Presentation is loading. Please wait.

Presentation is loading. Please wait.

7 Hypothesis Testing. Useful videos/websites: Video on writing hypothesis statements:

Similar presentations


Presentation on theme: "7 Hypothesis Testing. Useful videos/websites: Video on writing hypothesis statements:"— Presentation transcript:

1 7 Hypothesis Testing

2 Useful videos/websites: Video on writing hypothesis statements: Overview Video on hypothesis testing: Difference between Type I and II Errors:

3 Introduction to Hypothesis Testing Section 7.1

4 A hypothesis is a statement or claim regarding a characteristic of one or more populations. Definition

5 What do you mean by “claim”?

6 Let’s measure the raisins in each box with a random variable, x. H0: mu = 2 scoops H1: mu not = 2 scoops Which one is the claim?

7 Alternative hypothesis H a or H 1 contains a statement of inequality such as Null hypothesis H 0 contains a statement of equality such as , = or . For example: H0: Mr. Smith is innocent of the crime. H1: Mr. Smith is guilty of the crime. `

8 Write the claim about the population. Then, write its complement. Note: Either hypothesis, the null or the alternative, can represent the claim. Writing Hypotheses

9 A consumer magazine claims the proportion of cell phone calls made during evenings and weekends is at most 60%. Write the claim about the population. Then, write its complement. Either hypothesis, the null or the alternative, can represent the claim. A hospital claims its ambulance response time is less than 10 minutes. Writing Hypotheses claim

10 Type II Error Type I Error Correct H0: Mr. Smith is innocent of the crime. H1: Mr. Smith is guilty of the crime. Four Outcomes

11 Hypothesis Testing Errors Type I error: Reject a true Null hypothesis (i.e. innocent person found guilty) α = alpha = probability of Type I error Type II error: Do not reject a false Null hypothesis (i.e. guilty man goes free) β = beta = probability of Type II error

12 Two-tailed vs. One-tailed tests 1. two-tailed test: Equal versus not equal hypothesis Ho: parameter = some value H1: parameter some value 2. left-tailed test: Equal versus less than Ho: parameter = some value (or greater) H1: parameter some value 3. right-tailed test: Equal versus greater than Ho: parameter = some value (or less) H1: parameter some value

13 Right-tail test Two-tail test Left-tail test Types of Hypothesis Tests H a is more probable

14 One-tailed or two? 1.A university publicizes that the proportion of its students who graduate in 4 years is 82%. 14 H0:Ha:H0:Ha: p = 0.82 p ≠ 0.82 Two-tailed test z 0-zz ½ P-value area Solution:

15 One-tailed or two? 2.A water faucet manufacturer announces that the mean flow rate of a certain type of faucet is less than 2.5 gallons per minute. H0:Ha:H0:Ha: Left-tailed test z 0-z P-value area μ ≥ 2.5 gpm μ < 2.5 gpm Solution:

16 One-tailed or two? 3.A cereal company advertises that the mean weight of the contents of its 20-ounce size cereal boxes is more than 20 ounces. H0:Ha:H0:Ha: Right-tailed test z 0 z P-value ar ea μ ≤ 20 oz μ > 20 oz Solution:

17 1. Begin by assuming the equality condition in the null hypothesis is true. This is regardless of whether the claim is represented by the null hypothesis or by the alternative hypothesis. Hypothesis Test Strategy 2. Collect data from a random sample taken from the population and calculate the necessary sample statistics. 3. If the sample statistic has a low probability of being drawn from a population in which the null hypothesis is true, you will reject H 0. (As a consequence, you will support the alternative hypothesis.) 4. If the probability is not low enough, fail to reject H 0.

18 Two Methods: P-value Method – uses the probability of obtaining a sample statistics with a value as extreme (or more) than the one determined by sample data. Critical Value Method – define a ‘rejection region’ using a critical value (similar to the critical z).

19 P-values P-value (or probability value) The probability, if the null hypothesis is true, of obtaining a sample statistic with a value as extreme or more extreme than the one determined from the sample data. Depends on the nature of the test. 19 Larson/Farber 4th ed.

