In statistics, a Type I error is called a false positive. They occur when we mistakenly reject a hypothesis that is actually true. A Type II error is a false negative. They occur when we mistakenly accept a hypothesis that is actually false.Imagine you run an experiment to determine whether the kilometers per kilowatt(km/kWh) differs significantly between two models of electric vehicle: Tesla Model Y and Chevrolet Bolt. You hypothesize that there is no difference in their efficiency. Based on your findings, you determine your hypothesis is right and there is no difference between the km/kWh. Later, you learn that there is a significant difference in the km/kWh of these two models. What type of error did you commit?

A type I error means that:1 point The null hypothesis is true, and you do not reject the null hypothesis. The null hypothesis is true, and you reject the null hypothesis. The null hypothesis is false, and you reject the null hypothesis. The null hypothesis is false and cannot reject the null hypothesis.

Which of the following is an accurate definition of a Type II error?​​Group of answer choices​Rejecting a false null hypothesis​Rejecting a true null hypothesis​Failing to reject a true null hypothesis​Failing to reject a false null hypothesis

Use the situation below to answer the next two questions Q34 and 35, describe what it means in that context to make a Type I and Type II error.Testing a new drug with potentially dangerous side effects to see if it is significantly better than the drug currently in use. If it is found to be more effective, it will be prescribed to millions of people. In this scenario, making a Type I error means: Group of answer choicesWe do not find any difference between the drugs.We find evidence that the new drug is more effective but it is really not any better.The new drug is more effective.We find evidence that the new drug is more effective.We do not find enough evidence that the new drug is more effective but it really is more effective.

Type II error occurs when the test:Group of answer choicescorrectly fails to reject an actually true null hypothesis.incorrectly fails to reject an actually false null hypothesis.correctly rejects an actually false null hypothesis.incorrectly rejects an actually true null hypothesis.

A Type I error occurs when we:Group of answer choicesreject a true null hypothesis.do not reject a false null hypothesis.Do not reject a true null hypothesis.reject a false null hypothesis.