explain Type I and Type II Errors and One Tailed and Two Tailed Test ( not more than two line sentences for each )

Hypothesis TestingTest of significance (a level)Degree of freedom (df)One Tailed and Two Tailed TestType I and Type II Errors

35.In one tail test for the population mean if the null hypothesis is not rejected when the alternative hypothesis is true then which of the following happens?  A. Type 2 error  B. Type 1 error  C. No error  D. Two tailed test should've been used

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.

Potential errors relative to Hypothesis testing are referred to as Type I error and Type II error. Group of answer choicesTrueFalse