Chapter 1-Data Basics Flashcards
Numerical Variables
Consist of either continuous or discrete variables; think hard numbers like temperate (cont), distance (cont), rolled die results (disc), # of jelly beans (disc)
Continuous variables
Numerical variables like time, temp, sample mass, distance, # of hours slept, anything that can have (seemingly) infinite values between them
Discrete variables
Numerical values that increase in whole integer step-wise fashion. Ex. # of students, rolled die results, # jelly beans, babies in a nursery, etc.
Categorical Variables
a variable that can take on one of a limited, and usually fixed, number of possible values, assigning each individual or other unit of observation to a particular group or nominal category on the basis of some qualitative property.
Two subsets: regular categorical and ordinal
Regular Categorical Variable
Two or more categories with no intrinsic ordering. Ex: gender, hair color, race, animals
Ordinal Categorical Variables
Natural ordered categories and the distance between the categories is known. Ex: education, class grades, clothing size, Olympic metals, bedtime (if assigned)
Associated Variables
When two variables show some connection with one another; also known as dependent variables
Independent variables
When two variables have no known connection
Matrix (or matrices) table(s)
The column shows the variables and the row shows the observations
Exploratory Analysis
Ex: when you taste a spoonful of soup and the spoonful you tasted isn’t salty enough
Inference
Generalize and conclude for entire sample (i.e. the entire soup needs salt)
Explanatory Variable
The variable the might affect the response variable; factor studied for impact on outcome
Response variable
The variable being affected by the explanatory variable; outcome evaluated
Prospective study
Identifies individuals and collects info as events unfold
Retrospective study
Collection of data after events have taken place
