Identify the type I error and type II error that corresponds to the given
hypothesis. The proportion of settled medical malpractice suits is 0.28
I have been working on this one for 3 hours and am doing something wrong, Please help!!
To identify the type I error and type II error in hypothesis testing, we need to understand the context and formulate the null and alternative hypotheses.
In this case, the null hypothesis (H₀) would be that the proportion of settled medical malpractice suits is equal to 0.28. The alternative hypothesis (H₁) would be that the proportion is different from 0.28.
Now, let's define the type I and type II errors:
1. Type I Error:
A type I error occurs when we reject the null hypothesis (H₀) when it is actually true. In other words, we mistakenly conclude that the proportion of settled medical malpractice suits is different from 0.28, even though it is true. The probability of making a type I error is denoted by α (alpha) and is usually set as the significant level (e.g., 0.05).
2. Type II Error:
A type II error happens when we fail to reject the null hypothesis (H₀) when it is actually false. In this case, it means that we incorrectly conclude that the proportion of settled medical malpractice suits is 0.28, even though it is not. The probability of making a type II error is denoted by β (beta).
To accurately determine the type I and type II errors, we would need additional information such as the sample size, significance level (α), and the desired power of the test (1 - β).