20 The P-value is the probability of obtaining a sample statistic with a value as extreme or more extreme than the one determined by the sample data. If z is negative, twice the area in the left tail If z is positive, twice the area in the right tail P-values P-value = indicated area zz zz Area in left tail Area in right tail For a left tail test For a right tail test For a two-tail test

21 Finding P-values: 1-tail Test The test statistic for a right-tail test is z = Find the P-value. Answer: The area to the right of z = 1.56 is 1 –.9406 = The P-value is z = 1.56 Area in right tail

22 The test statistic for a two-tail test is z = –2.63. Find the corresponding P-value. Answer: The area to the left of z = –2.63 is The P-value is 2(0.0043) = Finding P-values: 2-tail Test z = –2.63

23 P-value Method 23 1.State the claim mathematically and verbally. Identify the null and alternative hypotheses. 2.Specify the level of significance. 3.Determine the standardized test statistic. 4.Find the area that corresponds to z. State H 0 and H a. Identify . Use Table 4 in Appendix B. In WordsIn Symbols

24 24 P-value Method – Part II Reject H 0 if P-value is less than or equal to . Otherwise, fai l to reject H 0. 5.Find the P-value. a.For a left-tailed test, P = (Area in left tail). b.For a right-tailed test, P = (Area in right tail). c.For a two-tailed test, P = 2(Area in tail of test statistic). 6.Make a decision to reject or fail to reject the null hypothesis. 7.Interpret the decision in the context of the original claim. In WordsIn Symbols

25 1. Identify Hypothesis and indicate which one is the claim. H 0 : H a : 2. Identify level of significance  = 3. Compute the test statistic. [Depends on what parameter is being tested.] 4. Find the area corresponding to z.Use preferred method for finding area in tail. 5. Find the P-valuea.For a one-tailed test, P = (Area in left tail). b.For a two-tailed test, P = 2(Area in tail). 6. Make a Decision Reject H0 if p-value <= , otherwise fail to reject. 7. Interpret the decision in the context of the original claim.

26 Example: Hypothesis Testing Using P-values You think that the average franchise investment information shown in the graph is incorrect, so you randomly select 30 franchises and determine the necessary investment for each. The sample mean investment is $135,000 with a standard deviation of $30,000. Is there enough evidence to support your claim at  = 0.05? Use the P-value method. 26

27 1. Identify Hypothesis and indicate which one is the claim. 2. Identify level of significance  = Compute the test statistic. [Depends on what parameter is being tested.] 4. Find the area corresponding to z. 5. Find the P-value 6. Make a Decision 7. Interpret the decision in the context of the original claim. H0 is claim

28 Solution: Hypothesis Testing Using P-values P-value z

29 1. Identify Hypothesis and indicate which one is the claim. 2. Identify level of significance  = Compute the test statistic. [Depends on what parameter is being tested.] 4. Find the area corresponding to z. 5. Find the P-value 6. Make a Decision 7. Interpret the decision in the context of the original claim. H0 is claim

30 Solution: Hypothesis Testing Using P-values 30 P-value P = 2(0.0655) = z

31 1. Identify Hypothesis and indicate which one is the claim. 2. Identify level of significance  = Compute the test statistic. [Depends on what parameter is being tested.] 4. Find the area corresponding to z.Area to the left of is equal to Find the P-valueP = 2(.0655) because this is a two-tailed test. P = Make a Decision Since.1310 > , we fail to reject H0. 7. Interpret the decision in the context of the original claim. Since the claim was that the average (mu) was equal to $143,260, we say “there is not enough evidence to reject the claim”. H0 is claim

32 Example: Testing with P-values Employees in a large accounting firm claim that the mean salary of the firm’s accountants is less than that of its competitor’s, which is $45,000. A random sample of 30 of the firm’s accountants has a mean salary of $43,500 with a standard deviation of $5200. At α = 0.05, test the employees’ claim. 32

33 1.H0: Mu = $45,000 (or more) H1: Mu < $45,000 (left-tailed test) 2.Alpha =.05 3.Xbar = $43,500, Sx = $5200 (Since n >= 30, we can use a z-statistic) 4.Compute z-statistic (See pg 387) z = Find the P-value: P(z <= -1.58) = Since the P-value of.0571 is NOT less than or equal to alpha (.05), we DO NOT REJECT H0 7.There is not sufficient evidence to support the claim that the mean salary is less than $45,000

34 Test Decisions with P-values The decision about whether there is enough evidence to reject the null hypothesis can be made by comparing the P-value to the value of, the level of significance of the test. If fail to reject the null hypothesis. If reject the null hypothesis.

35 There is enough evidence to reject the claim. Claim Interpreting the Decision Claim is H 0 Claim is H a Reject H 0 Fail to reject H 0 Decision There is not enough evidence to reject the claim. There is enough evidence to support the claim. There is not enough evidence to support the claim.

