Module 6, Foundations of Quantitative Research

Question 1

Foundational Concepts of Quantitative Research

Answer 1

1. sampling
2. variables
3. hypothesis testing
4. correlation and causation

Question 2

Foundational Concept: Sampling (population and sample)

Answer 2

• studying a sample of the population to provide a quantitative description about that population

population: the total number of possible units or elements that could be included in a study
- the units or elements is typically people (teams, organizations (classrooms), universities)

sample: a subset of the population used to represent the population
- we want to make inferences about a population
- if you are in sample you are in population
- for population, could impose inclusion criteria could be very restricted or quite broad

Question 3

Random Sampling

Answer 3

• participants are randomly selected from a population
• want sample to represent larger population
  ◦ make inferences from the
  sample about the larger
  population
• random sampling or random is the equal probability that any individual or unit from the population will be put into the sample or selected
• it is the least likely to happen
  ◦ in the process of random
  sampling you have to know
  who the entire population is
  (harder with something like
  selecting people with type II
  diabetes), the people who
  decide to consent are
  different

Question 4

Stratified Random Sampling

Answer 4

• population is divided on a characteristic and then randomly sampled
  ◦ example: how attitudes
  toward physical activity
  change throughout university
• we do this to get equal representation when we want to do statistical analyses for example
• this way there is not an over representation of a particular group (still same issues of random sampling though)
• you have to know who is in each group and consent remains an issue

Question 5

Systematic Sampling

Answer 5

• example: pick ever 100th person
• have a list of folks and say i am going to pick every one in ten for example
• not as common

Question 6

Purposive Sampling

Answer 6

• selection is based on specific criteria
  ◦ every study has inclusion
  criteria, this is not specific
  criteria (it is very specific
  inclusion criteria)
• information rich cases
• have a reason why are selecting these cases
• examples: snowball sampling, quota sampling, expert sampling

Question 7

Convenience Sampling

Answer 7

• selection is based on easy access to participants
• non-probability sampling
• most research is based on convenience samples

Question 8

Foundational Concept: Variables

Answer 8

variable: a property or characteristic that can take on different values
- a variable has to vary in values
- it is quantitative in nature
- example: look at different V02 max levels, performance measures, also things that are not directly measureable (team coherence)

Question 9

Independent Variable (IV)

Answer 9

• the variable or “part of the experiment” you are manipulating
  ◦ the “cause” of the dependent
  variable (DV) scores
  ◦ levels of the independent
  variable
  ◦ based on categories (the
  levels of IV I have is based on
  the level of groups I have)
  ◦ control groups or placebo
  groups are part of IV

Question 10

Dependent Variable (DV; outcome variable)

Answer 10

• the “effect” of the independent variable (IV)
• measured by the researcher
• the outcome of the manipulation

Question 11

Do athletes with patellofemoral syndrome (PFS) experience differences in knee pain if they wear KT tape or a knee brace?
- What is the IV/DV?
- How many Level of the IV?
- What Kind of Relationship?

Answer 11

• the independent variables are the KT or a knee brace (varying) (type of knee support) -> knee pain (DV)
• 2 levels of the IV
• arrow applies casual direction (direction of IV towards DV not other way around)

Question 12

What type of variables are used in correctional (non-experimental) studies?

Answer 12

predictor and criterion variables

Question 13

Predictor Variable

Answer 13

• the presumed “cause” in a correlational (non-experimental) study
• measured by the researcher
• if you are not manipulating anything, presumed IV in a non-experimental study
• it is common to have several predictor variables

Question 14

Criterion Variable

Answer 14

• the presumed “effect” in a correlational (non-experimental) study
• measured by the researcher
• it is not so obvious sometimes which one is predictor or criterion (pay attention to the arrow because even though it is not casual it can still help us)

time post surgery starting ACL rehab (predictor) -> time from surgery to return to play (criterion)

Question 15

Purpose: “to examine the association of total and specific types of physical activity, including walking or bicycling, exercising, work or occupational activity, home or housework, and leisure time inactivity with the risk of age-related cataract in women and men.”
Participants: “A total of 52 660 participants (23 853 women and 28 807 men) 45 to 83 years of age from the Swedish Mammography Cohort and the Cohort of Swedish Men.”

1. what type of study is this? correlational? experimental?
2. what are the predictor/IV variable(s)? predictor
3. what are the criterion/DV variable(s)? criterion
4. who can the findings from this study be generalized to?

Answer 15

1. correlational in nature
2. walking or bicycling, exercising, work or occupational activity, home or housework, and leisure time and total time physical activity
3. risk of age-related cataract in women and men (if you develop it or you do not)
4. 45-83 (middle to old-aged people), geographical location, access to healthcare etc.

