Test #1 Flashcards
(60 cards)
Statistics
- the study of how to collect, organize, analyze, and interpret numerical information from data
- both a science of uncertainty and the technology of extracting information from data
Individuals
the people or objects included in the study
Variable
a characteristic of the individual to be measured or observed
Quantitative Variable
has a value or numerical measurement for which operations such as addition or averaging make sense
Qualitative Variable
describes an individual by placing the individual into a category or group, such as male or female
Population data
the data from every individual of interest
Sample data
the data from some individuals or interest
Population Parameter
a numerical measure that describes an aspect of a population
Sample Statistic
a numerical measure that describes an aspect of a sample
Nominal level of measurement
- applies to data that consist of names, labels or categories
- no implied criteria by which the data can be ordered from smallest to largest
Ordinal level of measurement
- applies to data that can be arranged in order
- differences between data values either cannot be determined or are meaningless=
Interval level of measurement
- applies to data that can be arranged in order
- differences between values are meaningful
Ratio level of measurement
- applies to data that can be arranged in order
- both differences between data values and ratios of data values are meaningful
- the data has a true zero
Descriptive statistics
involves methods of organizing, picturing and summarizing information from samples or populations
Inferential statistics
involves methods of using information from a sample to draw conclusions regarding the population
Simple random sample
a subset of the population selected in such a manner that every sample size of n from the population has an equal chance of being selected
Four levels of measurement
1) Nominal
2) Ordinal
3) Interval
4) Ratio
Steps to draw a random sample
1) Number all members of the population sequentially
2) Use a table, calculator, or computer to select random numbers from the numbers assigned to the population members
3) Create the sample by using members with numbers corresponding to those randomly selected
Sampling Techniques
1) Random Sampling
2) Stratified Sampling
3) Systematic Sampling
4) Cluster Sampling
5) Multistage Sampling
6) Convenience Sampling
Random Sampling
Use a simple random sample from the entire population
Stratified Sampling
- Divide the entire population sequentially
- Strata are based on a specific characteristic such as age, income, education level, and so on
- All members of the stratum share the specific characteristic
- Draw random samples from each stratum
Systematic Sampling
- Number all members of the population sequentially
- from a starting point selected at random, include every kth member of the population sample
Cluster Sampling
- Divide the entire population into pre-exiting segments or clusters
- Clusters are often geographic
- Make a random selection of clusters
- Include every member of each selected cluster in the sample
Multistage Sampling
- Use a variety of sampling methods to crate successively smaller groups at each stage
- The final sample consists of clusters