## 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/(10^{3}) = 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

= a^{3} + 3a^{2}b + 3ab^{2} + b^{3}
- 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

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