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

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Published on 17 Apr 2013
School
Western University
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
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## 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.

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