POLS 3650- Simple Statistics (SS)- Chapter 2- Garbage In, Garbage Out (GIGO)
Dependent Variable Definition
*The Effect* -variable that is altered by the impact of the independent variable -what is being measured -represented by "Y"
Independent Variable Definition
*The cause* -the variable that is deliberately changed -represented as "X"
Sampling Error
-an error that occurs when a sample somehow does not represent the target population -the difference between the results of random samples taken at the same time
Measurement Validity Definition
-exists when a measure measures what we think it measures -->if this doesn't happen, then we have the problem of *measurement invalidity* -the correlation between some measure and some outcome that the measure is supposed to predict
Casual Validity Definition
-it involves the *accuracy of our casual inferences* -this notion is a major concern whenever we are attempting to test or assert casual relationships among a set or sets of variables -exists when a conclusion that A leads to B is correct
Operationalization Definition
-the decisions we make when trying to measures substantive concepts -*defining variables in practical terms* -the process of assigning a precise method for measuring a term being examined for use in a particular study
Nonprobability Sampling Definition
-the probability of any particular member of the population *being chosen is unknown* -widely used in exploratory and qualitative research
Experimental Designs Definition
A group of approaches that *allow inferences about causes and effects to be drawn* -this type of experiment is used for making sound causal inferences
Sampling Bias Definition
A term used to describe situations in which sample statistics will *not provide accurate estimates* of population parameters because of *flaws in the sampling process*
Spuriousness Definition
A.K.A. "The assumption of non spuriousness" -The empirical association between "X" and "Y" must not be caused by some other variable that is related to and precedes in time both "X" and "Y"
Ecological Fallacy
Assumes that a generalized cultural value applies equally well to all members of the culture -ex. in neighbourhoods or cities -whatever the study is and the conclusion of the study is, the _______ _____ of it is that we can't evaluate the accuracy of the casual assertions because there is no way to study every single person in the neighbourhood or city
Validity Definition
It is a fundamental property of any type of measurement -it asks, "are we measuring what we think we are measuring?"
Random Assignment Definition
Placing research participants into the conditions of an experiment in such a way that each participant has an equal chance of being assigned to any level of the independent variable
Temporal Ordering Assumption Definition
The notion that "X" must *precede* "Y" in time
Generalizability Definition
The only real way to check whether sampling bias is a serious threat to the external validity of your findings is to compare them to previous studies -the extent to which we can claim our findings inform us about a group larger than the one we studied
Proximate Causes Definition
They are those factors that are *temporally closest* or *most directly related* to the outcome variable -ex. the effect
Distal Causes Definition
They are those factors that influence the outcome variable in an *indirect route through some other intervening variable* -when a variable is a ______ cause, its influence on the outcome variable is *eliminated or diminished* dramatically when these other variables are taken into account
Empirical Association Definition
This is the notion that "X" *AND* "Y" must be statistically related in that changes in "X" (decreases or increases) are *linked* to changes in "Y" (decreases or increases)
Garbage In, Garbage Out (GIGO) Definition
This represents the consequence of having bad measurement, bad sample(s), bad theory, and generally bad research skills and no common sense -uninformed, misguided, nefarious, and dubious statistical analyses
Probability Sampling Definition
When there is a *known* probability of being selected in a sample (ex. the key feature of probability sampling) -the selection of large, random samples will allow for clearer inferences about population values