1. The Population Mean and Standard Deviation 1 X μ σ

2. Computing the Mean and the Standard Deviation in Excel μ = AVERAGE(range) δ = STDEV(range) 2

3. Exercise Compute the mean, standard deviation, and variance for the following data: 1 2 3 3 4 8 10 Check Figures – Mean = 4.428571 – Standard deviation = 3.309438 – Variance = 10.95238 3

4. The Normal Distribution 4 X μ P(-∞ to X)

5. Solving for P(-∞ to X) in Excel P(-∞ to X) = NORMDIST(X, mean, stdev, cumulative) – X = value for which we want P(-∞ to X) – Mean = µ – Stdev = δ – Cumulative = True (It just is) 5

6. Exercise in Solving for P(-∞ to X) What portion of the adult population is under 6 feet tall if the mean for the population is 5 feet and the standard deviation is 1 foot? – Check figure = 0.841345 6

7. P(X to ∞) 7 X μ

8. P(X to ∞) = 1 – P(-∞ to X) 8 X μ P(X to ∞) P(-∞ to X) P=1.0

9. Exercise What portion of the adult population is OVER 6 feet tall if the mean for the population is 5 feet and the standard deviation is 1 foot? – Check figure = 0.158655 9

10. P(X 1 to X 2 ) 10 X1X1 P(X1 < X < X2) X2X2

11. P(X 1 to X 2 ) in Excel P(X 1 to X 2 ) = P(-∞ to X 2 ) - P(-∞ to X 1 ) P(X 1 to X 2 )=NORMDIST(X 2 …)–NORMDIST(X 1 …) 11

12. Exercise in P(X 1 to X 2 ) in Excel What portion of the adult population is between 6 and 7 feet tall if the mean for the population is 5 feet and the standard deviation is 1 foot? – Check figure = 0.135905 12

13. Computing X 13 X μ P(-∞ to X)

14. Computing X in Excel X = NORMINV(probability, mean, stdev) – Probability is P(-∞ to X) 14

15. Exercise in Computing X in Excel An adult population has a mean of 5 feet and a standard deviation is 1 foot. Seventy-five percent of the people are shorter than what height? – Check figure = 5.67449 15

16. Z Distribution A transformation of normal distributions into a standard form with a mean of 0 and a standard deviation of 1. It is sometimes useful. 16 Z 0.12 0 X 8.6 8 μ = 8 σ = 10 μ = 0 σ = 1 P(X < 8.6)P(Z < 0.12)

17. Computing P(-∞ to Z) in Excel Z = (X-μ)/δ P(-∞ to Z) = NORMDIST(Z, mean, stdev, cumulative) – Mean = 0 – Stdev = 1 – Z = (X-μ)/δ – Cumulative = True (It just is) 17

18. Exercise in Computing P(-∞ to Z) in Excel An adult population has a mean of 5 feet and a standard deviation is 1 foot. Compute the Z value for 4.5 feet all. What portion of all people are under 4.5 feet tall – Z check figure = -.5 (the minus is important) – P check figure = 0.308537539 18

19. Z Distribution A transformation of normal distributions into a standard form with a mean of 0 and a standard deviation of 1. It is sometimes useful. 19 Z 0.12 0 X 8.6 8 μ = 8 σ = 10 μ = 0 σ = 1 P(X < 8.6)P(Z < 0.12)

20. Computing Z in Excel Z for a certain value of P(-∞ to Z) =NORMINV(probilility, mean, stdev) – Probability = P(-∞ to Z) – Mean = 0 – Stdev = 1 Change the Z value to an X value if necessary – Z = (X-μ)/δ, so – X = µ + Z δ 20

21. Exercise in Computing Z in Excel An adult population has a mean of 5 feet and a standard deviation is 1 foot. 25% of the population is greater than what height? – Check figure for Z = 0.67449 – Check figure for X = 0.308537539 21

22. Sampling Distribution of the Mean 22 Normal Population Distribution Normal Sampling Distribution (has the same mean) δ is the Population Standard Deviation δ Xbar is the Sample Standard Deviation. δ Xbar = δ/√n δ Xbar << δ