Question 16

Extraneous Variables

Answer 16

• variable that might effect the DV that is not the IV
• variable that explains the relationship between the IV and DV but is not apart of the study
• they are alternative explanations for your findings but they are not apart of the study (are not interested in them)

Question 17

Extraneous Variables may arise from:

Answer 17

1) participant variables
◦ ex. age, gender, sex, physical
fitness, health status
2) situational variables
◦ ex. temperature of testing
room, water availability,
wind, time of day
3) experimenter variables
◦ ex. appearance and conduct
of the researcher,
encouragement
- things that could impact DV but it is not what you are interested in looking at in terms of the IV
- think of what else can impact your DV

Question 18

Controlling for Extraneous Variables

Answer 18

1) can be controlled through the design of the study
- examples: experimental setting, instructions to participants, experimenter-participant interactions, participant selection criteria, random assignment with a control group
- held constant (through the selection/inclusion criteria - so certain people may not be selected as a result / eliminate different participants extraneous variable)
◦ is preferred method
2) can be controlled through statistical analysis
- ‘control variables’
- requires you to measure the variable
- measure something and try to control it statistical

Question 19

Random Assignment

Answer 19

random assignment is different than random sampling (how you get people into the study)
- random assignment: we already have the sample, there is an equal probability of people being placed into any group (the groups are equivalent (amongst each group if equivalent not everyone) - equal which helps reduce extraneous variables)

Question 20

Moderators

Answer 20

• variables that affect the strength of the relationship between IV/predictor & DV/criterion
• usually categorical in nature

exercise -> desire to eat
(age - moderator)

Question 21

Mediators

Answer 21

• variables that explain the relationship between IV & DV
• accounts for the relationship between the IV/predictor and the DV/criterion
• helps to think of mediator as the mechanism between IV/predictor & DV/criterion
• ‘why?’
• predictor is going to the mediator (predictor and criterion at the same time) and mediator goes to criteria

Question 22

Note on Variables

Answer 22

• identification of what the IV, DV, extraneous, control, mediator, and moderator variables is
  dependent on:
  ◦ our research question
  ◦ is specific to the context of
  your study
• example: age
  ◦ an be a predictor, control, or
  a moderator variable
  depending on the research
  question
• do not need to have moderator or mediator

Question 23

Hypothesis Testing

Answer 23

the process quantitative research is founded on the assumptions of hypothesis testing

Question 24

Research Hypotheses

Answer 24

a statement regarding an expected or predicted relationship between variables (has to be very specific)

research hypotheses specify (as precisely as possible) the nature (is there a relationship or is there not between variables) and direction of the relationship between the variables

Question 25

Research hypotheses can come from a variety of sources:

Answer 25

1. identifying a question or issue to be examined
2. review and evaluating relevant theories and research (how these variables are actually related to one another)
   A. theories helps us define
   what variables we might
   need to measure and
   define relationships
   between variables
   B. justify the hypothesis (use
   theories in previous
   research)

Question 26

A related to B versus A causes B

Answer 26

1. correlational design (associated can also be in place of related)
2. experimental design

Question 27

Time post ACL surgery to start rehab -> time to return to play
- is this correlational or experimental?
- what kind of variables are they?

Answer 27

correlational design / predictor and criterion

Question 28

There is a positive relationship between the time after ACL surgery to start rehabilitation and the time the athlete returns to their sport

There is a relationship between the time after ACL surgery to start rehabilitation and the time the athlete returns to their sport

Which one is directional and non-directional?

Answer 28

1. directional hypothesis
2. non-directional hypothesis

Question 29

Athletes with PFS who use KT tape will experience less knee pain than athletes with PFS who use a knee brace

There will be a difference in knee pain between athletes with PFS who use KT tape and those who use knee bracing

Are these experimental or correlational?
Which one is non-directional and which one is directional?

Answer 29

experimental
1. directional
- want to state which group is scoring higher or lower on the outcome variable (instead of saying positive or negative relationship)
- the less part indicates direction
2. non-directional

Question 30

A group of researchers were interested in seeing if caffeinated underwear would help participants
lose weight. participants were divided into a control group (wore their regular underwear) and an experimental group (wore caffeinated underwear)
1. What is the design of the study?
2. What is the independent and dependent variable?
3. Write a directional research hypothesis

Answer 30

1. experimental (manipulating type of underwear’s)
2. 2 levels of the IV (type of underwear’s) - lose weight
3. those who wear caffeinated underwear will lose more weight than those who wear normal underwear’s OR the participants who use caffeinated underwear will experience more weight less than those who wear normal underwear

Question 31

Correlation ≠ Causation

Answer 31

• the strength of the association between variables
• direction of the relationship (positive, negative)
• correlations coefficients range (-1 to +1; 0 = no relationship) - represented by lower case ‘r’
  ◦ if there is no correlation that
  coefficient will be zero
  ◦ only ranges from +1 to -1
  (the more you move away
  from 0 the stronger the
  relationship)
  ◦ positive correlation
  coefficient - positive
  relationship
  ◦ negative correlation
  coefficient- negative
  relationship
  ◦ horizontal line for no
  correlation

Question 32

3 Criteria to Establish Cause and Effect

Answer 32

1. the cause (IV) must precede the effect (DV) in time
2. the cause (IV) and effect (DV) must be correlated with each other (has to be a relationship there)
3. the change seen in the effect (DV) cannot be explained by another variable (tricky; extraneous variables - can we try to identify the other alternative explanations for these particular findings - how do you control for these and isolate)

Question 33

Purposive Sampling: Snowball Sampling

Answer 33

e.g., identify one person with the characteristic of interest, and have that person connect with others in their own network; for example, a woman with breast cancer might ask all the members of her survivorship group at the hospital to participate in a study

Question 34

Purposive Sampling: Quota Sampling

Answer 34

e.g., identifying a certain number or representation needed for the study and then sampling up to that number; for example, needing 10 women to complete a fitness test

Question 35

Purposive Sampling: Expert Sampling

Answer 35

e.g., identifying people with known experience and expertise in an area of interest; for example, asking all heart surgeons from a local hospital to complete a survey