foundations of quantitative research Flashcards
quantitative research based on the assumption of
post-positivism
foundational concepts of quantitative research
- sampling
- variables
- hypothesis testing
- correlation and causation
sampling
studying a sample of the pop to provide a quantitative description about that population
population
total number of possible units or elements that could be included in a study
sample
a subset of the population used to represent the population
relationship between sample and population
theoretical population -> to whom do you want to generalize
-need to meet inclusion criteria
study population -> to what pop can you get access
-could be lots of ppl eligible
sampling frame -> how can you get access to them
-divided into sampling technique and recruitment strategie
-what type of sampling technique are you gonna use? ***
-how are you gonna recruit participants **
sample -> whos in your study
best sampling technique
random sampling (random selection)
-randomly sampled from pop
-equal probability of any unit of the population being selected in the sample
-best way to get sample to rep pop
-hard todo
stratified random sampling
- population is divided on a characteristic and then randomly sampled
eg. how attitudes towards PA change throughout university
50 in 1st year, 50 in 2nd year, 50 in 3rd and fourth years
systematic sampling
eg. pick every 100th person
purposive sampling
-selection on specific criteria
-information rich cases
-have a reason why you are selecting these cases
-typically used in qualitative research *
snowball sampling,
quota sampling, expert sampling
***read about different types , test q
convenience sampling
selection based on easy access to participants
-non-probability sampling
eg. uni most sampled pop (easy to recruit)
variables
variable : a property or characteristic that can take on different values
eg. multiple measures of intelligence, what criteria you use
constructs : shift over time to include different aspects
independant variables
part of your experiment that you are manipulating
-cause of dv scores
-levels of the IV
-associated with experimental designs
dependant variables
outcome variable
-“effect” of the independant variable
-measured by the researcher
causal direction
arrow from knee support to knee pain
predictor variable
-presumed “cause” in a correlational (non-experimental) study
-measured by the researcher
-like independant variable
criterion variable
-the presumed “effect” in a correlational (non-experimental) study
-measured by the researcher
-like dependant variable
extraneous variables
a variable that might effect the DV that is not the IV
-variable that explains the relationship between the IV and DV but it is not apart of the study
-alternative explanation for our findings
-dont want these in our study
extraneous variables may arise from
- participant variables : age, gender, sex, fitness
- situational variables : temp of room, water avail, wind, time of day
- experimenter variables : appearance and conduct of the researcher, encouragement
controlling for extraneous variables
- design of the study
-setting, instructions, selection criteria, random assignment
-held constant - statistical analysis
-control variables (measure these variables and can control them)
-requires you to measure the variable
other thing we can do is random assignment
identifying IV
if all criteria similar for two tests but ones thing diff = independant variable
moderators variables
variables that affect the strength of the relationship between IV/predictor and DV/criterion
-usually categorical in nature
-stable not easily manipulated
-can make relationship stronger or weaker
exercise -»»»» desire to eat
-age acting in between to influence relationship
MEDIATORS (diff than moderator)
variables that explain the relationship between IV and DV
-accounts for the relationship between the IV/predictor and the DV/criterion
-helps to think of mediator as the mechanism between IV/predictor and DV/criterion
-“Why?’
-dont need to have mediator
exercise ——> desire to eat
exercise leads to metabolism that in tern effects the desire to eat
identification of variables dependant on :
-your research question
-specific to the context of your study
eg. age
-can be predictor, control, or a moderator variable depending on the research question
hypothesis testing
process of quantitative research is founded on the assumptions of hypothesis testing
research hypothesis
a statement regarding an expected or predicted relationship between variables
research hypothesis can come from
- identifying a question or issue to be examined
- review and evaluating relevant theories and research
research hypotheses specificy (as precise as possible)
the nature and direction of the relationship between the variables
1. a related to B
->correlational design
2. a causes b
->experimental design
correlational design directional and non directional hypoth
directional : there is a positive relationship bw time after ACL surgery to start rehab and time to return of sport
-direction of relationship
non d : there is a relationship bw time after ACL surg to start rehab and time to return of sport
-relationship
experimental design directional and non directional hypothesis
directional : athletes using KT tape will experience less knee paun than athletes who use a knee brace
-state which group is scoring higher or lower on the outcome vrariable
non d : there will be a diff in knee pain bw athletess
correlation
stregnth of the association bw variables
-direction of the relationship (positive or negative)
-correlations coefficients range (-1 to 1 ; o = no relationship)
3 criteria to establish cause and effect
- the cause (IV) must precede the effect (DV) in time
- the cause (IV) and effect (DV) must be correlated with each other
- the change seen in the effect (DV) cannot be explained by another variable
type of purposive sampling - snowball sampling
identify one person with the characteristic of interest, and have that person connect with others in their own networks
eg. cancer patient ask the members of her survivor group at hospital to participate in study
purposive sampling - quota sampling
identifying a certain number or representation needed for the study and then sampling up to that number
eg. needing 10 women to complete fitness test
expert sampling
identifying people with known experience and expertise in an area of interest
eg. asking all heart surgeons from a hospital to complete a survey
