# Biology 2244A/B Lecture Notes - Stratified Sampling, Simple Random Sample, Blind Experiment

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Published on 17 Apr 2013

Department

Biology

Course

Biology 2244A/B

Professor

BIOSTATS: Lecture 1 Notes

Statistics: a collection of methods for planning experiments, obtaining data, and

then organizing, summarizing, analyzing, interpreting, presenting, and drawing

conclusions based on data

Population: group of all individuals you are studying

Sample: some members of the population we select to measure

Census: the collection of data from every member of the population

Parameter: a measurement describing some characteristic of a population

Statistic: a measurement describing some characteristic of a sample

Types of Data –

Nominal

- Names, labels, categories (no order we can put them in)

- E.g. hair colour

Ordinal

- Categories that have an order to them (not numbers)

- Differences are meaningless between the data values

- E.g. stress levels

Interval

- Quantitative

- Like ordinal, but difference is meaningful (+ or -)

- No natural 0 starting point

- E.g. shoe size, temperature

Ratio

- Quantitative

- Ratios and differences are meaningful (x or /)

- Natural 0 starting point

- E.g. weight, age, distance

Bias: a systematic favoritism in the data selection process, resulting in misleading

results

- If you keep choosing randomly, it does not fix your problem

Confounding: occurs when effects of variables are somehow mixed so that the

individual effects of variables cannot be identified

Discrete data: number of possible values is either a finite or a “countable” number

Continuous data: infinitely many possible values that correspond to some

continuous scale that covers a range of values without gaps, interruptions, or jumps

## Document Summary

Statistics: a collection of methods for planning experiments, obtaining data, and then organizing, summarizing, analyzing, interpreting, presenting, and drawing conclusions based on data. Population: group of all individuals you are studying. Sample: some members of the population we select to measure. Census: the collection of data from every member of the population. Parameter: a measurement describing some characteristic of a population. Statistic: a measurement describing some characteristic of a sample. Names, labels, categories (no order we can put them in) Categories that have an order to them (not numbers) Differences are meaningless between the data values. Like ordinal, but difference is meaningful (+ or -) Ratios and differences are meaningful (x or /) Bias: a systematic favoritism in the data selection process, resulting in misleading results. If you keep choosing randomly, it does not fix your problem. Confounding: occurs when effects of variables are somehow mixed so that the individual effects of variables cannot be identified.