Week 1 - Notation Summation Flashcards
(22 cards)
Random variable
variable that can take on 2 or more values
Constant
value that does not change
Two types of random variables
discrete, continuous
Discrete data
things that can be measured in categories with no overlap
ex) hair colour, fav colour
Continuous data
variables across a continuum, can have decimals
ex) temperature, length, mass, reaction time, height
Ordered categorical/Pseudo-continuous (OC/PC)
when we use discrete data but treat it like continuous data
need to have at least 5 variables
Distributions
how the values for a random variable distributes over the range of possible values
2 types of distributions
empirical distributions and theoretical distributions
Empirical distribution
real data we have collected
described using sample statistics (average, standard deviation)
Theoretical distributions
based on abstract data (not real)
associated with populations (estimations)
described using population parameters
Sample statistics
any number calculated with data (average, standard deviation)
calculated on ACTUAL data
Population parameters
characteristics of a whole population (population mean or population standard deviation)
Estimated data
Frequency
amount of times a a score has been obtained
Population
the whole group of interest (SFU Undergrads)
Sample
Subset of values taken from a population
2 types of populations
census and statistical
Census population
the individuals/objects of interest in the study
Statistical population
the scores/measurements and inferring what they could look like
Data analysis
summarizing scores without making conclusions
Statistical inference
using sample stats to estimate population parameters (generalizing data)
Before inferencing we must:
1) Quantify - defining constructs in numbers (Intelligence to IQ scores)
2) organize
3) summarize with best representation of data
sample size
number of values recorded for a random variable (known as n)
