1. Fall Final Topics
by “Notecard”

2. Sampling
simple random sample, cluster random sample, stratified random sample, systematic random sample, multistage
voluntary response, convenience
population, sample, census
non-response, undercoverage, response bias, wording

3. Experimental Design (vocabulary)
Principals of good experiment
control, randomization, replication
experiment vs observation study
treatment, factors, experimental units, level
placebo, placebo effect
blind, double blind
lurking variable, confounding variable

4. Experimental Design completely randomized design
randomized block design
matched pair
always provide explanation of random allocation, describe treatments, compare in context

5. Simulations Number assignment Description of a trial Stopping rule
Summary of results
Be sure to clearly mark on number line so reader can follow your procedure

6. Center
mean
median
(mode)
resistance to outliers

7. Shape symmetrical, bell shaped skewed right (mean>median)
skewed left (mean<median)
bi-modal, multi-modal
uniform

8. Spread (variability) minimum, maximum range interquartile range
quartiles
variance
standard deviation: a measure of the typical or average distance each point is located from the mean
formula sheet!

9. Unusual features gaps, clusters – best seen by histogram or dotplot
outliers – best identified by boxplot
Q IQR
Q1 – 1.5 IQR

10. Binomial distribution
binomial setting…fixed # of trials
binomial formula – formula sheet
pdf versus cdf….n,p,k
mean of binomial – formula sheet
standard deviation of binomial – formula sheet
calculator tricks when P(x>#)

11. Linear Regression vocab
explanatory, response (predicted)
formulas for regression line, r, slope, y-intercept
regression line is always in context
computer output
centroid
residual plot

12. Linear Regression vocab II
influential point
extrapolation
associations
causation, common response, confounding

13. Linear Regression interpretations
slope
correlation coefficient
coefficient of determination
y-intercept
residual plot

14. Nonlinear regression linear model (L1, L2)
exponential model (L1, log y)
power model (log x, log y)
interpretations with “log” or “ln”

15. Probability rules sample space, tree diagram multiplication rule
verifying probability: 0<P<1, add to1
complement rule
general addition rule – formula sheet
general multiplication rule
disjoint/mutually exclusive

16. Conditional/independence
conditional probability
given on formula sheet
no formula if given tables
if 1 regular/2 conditional, use tree diagram
proving independence
based on P(A|B) = P(A)

17. Random variables basics
discrete versus continuous random variable
expected value (mean), variance – formula sheet
adding/subtracting constants
add/subtract the mean
variance is unchanged
multiplying (or dividing) constants
mutiply/divide the mean
mutiply/divide constant2 with variance

18. Combining Random variables
Add or subtract the means
Always add the variances
Cannot add standard deviations – must always convert!

19. Geometric geometric setting … until 1st success no formulas provided
no, no, no, no …yes

20. Normal distribution Empirical rule: 68-95-99.7 z-scores
assessing normality
histogram/stemplot : bell shaped, symmetrical, no unusual features
boxplot: symmetrical, no outliers
normal probability plot: linear, no significant gaps