[] Q [Research] Biostatistics concept / design.

Intro. Population vs. Sample
Good sampling -> assume all population appropriately.
(Good representation) -> (Correct generalization)

I. What kind of data?

1. Qualitative(alphabet) measured: binary(2), multilevel = Politative?(multiple)
a. nominal = sex(F M)
b. ordinal = grade(ABCD)
- a, b = will be described with frequency vs proportion(or percentage)
- proportion, percentage: complement rule(success + fail = 1 or 100%)

2. Quantitative(numeric =mathematical) measured: Continuous(uncountable, like height),
Discrete(countable, finite like number of pt.)
a. interval = temperature(not meaningful zero)
b. ratio = speed(meaningful zero = absence)
- a vs b = only meaningful zero or not.

II. how to describe group?

1. Representative of data = 'center'

- Informative strength = Mean > Median >>>> Mode
- Mean: all factors matter
- Median: good for avoiding outlier

2. Variability of data = 'how spread'

- Informative strength = SD > Range(IQR)

III. How dose they apply to?

1. Qualitative = frequency, proportion
2. Quantitative = Mean/SD or Median/Range

IV. Skewed (right skewed = Lt. deviated, Rt. tail = outlier)

1. Normally distributed = Mean/SD
2. Skewed = Median/Range

[ ] JMP for chapter 5.

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