IDS 270 Midterm - UIC Sparks
Most Recent Exam VersionS
Obervational Study - We observe the behavior or ask people questions as they are going
about their day to day lives. Ex. Call people and ask them how often they eat out.
Experiement - We impose some treatment on people and then observe their behavior or ask
questions. Ex. Give people a drug and then do chemical analysis of their blood.
Confounding variables - Two variables where the effect of one on the dependent variable
cannot be separated from the effect of the other. Ex. If you take drugs and drink alcohol and
then have a car accident, the effect of the drugs vs. the alcohol cannot be separated from
each other as the cause of the accident.
Population - The set of everything. Ex. All the people in America
Sample - A small group pulled from the population. Ex. Sample 40 voters from the population
of America
Voluntary Response Sampling - People volunteer to give data for a study. Ex. people text to a
phone number if they agree with a statement and text to a different one if they disagree
Convenience Sampling - People are selected to be in a sample because of convenience or low
expense. Ex. Mall intercepts, or asking the people on the floor of your dorm to fill out a
survey.
Bias - Systematically favoring a certain outcome from research
Simple Random Sampling - Label all the people in the population with a number. Have a
computer select a set of random numbers in that range. People labeled with the number are
, selected for the sample. Therefore, every person or sub-group of people has an equal chance
of being in the sample.
Stratified Sampling - First breaking the population into natural segments (called strata) and
then using random sampling within the strata. Ex. Radio stations or types of colleges
(community colleges, public universities, private universities, stand-alone liberal arts colleges)
Multi-Stage sampling - Basically practicing stratified sampling repeatedly to get to a final
sample.
Under Coverage - Where some members of the population cannot be selected for the sample.
Ex. People without phones if one is collecting data over the phone.
Non Response - When an individual selected for the sample does not provide information.
Response Bias - Not answering truthfully when asked question about sensitive subjects. Ex.
"How much pot do you smoke"
Subjects - People who are involved in an experiment.
Factors - the explanatory variables in an experiment
Level - the specific values that the experimenter chooses for a factor
Treatment - A unique combination of levels of factors given to a set of subjects
Interaction - the interplay that occurs when the effect of one factor depends on another
factor
Most Recent Exam VersionS
Obervational Study - We observe the behavior or ask people questions as they are going
about their day to day lives. Ex. Call people and ask them how often they eat out.
Experiement - We impose some treatment on people and then observe their behavior or ask
questions. Ex. Give people a drug and then do chemical analysis of their blood.
Confounding variables - Two variables where the effect of one on the dependent variable
cannot be separated from the effect of the other. Ex. If you take drugs and drink alcohol and
then have a car accident, the effect of the drugs vs. the alcohol cannot be separated from
each other as the cause of the accident.
Population - The set of everything. Ex. All the people in America
Sample - A small group pulled from the population. Ex. Sample 40 voters from the population
of America
Voluntary Response Sampling - People volunteer to give data for a study. Ex. people text to a
phone number if they agree with a statement and text to a different one if they disagree
Convenience Sampling - People are selected to be in a sample because of convenience or low
expense. Ex. Mall intercepts, or asking the people on the floor of your dorm to fill out a
survey.
Bias - Systematically favoring a certain outcome from research
Simple Random Sampling - Label all the people in the population with a number. Have a
computer select a set of random numbers in that range. People labeled with the number are
, selected for the sample. Therefore, every person or sub-group of people has an equal chance
of being in the sample.
Stratified Sampling - First breaking the population into natural segments (called strata) and
then using random sampling within the strata. Ex. Radio stations or types of colleges
(community colleges, public universities, private universities, stand-alone liberal arts colleges)
Multi-Stage sampling - Basically practicing stratified sampling repeatedly to get to a final
sample.
Under Coverage - Where some members of the population cannot be selected for the sample.
Ex. People without phones if one is collecting data over the phone.
Non Response - When an individual selected for the sample does not provide information.
Response Bias - Not answering truthfully when asked question about sensitive subjects. Ex.
"How much pot do you smoke"
Subjects - People who are involved in an experiment.
Factors - the explanatory variables in an experiment
Level - the specific values that the experimenter chooses for a factor
Treatment - A unique combination of levels of factors given to a set of subjects
Interaction - the interplay that occurs when the effect of one factor depends on another
factor