23. Sampling Distribution of the Mean For the sampling distribution of the mean. – The mean of the sampling distribution is X bar – The standard deviation of the sampling distribution of the mean, δ Xbar, is δ/√n This only works if δ is known, of course. 23

24. Exercise in Using Excel in the Sampling Distribution of the Mean The sample mean is 7. The population standard distribution is 3. The sample size is 100 Compute the probability that the true mean is less than 5. Compute the probability that the true mean is 3 to 5 24

25. Confidence Interval if δ is Known Using X 25 Point Estimate for X bar Lower Confidence Limit Xmin Upper Confidence Limit Xmax X units:

26. Confidence Interval 95% confidence level X min is for P(-∞ to X min ) = 0.025 X max is for P(-∞ to X max ) = 0.975 X = NORMINV(probability, mean, stddev) – Here, stdev is δ Xbar = δ/√n 26

27. Exercise For a sample of 25, the sample mean is 100. The population standard deviation is 50. What is the standard deviation of the sampling distribution? – Check figure: 10 What are the limits of the 95% confidence level? – Check figure for minimum: 80.40036015 – Check figure for maximum: 119.5996 27

28. Confidence Interval if δ is Known Done Using Z 28 Z α/2 = -1.96Z α/2 = 1.96 Z units:0

29. Confidence Intervals with Z in Excel X min = X bar – Z α/2 * δ/√n – Why? – Because multiplying a Z value by δ/√n gives the X value associated with the Z value X max = X bar + Z α/2 * δ/√n Common Z α/2 value: – 95% confidence level = 1.96 29

30. Exercise in Confidence Intervals with Z in Excel The sampling mean X bar is 100. The population standard deviation, δ, is 50. The sample size is 25. What are X min and X max for the 95% confidence level? – Check figure: Z α/2 = 1.96 – X min = 80.4 (same as before) – X max = 119.6 (same as before) 30

31. Confidence Intervals, δ Unknown Use the sample standard deviation S instead of δ Xbar. – No need to divide S by the square root of n – Because S is not based on the population δ Use the t distribution instead of the normal distribution. 31

32. Computing the t values Z = TINV(probability, df) – probability is P(-∞ to X) – df = degrees of freedom = n-1 for the sampling distribution of the mean. X min = X bar – Z(.025,n-1)*S X max = X bar + Z(.975,n-1)*S 32

33. Exercise For a sample of 25, the sample mean is 100. The sample standard deviation is 5. What is Z for the 95% confidence interval? – Check figure 2.390949 What is the lower X limit? – Check figure 88.04525 (With δ known, was 80.40036015) What is the upper X limit? – Check figure 111.9547 (With δ known, was 119.5996) 33

34. t test for two samples What is the probability that two samples have the same mean? 34 Sample ASample B 11 32 55 54 78 99 10 Sample Mean 5.7142865.571429

35. The t Test Analysis Go to the Data tab Click on data analysis Select t-Test for Two- Sample(s) with Equal Variance 35

36. With Our Data and.05 Confidence Level 36 t stat = 0.08 t critical for two- tail (H1 = not equal) = 2.18. T stat < t Critical, so do not reject the null hypothesis of equal means. Also, α is 0.94, which is far larger than.05

37. t Test: Two-Sample, Equal Variance If the variances of the two samples are believed to be the same, use this option. It is the strongest t test—most likely to reject the null hypothesis of equality if the means really are different. 37

38. t Test: Two-Sample, Unequal Variance Does not require equal variances – Use if you know they are unequal – Use is you do not feel that you should assume equality You lose some discriminatory power – Slightly less likely to reject the null hypothesis of equality if it is true 38

39. t Test: Two-Sample, Paired In the sampling, the each value in one distribution is paired with a value in the other distribution on some basis. For example, equal ability on some skill. 39

40. z Test for Two Sample Means Population standard deviation is unknown. Must compute the sample variances. 40

41. z test Data tab Data analysis z test sample for two means 41 Z value is greater than z Critical for two tails (not equal), so reject the null hypothesis of the means being equal. Also, α = 2.31109E-08 <.05, so reject.

42. Exercise Repeat the analysis above. 42