers who perform background checks when evaluating a candidate for employment ("Majority of Employers Background Check Employees...Here's Why," November $17,$ $2016,$ retrieved November 19,2016 ). Suppose you are interested in determining if the resulting data provide strong evidence in support of the claim that more than two-thirds of employers perform background checks. To answer this question, what null and alternative hypotheses should you test? (Hint: See Example $10.4 .)$

Labs

Want to see this concept in action?

NEW

Explore this concept interactively to see how it behaves as you change inputs.

View Labs

Key Concepts

Hypothesis Testing

Hypothesis testing is a statistical method used to make an inference about a population parameter based on sample data. It involves proposing an initial hypothesis and then determining whether the evidence supports or contradicts this assumption.

Null Hypothesis

The null hypothesis (H0) is a default or baseline assumption that there is no difference or effect—in this problem, it states that the true proportion of employers who perform background checks is equal to two-thirds (p = 2/3). It serves as the statement to be tested against the alternative.

One-Sample Proportion Test

A one-sample proportion test is a statistical procedure used when the interest is in testing a hypothesis about the proportion of successes in a single population. Here, it is used to assess whether the observed sample evidence provides enough support to reject the null hypothesis in favor of the alternative.

Alternative Hypothesis

The alternative hypothesis (Ha) is a statement that contradicts the null hypothesis, representing the effect or difference the researcher expects. In this case, it claims that the proportion of employers who perform background checks is greater than two-thirds (p > 2/3), implying a one-tailed test.

Transcript

Please give Ace some feedback