Chapter 1: Sampling and Data Flashcards
Definitions including "Types of Sampling" and "Types of Variables (36 cards)
Random Sample
To make a sample, you randomly take a certain # from the population
Convenience Sample
To make a sample, you gather the group by a method convenient to the researcher. It is not random and could be bias (skewed).
Stratified Sampling
The population is divided into groups by similar characteristics. These groups are called strata. A random sample is taken from each strata.
Cluster Sampling
The population is divided into groups called clusters. Entire clusters are taken for analysis.
Systematic Sampling
The population items are ordered and every nth # is chosen.
Discrete Variables
They are counting #s like 0,1,2,3
Continuous Variables
They can be any type of value including fractions and decimals.
Interval Variables
No meaning for zero
Ratio Variables
Zero
Ordinal Variables
They have a natural order like grades (1st, 2nd, 3rd)
Nominal Variables
They have no natural order like the country you live in
What is the study of statistics?
The act of collecting, analyzing, and interpreting data that can then be presented
Descriptive Statistics
Organizing and summarizing data
Inferential Statistics
Uses probability to see how confident/good conclusions are
Population
People, things, objects being studied
Paremeter
A # that is a property of the population
Sample
A portion/subset of a larger population to gain info about a population
Statistic
that represents a property of the sample
Data
Actual values of the variable (#s or variables)
What is a single value called?
Datum
Mean
Arithmetic average
Proportion
Accepted values/total
Quantitative Data
-Always #s
-Comes from counting or measuring attributes of a population
Qualitative Data
-Categories or descriptions of a population
-Described by words or letters
-Display with a pie chart and bar graph
