1 / 8

Hypothesis Testing

Hypothesis Testing. Topics: Essentials Hypotheses Testing Examples. E ssentials: Hypothesis Testing (Testing Claims.). What is a hypothesis. Null vs. Alternative hypotheses Statistical Significance: Critical Values & p-values One-sample Tests for mean & proportions.

marygarner
Télécharger la présentation

Hypothesis Testing

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Hypothesis Testing Topics: Essentials Hypotheses Testing Examples

  2. Essentials:Hypothesis Testing(Testing Claims.) • What is a hypothesis. • Null vs. Alternative hypotheses • Statistical Significance: • Critical Values & p-values • One-sample Tests for mean & proportions

  3. What is a Hypothesis • In statistics, a hypothesis is a claim or statement about a characteristic of a population. • A Null Hypothesis, denoted Ho, is a statistical hypothesis that contains a statement of equality such as . • The Alternative Hypothesis, denoted Ha, is the compliment of the null hypothesis. It is a statement that must be true if Ho is false and it contains a statement of inequality, such as .

  4. Null Hypothesis: A statement that nothing interesting is happening – that there is no difference between observed data and what was expected. The p-value: level at which you are testing a hypothesis; the probability that the data would be at least as extreme as those observed if the null hypothesis were true. Type I Error (a error): the probability of rejecting a null hypothesis when in fact it is true.

  5. Testing the Hypothesis • There are two basic approaches to testing a hypothesis. • 1) p-value approach • 2) critical value approach • Similar to when we calculated confidence intervals, the formula used depends upon the characteristics of the sample. These formulas result in a test statistic which is then examined at a given significance level.

  6. Age of patients:The admissions office at Memorial Hospital recently stated that the mean age of its patients was 46 years. A random sample of 120 ages was obtained from admissions office records in an attempt to disprove the claim. Is a sample mean of 44.2 years, with a standard deviation of 20 years, significantly smaller than the claimed 46 years at the a = .10 level of significance?

  7. Hamburger Fat Content:A restaurant claims that its hamburgers have no more than 10 grams of fat. You work for a nutritional health agency and are asked to test this claim. You find that a random sample of nine hamburgers has a mean fat content of 13.5 grams and a standard deviation of 5.8 grams. At a = 0.10, do you have evidence to reject the restaurant’s claim?

  8. Genetically Modified Foods: An environmentalist claims that more than 58% of British consumers want supermarkets to stop selling genetically modified foods. You want to test this claim. You find that in a sample of 100 randomly selected British consumers, 61% say that they want supermarkets to stop selling genetically modified foods. At a = 0.10, can you support the environmentalist’s claim?

More Related