cogs 14b definitions Flashcards
What is statistics?
quantification and interpretation of variability
Discrete Variables
a variable that takes on distinct, countable values ; giving whole numbers
examples: # of siblings, political party
Continuous Variables
have potentially infinite values between any two observed values
examples: height, weight, interest rates
What are the three levels of measurement?
Nominal, Ordinal (ranked), Interval/Ratio
Define Nominal data fa me?
variables that have two or more categories, but which do not have an intrinsic order
examples: sex, blood type, favorite kpop group
Define Ordinal (ranked) data fa me?
a set of categories that are organized in and ordered or ranked sequence ; possesses an inherent order
examples: letter class grades, clothing size
Define Interval/Ratio data fa me?
- used to measure variables with equal intervals between values
~ interval has no true zero point while ratio does
~ quantitative
interval example: IQ score, GPA
ratio example: distance, weight, income
Population
Complete collection of observations or potential observations
for all individuals or units of interest
Sample
A partial set of observations taken from the population
Convenience sample
respondents from a population that can be conveniently
contacted/accessed by the researcher
examples: from a poll, survey, people in crowded locations
Parameter
value reflecting something in the entire population of interest
Statistic
a value that reflects something from a sample (can be estimate
of population parameter)
Random sampling
all potential observations in the population have an
equal chance of being selected in a sample
Sampling error
samples can be unrepresentative of the whole population to varying degrees and this causes errors of varying sizes based on level of representativeness - due to this, sample statistics will
vary by chance
Descriptive Statistics
Provides description of data collected
- Approaches presentation of data in a digestible manner
- How can we organize the sample data?
- Measures of central tendency and variability, mean, median, mode
Inferential Statistics
Helps figure out how sample of data will generalize
- Makes inferences and estimates using data
- Hypothesis testing, confidence intervals, regression analysis, ANOVA
- What does the sample data say about the population?