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Chapter 23 Inferences about Means. Review  One Quantitative Variable  Population Mean Value _____  Population Standard Deviation Value ____.

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Presentation on theme: "Chapter 23 Inferences about Means. Review  One Quantitative Variable  Population Mean Value _____  Population Standard Deviation Value ____."— Presentation transcript:

1 Chapter 23 Inferences about Means

2 Review  One Quantitative Variable  Population Mean Value _____  Population Standard Deviation Value ____

3 Review  Estimate ________  Take random sample Calculate sample mean ________ Calculate sample standard deviation _______

4 Long Term Behavior of Sample Mean Statistic  Sampling distribution of sample mean For variables with normal distributions. For variables with non-normal distribution when sample size n is large.

5 Problem: ____________________  Solution: Replace _______________ with __________________________.  Standard error of the sample mean

6 Sampling distribution of Sample Mean

7 The t distribution  Different t distribution for each value of ________.

8 Using the t distribution  Assumptions Random sample. Independent values. No more than 10% of population sampled. Nearly Normal Population Distribution.  __________________________________________

9 History of t distribution  William S. Gosset Head brewer at Guinness brewery in Dublin, Ireland. Field experiments - find better barley and hops.  Small samples  Unknown σ. Published results under name Student. t distribution also called Student’s t.

10 The t distribution  t distribution _________________________________

11 t distribution table  Row = degrees of freedom.  Column One tail probability.  Table value = t* where P(T(n-1) > t*) = α Two tail probability.  Table value = t* where P(T(n-1) > t*) = α/2  t* = critical value for t distribution.

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14 Inference for μ  C% Confidence interval for μ.  t* comes from t distribution with (n-1) d.f.

15 Example  Find t* for 95% CI, n = 10 90% CI, n = 15 99% CI, n = 25

16 Example #1  A medical study finds that in a sample of 27 members of a treatment group, the sample mean systolic blood pressure was 114.9 with a sample standard deviation of 9.3. Find a 90% CI for the population mean systolic blood pressure.

17 Example #1 (cont.)  d.f. = ___________  t* = __________  Assumption: Blood pressure values must have a fairly symmetric distribution.

18 Example #1 (cont.)

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20 Example #2  Medical literature states the mean body temperature of adults is 98.6. In a random sample of 52 adults, the sample mean body temperature was 98.28 with a sample standard deviation of 0.68. Find a 95% confidence interval for the population mean body temperature of adults.

21 Example #2 (cont.)  d.f. = ___________  t* = 2.009  Assumption: ______________________

22 Example #2 (cont.)

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24 Hypothesis Test for μ  H O : _______________  H A : Three possibilities _____________

25 Hypothesis Test for μ  Assumptions

26 Hypothesis Test for μ  Test Statistic

27 P-value for H A : ___________  P-value = P(t n-1 > t)

28 P-value for H A : ____________  P-value = P(t n-1 < t)

29 P-value for H A : _________  P-value = 2*P(t n-1 > |t|)

30 Hypothesis Test for μ  P-value Small ________________________________ _______________________________________ Large ________________________________ _______________________________________  Small and large p-values determined by α.

31 Hypothesis Test for μ  If p-value < α  If p-value > α

32 Hypothesis Test for μ  Conclusion: Always stated in terms of problem.

33 Example #1  A medical study finds that in a sample of 27 members of a treatment group, the sample mean systolic blood pressure was 114.9 with a sample standard deviation of 9.3. Is this enough evidence to conclude that the mean systolic blood pressure of the population of people taking this treatment is less than 120. Use α = 0.1

34 Example #1 (cont.)  Ho:____________  Ha:____________  Assumptions

35 Example #1 (cont.)

36  d.f. = ______________  P-value

37 Example #1 (cont.)  Decision:  Conclusion:

38 Example #2  The manufacturer of a metal TV stand sets a standard for the amount of weight the stand must hold on average. For a particular type of stand, the average is set for 500 pounds. In a random sample of 16 stands, the average weight at which the stands failed was 490.5 pounds with a standard deviation of 10.4 pounds. Is this evidence that the stands do not hold the standard average weight of 500 pounds? Use α = 0.01

39 Example #2 (cont.)  Ho: ____________  Ha: ____________  Assumptions

40 Example #2 (cont.)

41  d.f. = ________  P-value

42 Example #2 (cont.)  Decision:  Conclusion:

43 Example #3  During an angiogram, heart problems can be examined through a small tube threaded into the heart from a vein in the patient’s leg. It is important the tube is manufactured to have a diameter of 2.0mm. In a random sample of 20 tubes, they find the mean diameter of the tubes is 2.01mm with a standard deviation of 0.01mm. Is this evidence that the diameter of the tubes is different from 2.0mm? Use α = 0.01

44 Example #3 (cont.)  Ho:______________  Ha:______________  Assumptions

45 Example #3 (cont.)

46  d.f. = ___________  P-value

47 Example #3 (cont.)  Decision:  Conclusion:


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