"Here are the hypotheses they'll use." So, the null hypothesis is that 40% or fewer of the students are interested in a meal plan, while theĪlternative hypothesis is that more than 40% are interested. "Let P represent the proportion "of students interested in a meal plan. Interested in a meal plan "is higher than 40%, in which case they "will consider building a new cafeteria. Sample of their students "to see if there is strong evidence "that the proportion "A large university is curious "if they should build another cafeteria. To reject something that is false, that is Type II. Something that's false?" And the rejecting something that is true, that's Type I, and failing So, one way to think about it, first you say, "Okay,Īm I making an error? "Am I rejecting something that's true, "or am I failing to reject Hypothesis is not true, so this one right over here, this one would actuallyīe, this is an error. Town's unemployment rate is 9% "when it actually is not." So, this is a situation where she fails to reject the null hypothesis, even though the null When the null hypothesis is actually true, not an error. This would be failing to reject the null hypothesis Unemployment rate is 9% "when it actually is." Well, once again, this If the null hypothesis isn't true, it's not a problem to reject it, so this one wouldn't be an error. Unemployment rate is not 9% "when it actually is not." Well, this wouldn't be an error. So, I'm liking this choice, but let's read the other Though the unemployment rate actually is 9%. Though the null hypothesis is actually true, even The unemployment rate is not 9%, she would have to reject the null hypothesis, even Town's unemployment rate "is not 9% when it actually is." Yeah, in this situation, in order to conclude that Is 9% in this town, so let's see which of theseĬhoices match up to that. Rate is 9% in this town, even though it actually And so, in this case, that would be rejecting the hypothesis that the unemployment Somehow contradicts reality, even though you didn't intend to. And in general, if you'reĬommitting either a Type I or a Type II error, you'reĭoing the wrong thing, you're doing something that Reject null hypothesis, even though, even though our null hypothesis is true. This is a situation where we reject the null hypothesis,Įven though it is true. Now, let's work through this together, so let's just remind "Under which of the following conditions "would the mayor commit a Type I error?" So, pause this video,Īnd see if you can figure it out on your own. "Here are the hypotheses she'll use." So, her null hypothesis is that, hey, the unemployment rate in her town is the same as for the country, and her alternative hypothesis is that it is not the same. If the unemployment rate "is significantly different Holds true for her town, "so she plans on taking a sample "of her residents to see "The mayor of a local town wonders "if this national result
We are told, "A large nationwide poll recently showed "an unemployment rate ofĩ% in the United States.
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