Sampling and Data: Summary
1.8
2008/04/09 14:07:51 GMT-5
2008/10/27 20:31:38.760 GMT-5
Susan
Dean
deansusan@deanza.edu
Barbara
Illowsky
illowskybarbara@deanza.edu
Susan
Dean
deansusan@deanza.edu
Barbara
Illowsky
illowskybarbara@deanza.edu
Connexions
cnx@cnx.org
cluster
continuous
convenience
cumulative
data
discrete
frequency
parameter
population
probability
qualitative
quantitative
random
relative
replacement
sample
sampling
simple
statistic
statistics
stratified
systematic
variable
This module provides an outline/review of key concepts related to statistical sampling and data.
Statistics- Deals with the collection, analysis, interpretation, and presentation of data
Probability- Mathematical tool used to study randomness
Key Terms- Population
- Parameter
- Sample
- Statistic
- Variable
- Data
Types of Data- Quantitative Data (a number)
- Discrete (You count it.)
- Continuous (You measure it.)
- Qualitative Data (a category, words)
Sampling- With Replacement: A member of the population may be chosen more than once
- Without Replacement: A member of the population may be chosen only once
Random Sampling- Each member of the population has an equal chance of being selected
Sampling Methods- Random
- Simple random sample
- Stratified sample
- Cluster sample
- Systematic sample
- Not Random
- Convenience sample
Samples must be representative of the population from which they come. They must have the same characteristics. However, they may vary but still represent the same population.
Frequency (freq. or f)- The number of times an answer occurs
Relative Frequency (rel. freq. or RF)
- The proportion of times an answer occurs
- Can be interpreted as a fraction, decimal, or percent
Cumulative Relative Frequencies (cum. rel. freq. or cum RF)
- An accumulation of the previous relative frequencies