36

37 Critical Value method 37 1.State the claim mathematically and verbally. Identify the null and alternative hypotheses. 2.Specify the level of significance. 3.Find the standardized test statistic 4.Determine the critical value(s) & rejection region(s). Use Table 4 in Appendix B. In WordsIn Symbols

38 Critical Value Z method – Part II Larson/Farber 4th ed.38 5.Make a decision to reject or fail to reject the null hypothesis. 6.Interpret the decision in the context of the original claim. If z is in the rejection region, reject H 0. Otherwise, fail to reject H 0. In WordsIn Symbols

39 Rejection Regions and Critical Values Rejection region (or critical region) The range of values for which the null hypothesis is not probable. If a test statistic falls in this region, the null hypothesis is rejected. A critical value z 0 separates the rejection region from the nonrejection region. 39

40 Rejection Regions and Critical Values 40 Finding Critical Values in a Normal Distribution 1.Specify the level of significance . 2.Decide whether the test is left-, right-, or two-tailed. 3.Find the critical value(s) z 0. If the hypothesis test is a.left-tailed, find the z-score that corresponds to an area o f , b.right-tailed, find the z-score that corresponds to an area of 1 – , c.two-tailed, find the z-score that corresponds to ½  and 1 – ½ . 4.Sketch the standard normal distribution. Draw a vertical li ne at each critical value and shade the rejection region(s).

41 Example: Finding Critical Values Find the critical value and rejection region for a two-tailed test with  = z 0z0z0 z0z0 ½ α = – α = 0.95 The rejection regions are to the left of -z 0 = and to the right of z 0 = z 0 = 1.96-z 0 = Solution:

42 Decision Rule Based on Rejection Region 42 To use a rejection region to conduct a hypothesis test, calculate the standardized test statistic, z. If the standardized test statistic 1. is in the rejection region, then reject H is not in the rejection region, then fail to reject H 0. z 0 z0z0 Fail to reject H 0. Reject H 0. Left-Tailed Test z < z 0 z 0 z0z0 Reject H o. Fail to reject H o. z > z 0 Right-Tailed Test z 0 z0z0 Two-Tailed Test z0z0 z < -z 0 z > z 0 Reject H 0 Fail to reject H 0 Reject H 0

43 Example: Testing with Critical Value Employees in a large accounting firm claim that the mean salary of the firm’s accountants is less than that of its competitor’s, which is $45,000. A random sample of 30 of the firm’s accountants has a mean salary of $43,500 with a standard deviation of $5200. At α = 0.05, test the employees’ claim. 43

44 Example – Critical Z 44 H 0 : H a :  = Rejection Region: μ ≥ $45,000 μ < $45, Decision: At the 5% level of significance, there is not sufficient evidence to support the employees’ claim that the mean salary is less than $45,000. Test Statistic z Fail to reject H 0 Z c =-1.645

45 Hypothesis Testing for the Mean Large Samples (n  30) Section 7.2

46 The z-Test for a Mean The z-test is a statistical test for a population mean. The z-test can be used: (1) if the population is normal and s is known or (2) when the sample size, n, is at least 30. The test statistic is the sample mean and the standardized test statistic is z. When n  30, use s in place of.

47 A cereal company claims the mean sodium content in one serving of its cereal is no more than 230 mg. You work for a national health service and are asked to test this claim. You find that a random sample of 52 servings has a mean sodium content of 232 mg and a standard deviation of 10 mg. At  = 0.05, do you have enough evidence to reject the company’s claim? 1. Write the null and alternative hypothesis. 2. State the level of significance.  = Determine the sampling distribution. Since the sample size is at least 30, the sampling distribution is normal. The z-Test for a Mean (P-value)

48 4. Find the test statistic and standardize it. 5. Calculate the P-value for the test statistic. Since this is a right-tail test, the P-value is the area found to the right of z = 1.44 in the normal distribution. From the table P = 1 – n = 52 s = 10 Test statistic z = 1.44 Area in right tail P =

49 6. Make your decision. 7. Interpret your decision. Compare the P-value to. Since > 0.05, fail to reject H 0. There is not enough evidence to reject the claim that the mean sodium content of one serving of its cereal is no more than 230 mg.

50 A cereal company claims the mean sodium content in one serving of its cereal is no more than 230 mg. You work for a national health service and are asked to test this claim. You find that a random sample of 52 servings has a mean sodium content of 232 mg and a standard deviation of 10 mg. At  = 0.05, do you have enough evidence to reject the company’s claim? 2. State the level of significance. = Determine the sampling distribution. Since the sample size is at least 30, the sampling distribution is normal. The z-Test for a Mean (Critical Value) 1. Write the null and alternative hypothesis.

