## Statistics 100 Fall 2017 Sections

 Karle Flanagan Section L1TR 12:30pm-1:50pmLincoln Hall Theater Section L2TR 3:30pm-4:50pmLincoln Hall Theater Ellen Fireman Online Section Danielle Sass Section S1MWF 12:00pm-12:50pm1027 Lincoln Hall

## Outline of Course Content

 Experimental Design - Why randomized controls are key. What the possible confounders in observational studies are. Descriptive Statistics - mean, median, SD, histograms, normal curve, etc. Linear Regression - correlation coefficient, regression equation, etc. Probability Statistics for Chance Numbers - expected value and Standard error of chance processes, probability histograms and convergence to normal curve. Focus is on developing simple chance models box models- drawing numbers at random from a box) that more complicated sampling processes can be translated into. Sampling and Statistical Inference - Using sample means and percents to estimate population means and proportions, and attaching margins of errors to our estimates by computing confidence intervals. Why randomized sampling is key. Hypothesis Tests-one sample and two sample Z-tests, t-tests and chi-square tests for goodness of fit and independence. Focus is on understanding how these tests depend on chance models. Limits of Significance Tests- understanding what the P-value means and under what circumstances it is valid. (For example, hypotheses must be stated before looking at the data, the total number of experiments before significant results were found must be reported, etc.)

#### Meditations on the Statistical Method

Plato despair!
We prove by norms
How numbers bear
Empiric forms,

How random wrongs
Will average right
If time be long
And error slight;

But in our hearts
Hyperbole
Curves and departs
To infinity.

Error is boundless.
Nor hope nor doubt,
Though both be groundless,
Will average out.

JV Cunningham

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