# Chap Important Not Important … - Population vs sample (parameter vs statistic) ```Chap
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Important
- Population vs sample (parameter vs statistic)
- 2 branches of statistics
- qualitative vs quantitative
- observational study vs experiment
- sampling approaches
Distributions: frequency, relative frequency, cumulative
Graphical displays: histograms, stem-and-leaf, dotplots
(when to use which)
- measures of center: mean, median mode (how to
calculate [formulas!], when to use)
Distribution shapes: uniform, skewed, symmetric …
- measures of variation: range, variance (population and
sample), std dev (pop and sample); how to calculate
(formulas!))
- Empirical Rule
- quartiles (how to calculate and interpret)
- percentiles (how to interpret)
- 5 number summary and box-and-whisker
- IQR (how to calculate and interpret)
- z-score/standard score (how to calculate and interpret)
!!
- Probability – Fundamental Counting Principle, trees
- Classical, Empirical, Subjective probability
- Probability distribution: what is it, properties, mean
- Complements
- Independent vs dependent events
- Mutually exclusive events
- Addition Rule for independent events
- Venn diagram
- Combination &amp; Permutation (when to use, how to
calculate)
Not Important …
- Levels of measurement
(nominal, ordinal …)
- Use of random # table
- replication, placebo,
confounding variable
- identifying bias sampling/survey
- class limits, class boundaries
- frequency polygon, ogive, pie
chart, time series
- weighted mean
- Chebychev’s Theorem
- std dev of grouped data
- how to determine outliers
- Law of large numbers
- Conditional probability formula
- Distinguishable Permutations
```