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Card Set Information
Author:
mgt1084
ID:
156892
Filename:
Com
Updated:
2012-06-02 13:51:45
Tags:
Communication Research Methods
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Description:
Test One
Show Answers:
measurement
observable characteristics of our variables
triangulations
multiple approaches in one research study; means to enhance the quality of the work done
methodologically
using both quantitative and qualitative methods
data
instead of using methods, bring in data from different instituations or places
researcher triangulation
have multiple researchers collect data
theoretical triangulation
bring in different theories and triangulate betweent two to three of them
Variable measurement: nominal
simply asking a question that puts a variable into a category.
Nominal characteristics:
must be mutually exclusive,
must be equivalent
must be exhaustive --> you leave no possible responses out
Ordinal characteristics
must meet all the nominal characteristics, but is also rank order
anytime you have to rank your sources, such as grades or team sports
Interval characteristics
equal distances between two points on the scale
we will know how much someone likes something
zero rating
: its a point on the scale, doesnt mean it doesnt exist
Likert Scales
scale must be an interval
low numbers are disagree, higher numbers are agreement (1-5)
likert type scale uses any modification such as 1-7
semantic differential scales
polar opposites on both ends of the scale
ratio measurement scales
zero does not mean the variable does not exist
tunnel method
same types of questions throughout
funnel method
start with broader questions, then narrow them down
inverted funnel method
specific to broad
4 question order effects
consistency
: lying about something up front means you will probably lie the whole way through
fatigue
: questionnaire is too long
redundancy
: similar questions posed in different ways annoy the reader and they can start to check boxes
response set
: clicking one question the whole way through
reliability
consistency
validity
accuracy
internal validiy
draw accurate conclusions from my research
we want a high amount of internal validity
external validity
how generalizable are my findings, as in, how much can i apply what i found to other people
if you are valid you must be
reliable as well. you are not necessarily valid if you are reliable
measurement reliability
consistency of our measure and establishes high internal validity
Three ways to have measurement reliablity
test/retest method
: comparing when tests are taken twice
alternative forms
: give one group of people your measure and also give them a measure that is testing about a similar concept
split half
: compare each half of the quetions to each other
internal consistency method
best method to have measurement reliability
calculates all the possible split halves, all the possible outcomes to give the best one
Chronbachs Alpha gives this to us, we want higher than .7
Threats to internal validity
history effect
: something external to the study affects the participants
sleeper effect
: effects of the study took longer than expected and you didn't wait long enough to observe them
sensitization
: give a group a measure and ask them to take the same measure at a later time; didnt give them long enough to forget their answers
data analysis
: certain procedures and statistical analysis should be used in certain instances
more threats to internal validity
participants:
must have good incentive
Hawthorne effect
: know they are being studied
selection
: who are the people being studied
statistical regression to the mean
: need a larger group of people if your average is unusually high
mortatlity/attritition
: people drop out of the study
maturation
: internal changes that are going on in the participant
researcher threats to internal validity:
combat threats to ourselves
blind procedure
: participants do not know what group they are in
double blind
: neither participants or researcher know what group they are in
external validity:
ecological validity: does the research describe what is accurately happening in real life
replication:
exact
: repeat study in exact same way
partial
: keeps some of the study the same, but modifies others
conceptual
: keeps the concept of the study the same but uses entirely new procedures
what is a sample
a subgroup of people collected from both a population and target population that actually participate in the study
three problems with samples
size
: contingent on statistical distribution -need a minimum of thirty people
bias
: systematically exculded some people that could have been useful to the study
representativeness
: we want our sample to accurately represent our population
sampling frame
list of all possible participants
sampling unit
each person on the roster
sampling error:
the extent to which my sampling deviates from my population
confidence level
how confident i am that my sample is representative of my population --> want to be 95% or higher
confidence interval:
plus or minus range that i believe my sample will fall between
IRB guiding principle
the rewards of doing my research do not outweigh the costs
empiracal
observable
conceptualization:
the dictionary definition of what you are going to stuyd
operationalizaton:
how are you going to measure your variables
Data collection
what method are you going to use
data analysis:
what statistical tests are you going to use; qualitative or quantitative
reconceptualization
discussion about how does it fit in with the theory, is more research needed, etc
Epistemology
Pos
: researcher and work are seperate from one another
Nat
: your perspective affects your research
Axiology:
pos
: research should be value free, unbiased
nat
: how you view the world is important to your research
Methodological
pos
: deduction, reason down to a conclusion- cause and effect, quantitative methods
nat
: induction -specific to general, goal is a wholistic understanding at human behavior
Rhetorical assumption
Pos
: standardized, in the third person
Nat
: first person, more story telling type way
Research Question and the three types
tends to be less defined- unsure of what to look for or find
descriptive
: describe something or something that there is no information about
tests of association
: purpose of there is a relationship between concepts being studied
Tests of difference
: looking for differences between groups
Hypothesis and two types
hypothesis is a statement
tests of association
: purposing a relationship
tests of difference
: will state a difference between variables
Two tailed and one tailed questions
two tailed
: does not predict a direction
one tailed
: predicts a direction between the variables
independent variable
influences change in the dependent variable
dependent variable
is the variable being changed
recursive cuasal model:
one way street
: one cause --> one effect
ie
: smoking cigarettes cuases cancer, and not the other way around
non-recursive cuasal models
two way street, reciprocal cause and effect go both ways
non-causal relationship:
variables are related but changes in the one do not cause changes in the other