Here are my PowerPoint slides, with a summary of my narration in the speaker’s notes. You can also download a .PDF export.

Here’s the further info and how-to on the Excel macros I demonstrated.

The Student’s t-test is built into Microsoft Excel. You can use it in two ways:

- By directly inputting the T.TEST() function into a worksheet cell.
- By enabling the Data Analysis ToolPak, which comes with Excel but is disabled by default.

The Analysis ToolPak provides a convenient wizard that builds up the nice tables shown in the talk, but is otherwise equivalent to using the T.TEST() function.

Many of the macros depicted in my talk come from the excellent *Real Statistics In Excel* macro package. You can download it directly from its creator here.

In particular, this page describes the use of the Mann-Whitney U test I depict in the talk.

My custom Excel add-in for calculating confidence intervals on relative risk and difference of proportions tests is here. It provides these functions:

**RRISK**: calculates the relative risk as shown in the talk. It takes four parameters, each of which should be a single cell: ( # of individuals in control group with a NEGATIVE result, # of individuals in control group with a POSITIVE result, # of individuals in experimental group with a NEGATIVE result, # of individuals in experimental group with a POSITIVE result). Note that these are absolute counts and not percentages.**RRISK_CONF_LO**: calculates the lower bound of the confidence interval around the result of RRISK(). It takes the same four parameters as RRISK(), plus a fifth alpha parameter which is basically the % chance you’re willing to tolerate that the actual ratio lies outside your interval. ie, for a 95% confidence interval, specify 0.05.**RRISK_CONF_HI**: As RRISK_CONF_LO, but gives you the upper bound of the confidence interval.**DIFFPROP_CONF_LO**: Same parameters as RRISK_CONF_LO, but gives you the lower bound of the*difference of proportions*test –*ie*, use this when you are calculating an absolute difference in percentage points, and not a relative “monocled players are 2.4x as likely to own pants.”**DIFFPROP_CONF_HI**: As _LO, but gives you the upper bound.**T_DIFFMEANS:**Gives you the confidence interval of the difference of means in a two-sample t-test – the 8.13 value from the HDD/SSD build times example in my talk. It takes three parameters:- The range of cells containing all the values from sample group A
- The range of cells containing all the values from sample group B
- alpha, which is basically the % chance you’re willing to tolerate that the actual difference of means lies outside your interval. ie, for a 95% confidence interval, specify 0.05.

Here’s a macro-enabled worksheet demonstrating their use.

*Real Statistics In Excel* is generally an excellent resource for the background of a variety of tests and how to implement them in Excel; I relied on it heavily in my talk preparation.

statisticslectures.com has a nice set of YouTube videos that teach basic statistics in easily digestable chunks.

OnlineStatBook and StatTrek offer fairly legible introductions to all the hypothesis tests I described. In particular I got the math for my confidence macros from OnlineStatBook.

]]>A PDF export of the slides for my talk is now available here. I’ve also created a support page where I’ll gather all information, bibliography, and followup associated with that particular talk.

I’ve also posted the the videos mentioned in the slides (since obviously they can’t be embedded into a PDF):

- Two Bots: Environment-Aware Speech
- Two Bots: Starting a Conversation
- Two Bots: Memory and Context
- Left4Dead2: Variety
- Left4Dead2: Automatic Barks
- Left4Dead2: Environmentally Triggered Dialog

Thanks to everyone who stuck with me through late flights and laptop failures to the last session of GDC 2012!

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