Chapter 3: Measurements, Mistakes & Understandings Flashcards
(23 cards)
deliberate bias
a survey being conducted to support a certain cause phrase questions in a biased manner; wording of the question will indicate a desired answer
unintentional bias
questions may be worded in such a way that the meaning is misinterpreted by a large percentage of the respondents
desire to please
most survey respondents have a desire to please the person asking the question so they may respond to the questions in the manner that they think the asker is looking for
asking the uninformed
people tend not to let other know when they are uninformed or misinformed to so they will likely answer question incorrectly
unnecessary complexity
what the question and asking and what way the answer should be constructed should be clear and not open to interpretation
ordering of questions
the ordering of questions can alter one’s response
confidentiality & anonymity
the sample of people surveyed will provide certain response depending on whether or not they feel that their information and identity are protected
open questions
a question in which the respondent are allowed to answer in their own words
closed questions
a question in which the respondent must select an answer from a list of predetermined alternatives
categorical variables
are those we can place into a category but that may not have any logical ordering. example: male or female
ordinal variables
variables that have a natural ordering as “strongly agree” to “strongly disagree” or level of education
nominal variables
To distinguish them from ordinal variables, categorical variables for which the categories do not have a natural ordering are sometimes called nominal variables.
measurement/quantitative variables
are those for which we can record a numerical value and then order respondents according to those values.
interval variable
is a measurement variable in which it makes sense to talk about differences, but not about ratios. example: temperature
ratio variable
has a meaningful value of zero, and it makes sense to talk about the ratio of one value to another. example: pulse rate, speed
discrete variable
variable is one for which you could actually count the possible responses (these variables are always reported in whole numbers). example: # of car accidents in a set period of time
continuous variable
can be anything within a given interval. Age, for example, falls on a continuum.
valid measurement
is one that actually measures what it claims to measure. To determine whether a measurement is valid, you need to know exactly what was measured.
reliable measurement
is one that will give you or anyone else approximately the same result time after time when taken on the same object or individual.
biased measurement
a measurement that is systematically off the mark in the same direction. For example: If you were trying to weigh yourself with a scale that was not satisfactorily adjusted at the factory and was always a few pounds under, you would get a biased view of your own weight.
variability
measurements are likely to differ from one time to the
next or from one individual to the next because of unpredictable errors or discrepancies that are not readily explained.
measurement error
The amount by which each measurement differs
from the true value
natural variability
variability the results from the changes within the time period that the variable that is measured (unemployment rates, heights, blood pressure etc) or across different individuals within a sample size
