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Statistics Chapter 1 & 2
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Terms in this set (37)
Total set of subjects we are interested in studying
Population
Characteristics, Generally unknown and fixed
Parameters
A list of all members of population
Frame
A survey of all elements in the frame
Example: All students at USNA, All college students in the U.S.
Census
Subset of the population which is used to gain insight about the population
Sample
Is a fact or characteristic of the sample
Statistic
The collection, organization, analysis, and presentation of data
Descriptive Statistics
Make reasonable guesses about population characteristics
*Making assumptions
Inferential Statistics
"Extra" variables that are not accounted for during experimentation and can cause skewed results
Confounding Variable
Observes data that already exists
Observe situation with no element of control
Observational Study
Reveal the response of one variable (response variable) to changes in another variable (explanatory variable)
Observational Study
Condition applied to a group of subjects in an controlled experiment
Treatment
Had treatment applied in Controlled Experiment
Experimental Group
Does not have treatment applied in Controlled Experiment
Control Group
People or things being studied in an experiment
*If people, then called participants
subjects
Causes or explains changes in a response variable
explanatory Variable
Experimental units are randomly assigned to two different treatments
completely Randomized Design
Control and treatment groups are the same
Measure response variable before and after treatments
before and after study
A fake treatment that has the potential to cause a response
the placebo effect
Participants and those interacting with participants do not know which group the participant is in
double blind study
Measure what exists without experiment
observational study
Tendency to overestimate or underestimate the value of a population parameter
bias
The relationship between two variables can be heavily affected by a third variable
simpson's paradox
Participants do not know if they are in the control or treatment group
single blind experiment
Data that can take on any value within some interval
Example: Height, Weight
Something you can measure
continuous data
Observations that are restricted to a set of values that possess gaps (such as 1,2,3,4)
Example: number of pets, number of children
Something you can count
discrete data
Quality of the data
levels of measurement
Data that represents whether a variable possesses a characteristic
nominal data
Data in categories that have some associated order
ordinal data
Data can be ordered and the arithmetic difference is meaningful
interval data
Similar to interval data, except it has a meaningful zero value
ratio data
measured on a nominal or ordinal scale
Example: gender, hair color, class year, company
qualitative data
measured on an interval or ratio scale
quantitative data
originates as measurements usually taken from some process over equally spaced intervals of time
time series data
time series data varies around some central value
Example: radar clutter, wind noise, temperature fluctuations
stationary process
time series data possesses a trend
non-stationary process
measurements created at approximately the same period in time
many measurements at the same time
cross sectional data
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