1. Good Statistics with Microsoft Excel Howard Grubb, Roger Stern and Colin Grayer Department of Applied Statistics 6th June 2001

2. Statistical Activities Statistics is concerned with data management and analysis Applied Statistics Advisory service to support research across the University Excel is widely used Statistics teaching by many departments Excel can be a useful starting point most students are familiar with Excel Data from other sources administrative – workloads, exam marks

3. Contents Why Excel? Why this seminar? Using standard Excel Extending it Good Practice Conclusions Discussion …

4. Why Excel? Very popular “everyone” knows it, except perhaps statisticians! Good for exploratory/descriptive statistics graphs and tables - see later Dynamic both graphics and calculations change data and analysis updates Easy to extend powerful (visual) language associated with Excel

5. Practical examples Rice survey and bank data list format (by factor) Administrative – timetabling restricting data multiple, linked sheets (one copy of data) (extending Excel – programs vs packages) Exploratory - anaerob2.xls dynamic calculation

6. Software Strategy Mixed software strategy students are comfortable within Windows sometimes more so than staff! so mixing software for statistical applications is now straightforward training can concentrate on the statistical ideas and not simply on mastering the software Easy to add Excel to existing software adds to, does not need to replace existing statistical software (e.g. Minitab, SPSS …)

7. Why ignore Excel? Does not encourage good (statistical) practice provides the freedom to make a mess from data entry onwards (Advanced) statistical facilities have problems not all numerically stable not sufficiently powerful, hence usually still need another (statistics) package Why add yet another package?

8. On balance Suggest the case for adding Excel is strong to our Advisory support and encouraging staff and students to use it well Is sufficiently strong to warrant this seminar Otherwise many people use it extensively, by default perhaps spending longer, and not doing their work as efficiently as they might

9. Excel in action Tabulation called pivot tables And dynamic nature can make some teaching easy Demonstration tables - bank plots - templates

10. Adding “good statistics” Excel encourages “list format” obvious layout of data for any statistics package But some Excel statistics and graphics do not use the data in this form So to encourage “good statistics with Excel” we have our own Excel add-in written within Department of Applied Statistics other Add-Ins extend the facilities ours improves the existing ones

11. http://www.rdg.ac.uk/~snsgrubb/excel Manage menu including stack and unstack Graphics menu including x-y plot by a factor boxplots Statistics menu including describe, summary, t-interval uses solid algorithms General data in “list” format handles missing values links (so dynamic) handles filters (hidden rows)

12. Demonstration Rice x-y plot adding lines (UnStack) boxplots by UnStack Dynamic plots Help and good-practice guidelines

13. Adding to Excel Easy to do – now offer training on this Facilities for adding are easier than in many statistics packages Results in an environment easy to distribute available on most machines Example timetable - program adaptive sampling – quick demonstration SSC-Stat - package

14. Good-practice guidelines Validated data entry When to move to a database package? Keep your data safe! Exploratory analysis/graphics Basic statistics When to move to a statistics package When to stop programming?!

15. Expertise/resources at Reading Training courses could be provided based on courses we already run for external clients Excel for Statistics, what you can do (3 days, including macros) Basic statistics using Excel (2 days, from January 2002) Scientific data management using MS Access (2-3 days) Support for Good Practice local “add-in” many other resources – see web-page Advisory Service