Intro/Chapter 1 Flashcards
Descriptive Statistics
Reducing a closed set of data into key features
Inferential Statistics
Drawing conclusions about a larger group than you have data for; generalizations
3 steps of Inferential Statistics
1) Estimating/ Creating generalization
2) Testing the hypothesis
3) Fitting to a statistical model
2 Types of Numerical Data
continuous and discrete numerical data
Continuous Numerical Data
Data in a range, e.g: time, length
Discrete Numerical Data
Counted integers
2 Types of Categorical Data
Nominal and ordinal categorical data
Nominal Categorical Data
No natural order to the categories, e.g: gender, colors
Ordinal Categorical Data
A natural order to the categories, e.g: weekdays, scales on a test
Confounding Variables
variables that varies both the independent dependent variable, making an apparent, but not valid correlation.
Population
all subjects/specimens of interest
Sample
subset of population of size ‘n’
Histogram
basically a bar chart that plots y as frequency
Which side does the histogram favor?
Right. [ )
IQR
Inter quartile range Q3 - Q1
Standard deviation
s = sqrt((1/(n-1))(sum(yi-y)^2))
Sample variance
s^2
Sum of differences
sum(yi-ybar)
RV - Definition and common variable
Represents a random process (X)
Realization - Definition and common variable
observed outcome of RV (x)
Probability Distribution of X
describes values that X can take and the probability of each. ( Normally a table for discreet RV)
Discrete RV - Definition and function
only certain values can be listed p(x)
Two properties of discrete RV and variables
Mean(mu) and variance(sigma^2)
Continuous RV- Definition and function
X takes values in a range, cannot list all of them. f(x)
p.d.f - relates to… and symbol
probability density function f(x)
Mean (RV)
mu(x) = E(x) = sum(xp(x))
Variance (RV)
sigma^2 = VAR(X) = sum(((x-mu(x))^2)p(x))
Binomial RV
n identical trials with 2 outcomes. Probability of each trial is (pi)
Binomial RV - how to symbolize
X~Bin(n,(pi))
Binomial RV - p.m.f
p(x) = ((n!)/(x!(n-x)!))((pi^x)((1-pi)^(n-x)))
Binomial RV - mean
mu(x) = n(pi)
Binomial RV - variance
sigma^2 = n(pi)(1-(pi))
Normal RV - how to symbolize
X~N(mu,sigma^2)
Normal RV - inflection points occur…
at mu +- sigma
Normal RV - Area under f(x) between inflection points
0.68