51 n = 52 = 232 s = Make your decision. 6. Find the test statistic and standardize it. 8. Interpret your decision. 5. Find the rejection region. Rejection region Since H a contains the > symbol, this is a right-tail test. z = 1.44 does not fall in the rejection region, so fail to reject H 0 There is not enough evidence to reject the company’s claim that there is at most 230 mg of sodium in one serving of its cereal Find the critical value. z0z0

52 Using the P-value of a Test to Compare Areas z0z0 Rejection area 0.05 z 0 = –1.645 z Area to the left of z z = –1.23 For a critical value decision, decide if z is in the rejection region If z is in the rejection region, reject H 0. If z is not in the rejection region, fail to reject H 0. = 0.05 For a P-value decision, compare areas. If reject H 0. If fail to reject H 0. P =

53 Hypothesis Testing for the Mean Small Samples (n < 30) Section 7.3

54 Find the critical value t 0 for a left-tailed test given  = 0.01 and n = 18. Find the critical values –t 0 and t 0 for a two-tailed test given d.f. = 18 – 1 = 17 t 0 t 0 = –2.567 d.f. = 11 – 1 = 10 –t 0 = –2.228 and t 0 = The t Sampling Distribution = 0.05 and n = 11. Area in left tail t 0

55 A university says the mean number of classroom hours per week for full-time faculty is A random sample of the number of classroom hours for full-time faculty for one week is listed below. You work for a student organization and are asked to test this claim. At  = 0.01, do you have enough evidence to reject the university’s claim? Write the null and alternative hypothesis 2. State the level of significance = Determine the sampling distribution Since the sample size is 8, the sampling distribution is a t-distribution with 8 – 1 = 7 d.f. Testing –Small Sample

56 t = –1.08 does not fall in the rejection region, so fail to reject H 0 at = 0.01 n = 8 = s = Make your decision. 6. Find the test statistic and standardize it 8. Interpret your decision. There is not enough evidence to reject the university’s claim that faculty spend a mean of 11 classroom hours. 5. Find the rejection region. Since H a contains the ≠ symbol, this is a two-tail test. 4. Find the critical values. – t0t0 –t0–t0

57 Hypothesis Testing for Proportions Section 7.4

58 p is the population proportion of successes. The test statistic is. If and the sampling distribution for is normal. Test for Proportions The standardized test statistic is: (the proportion of sample successes)

59 Test for Proportions - Example A communications industry spokesperson claims that over 40% of Americans either own a cellular phone or have a family member who does. In a random survey of 1036 Americans, 456 said they or a family member owned a cellular phone. Test the spokesperson’s claim at  = What can you conclude? 1. Write the null and alternative hypothesis. 2. State the level of significance.  = 0.05

60 3. Determine the sampling distribution. 7. Make your decision. 6. Find the test statistic and standardize it. 8. Interpret your decision. z = 2.63 falls in the rejection region, so reject H 0 There is enough evidence to support the claim that over 40% of Americans own a cell phone or have a family member who does. 1036(.40) > 5 and 1036(.60) > 5. The sampling distribution is normal. n = 1036 x = Find the critical value Find the rejection region. Rejection region

61

62 Copyright © 2007 Pearson Education, I nc. Publishing as Pearson Addison-We sley Slide State the null and alternative hypotheses. A company claims the mean lifetime of its AA batteries is more than 16 hours. A. H 0 : μ > 16 H a : μ ≤ 16 B. H 0 : μ < 16 H a : μ ≥ 16 C. H 0 : μ ≤ 16 H a : μ > 16 D. H 0 : μ ≥ 16 H a : μ < 16

63 Copyright © 2007 Pearson Education, I nc. Publishing as Pearson Addison-We sley Slide State the null and alternative hypotheses. A student claims the mean cost of a textbook is at least $125. A. H 0 : μ > 125 H a : μ ≤ 125 B. H 0 : μ < 125 H a : μ ≥ 125 C. H 0 : μ ≤ 125 H a : μ > 125 D. H 0 : μ ≥ 125 H a : μ < 125

64 Copyright © 2007 Pearson Education, I nc. Publishing as Pearson Addison-We sley Slide You are testing the claim that the mean cost of a new car is more than $25,200. How should you interpret a decision that rejects the null hypothesis? A. There is enough evidence to reject the claim. B. There is enough evidence to support the claim. C. There is not enough evidence to reject the claim. D. There is not enough evidence to support the claim.

65 Copyright © 2007 Pearson Education, I nc. Publishing as Pearson Addison-We sley Slide True or false: Given H 0 : μ = 40 H a : μ ≠ 40 and P = You would reject the null hypothesis at the 0.05 level of significance. A. True B. False

66 Answers Answers: 1. (C) 2. (D) 3. (B) 4. (A)


Download ppt "7 Hypothesis Testing. Useful videos/websites: Video on writing hypothesis statements:"

Similar presentations


Ads by Google