Tues Sep 9 - Statistics Lecture Notes

• introductions
• questions
• algebra and arithmentic ( review or heads-up )
  • percent : 16% = 16/100 = 0.16
  • exponents : 10^-3 = 1/(10³) = 0.001; (x^a)(x^b) = x^(a+b) ; 25^0.5 = 5
  • function notation : sqrt(16) = 4 means
    "Doing the square root thing to the number 16 gives 4."
  • expanding and collecting terms :
    (a+b)³
    = (a+b)(a+b)(a+b)
    = a (a+b)(a+b) + b(a+b)(a+b)
    = [ aa(a+b) + ab(a+b) ] + [ba(a+b) + bb(a+b)]
    = aaa + aab + aba + abb + baa + bab + bba + bbb
    = a³ + 3a²b + 3ab² + b³
  • lists of numbers : tests = {65,70,70,85,85,90,90,90}
• definitions from chapter 1 - discuss briefly
  • population - all of the things under consideration
  • sample - some part of a population
  • random - particular kind of selection process with given probabilities (typically uniform) for the outcomes
  • biased - not random
  • descriptive statistics - using numbers to summarize a completely known population
  • inference - deriving numbers from a sample and using them to make educated guesses about the population they came from.
  • data - the information collected for a given project.
• spreadsheets
  • Excel or similar; show demo in class
  • "CSV" = "comma separated values" text format for import/export
  • describe data collection "class survey" assignment, pg 23

• descriptive statistics from chapter 2
  (We'll see how far we get; this'll probably continue into Thursday's class.)
  • median - half bigger, half smaller
  • mean = sum(values)/count(values)
  • standard deviation = sigma (too messy to write here)
  • z-score = (value - mean)/sigma
  • examples