1. Guide to Using Excel For Basic Statistical Applications To Accompany Business Statistics: A Decision Making Approach, 6th Ed. Chapter 3: Describing Data Using Numerical Measures By Groebner, Shannon, Fry, & Smith Prentice-Hall Publishing Company Copyright, 2005

2. Chapter 3 Excel Examples  Population Mean - Population Mean - Foster City Hotel  Mean, Median,and Mode- Mean, Median,and Mode- Weigh-In-Motion  Percentiles and Quartiles Percentiles and Quartiles Weigh-In-Motion More Examples

3. Chapter 3 Excel Examples (continued) ä Measures of Variation - Measures of Variation - Weigh-In-Motion ä Empirical Rule - Empirical Rule - Burger N’ Brew

4. Population Mean Foster City Hotel Issue: Determine the mean nightly revenue for the Foster City Hotel. Objective: Use Excel to calculate the population mean revenue Data File is FosterCity.xls

5. Open the Excel file called FosterCity.xls Population Mean – Foster City Hotel

6. Option 1 – Use the Excel Average function. Click the function wizard – Select Statistical category – Select Average Population Mean – Foster City Hotel

7. Specify data range - Click OK Population Mean – Foster City Hotel

8. Population Mean Population Mean – Foster City Hotel

9. Optional Method: Select Tools, then Data Analysis Population Mean – Foster City Hotel

10. Select Descriptive Statistics Population Mean – Foster City Hotel

11. Define Data Range and select options Population Mean – Foster City Hotel

12. Mean Revenue Population Mean – Foster City Hotel

13. Mean, Median and Mode- Weigh-In-Motion Mean, Median and Mode- Weigh-In-Motion Issue: Does the WIM scale produce gross weights that are close to the POE weights? Objective: Use Excel to develop histograms for the weights from each scale and to compute the mean, median, and mode for each scale. The data file is Trucks.xls.

14. Open the data file called Trucks.xls Data File contains 200 trucks. Last row is 201 Mean, Median, and Mode- Weigh-In-Motion

15. Constructing histograms was covered in Chapter 2 (See Capital Credit Union) here is an optional method for determining the frequency distribution and histogram using Pivot Tables Mean, Median, and Mode- Weigh-In-Motion

16. Group the WIM weights by 10,000 pounds starting at 15,000 pounds (See Capital Credit Union example in Chapter 2 for specific steps required to group data. Mean, Median, and Mode- Weigh-In-Motion

17. Highlight the frequencies and click on the Chart Wizard to develop “quick- and dirty” histogram Mean, Median, and Mode- Weigh-In-Motion

18. Close Gaps by selecting bars – Right Clicking – select Format Data Series - then Options. Mean, Median, and Mode- Weigh-In-Motion

19. Completed Histogram for WIM gross weights – Repeat the process for POE gross weights. Then compute mean, median and modes for both variables Mean, Median, and Mode- Weigh-In-Motion

20. Select Tools – then select Data Analysis Mean, Median, and Mode- Weigh-In-Motion

21. Click on Descriptive Statistics Mean, Median, and Mode- Weigh-In-Motion

22. Define Data Range and select options Mean, Median, and Mode- Weigh-In-Motion

23. Delete un-needed columns Mean, Median, and Mode- Weigh-In-Motion

24. Mean, Median, and Mode Mean, Median, and Mode- Weigh-In-Motion

25. Percentiles and Quartiles- Weigh-In-Motion Issue: Determine Percentiles and Quartiles for WIM and POE Gross Weights Objective: Use Excel to calculate 10 th percentiles and 1 st and 3 rd quartiles for weigh-in-motion data. Data file is Trucks.xls

26. Open the data file called Trucks.xls Data File contains 200 trucks. Last row is 201 Percentiles and Quartiles – Weigh-In-Motion

27. Select function wizard – Statistical – then Percentile Percentiles and Quartiles – Weigh-In-Motion

28. Enter Data Range and desired percentile Percentiles and Quartiles – Weigh-In-Motion

29. WIM Percentile Results – Process also repeated for POE Percentiles and Quartiles – Weigh-In-Motion

30. Select Chart Wizard – click on Statistical – then select Quartiles Percentiles and Quartiles – Weigh-In-Motion

31. Enter Data Range and desired quartile Percentiles and Quartiles – Weigh-In-Motion

32. 1 st and 3 rd quartiles for WIM and POE gross weights Percentiles and Quartiles – Weigh-In-Motion

33. Measures of Variation - Weigh-In-Motion Issue: Understand the Variation in POE and WIM gross Weights Objective: Use the Excel to compute various measures of variation in WIM and POE Gross Weights Data file is Trucks.xls

34. Open the data file called Trucks.xls Data File contains 200 trucks. Last row is 201 Measures of Variation – Weigh –In-Motion

35. Click on Tools tab – then select Data Analysis – then choose Descriptive Statistics Measures of Variation – Weigh –In-Motion

36. Define data range, output location – request Summary Statistics Measures of Variation – Weigh –In-Motion

37. Standard Deviation, Variance, and Range Measures of Variation – Weigh –In-Motion

38. For POE, select Tools – Data Analysis – Descriptive Statistics Define data range, output location – request Summary Statistics Measures of Variation – Weigh –In-Motion

39. Standard Deviation, Variance, and Range Measures of Variation – Weigh –In-Motion

40. Empirical Rule - Burger N’ Brew Issue: Analyze the Phoenix Burger Sales Distribution Objective: Use the Excel to compute graphs and numerical measures necessary for using the empirical rule to analyze sales at Burger N’ Brew Data file is BurgerNBrew.xls

41. Open the data file called BurgerNBrew.xls Data File contains sales for 365 days. Last row is 366. Empirical Rule – Burger N’ Brew

42. First, develop histogram – class width = 2. Form Bins (upper limit of each class) Refer to Example 2-6 for detailed steps in developing the histogram Empirical Rule – Burger N’ Brew

43. Click on Tools tab – then Data Analysis – then Histogram Empirical Rule – Burger N’ Brew

44. Define input range, bin range, output location – check Chart Output Empirical Rule – Burger N’ Brew

45. Excel default output – See Capital Credit Union example Chapter 2 for specific steps to enhance the histogram – close gaps, label, etc. Empirical Rule – Burger N’ Brew

46. Finished Histogram – Bell Shaped Distribution Empirical Rule – Burger N’ Brew

47. To compute numerical measures – Click Tools – Data Analysis – Descriptive Statistics Empirical Rule – Burger N’ Brew

48. Define data range, output location – request Summary Statistics Empirical Rule – Burger N’ Brew

49. Mean and Standard Deviation Empirical Rule: 68% within 15.12 + (1)3.13 95% within 15.12 + (2)3.13 99.7% within 15.12 + (3)3.13) Empirical Rule – Burger N’ Brew