# Analyze the Data.  What did we learn from the data?  Does this sample convince you that more than half of all customers at this store are female? 

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Analyze the Data

 What did we learn from the data?  Does this sample convince you that more than half of all customers at this store are female?  What do you think the real percentage is? 60%, 70%, 80%?  What values are a reasonable guess for the population of females?  What percentage was of females was present for our sample?  Does our sample proportion convince you that more than half of all the customers at this Starbucks are female?

 Roll 2 dice and add them together.  What are the possible totals?  Which sum will come up most often?  Do these dice seem “fair”?  How does this relate back to the sample data?  Lets assume the Starbucks population is ”fair” or 50-50. Is there an experiment we can conduct to determine if your sample data is acceptable?

 Flip your coin 26 times and record the results  Can we extend this type of reasoning to our sample of 260 customers?  Is it possible that 50% of the customers were male and 50% female and you just happened by coincidence to get more females in your sample?  How can we decide whether our sample result is different enough from 50-50 to convince us there is something funny going on?  Computer simulation

 Let the computer applet toss a coin 260 times  If we get heads, that customer is a female, tails means a male  With this experiment, we can repeat the process of sampling from a 50-50 population many times (unlike the actual study)

 Shaughnessy, M., Chance, B., and Kranendonk, H. (2009). Focus in high school mathematics: Reasoning and sense making in statistics and probability. NCTM.  Key Curriculum Press: Exploring Statistics with Fathom, 2007  Coin Toss Applets:  http://www.socr.ucla.edu/htmls/SOCR_Experime nts.html http://www.socr.ucla.edu/htmls/SOCR_Experime nts.html  http://statweb.calpoly.edu/bchance/applets/Bino mDist3/BinomDist.html

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