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Exam 2 Flashcards

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1
Q

Determining Sample v. Population

Sample

A

A subset of the population (smaller in size)
Needs to be representative
Tested due to convenience

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2
Q

Determining Sample v. Population

Population

A

A group of data or people to which we want our research to refer
Is like the sample, only larger
Difficult to get access to these observations

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3
Q

Sample selection (sampling)

A 
Determine population for research study
Determine access to sample
Determine representative sample size (G*Power program does this)
Decide upon sampling method
Get your participants!
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4
Q

The Interplay

A 
Sample Size (1 to Infinity)
Power (Low, Moderate, High)
Alpha Level (0.01, 0.05)
Effect Size (Small, Medium, Large)
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5
Q

Random sampling methods

A 
Simple Random Sampling
Systematic Sampling
every Nth person
Stratified Random Sampling (proportionate or non-proportionate)
you split the group
Cluster Random Sampling
the groups were split for you
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6
Q

Nonrandom Sampling Methods

A

Convenience Sampling
drawing from people that are easiest to access
Quota Sampling- gathering representative data from a group
Purposive Sampling-sampling based on opinion of expert
Snowball Sampling-existing subjects recruit future subjects

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7
Q

Types of research

A

Non-Experimental Research
Experimental Research
Quasi experimental
Mixed methods research

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8
Q

non experimental research

A 
descriptive
relational
predictive
survey
case study
naturalistic observation
archival
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9
Q

experimental research

A

differential, cause and effect

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10
Q

quasi ecperimental

A

same as expectational but with less control over participants and variables

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11
Q

mixed methods research

A

both experimental and non experimental components

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12
Q

research designs

A

Each research strategy has it’s own design options

Things to consider:
Group versus Individual
Within-subject versus Between-subject
Variables included in study
Analysis of variables
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13
Q 
Research Procedures
(Methodology)
A 
How the variables will be manipulated
How the variables will be regulated
How the variables will be measured
Necessary sample size
Measures to be used
Specific study procedures
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14
Q

Quantitative v. Qualitative Research

quantitative

A

Precise and Measurable
Most commonly seen in publications
Data is in numerical form and is statistically analyzed

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15
Q

Quantitative v. Qualitative Research

qualitative

A

Subjective and interpretive
Multimethod triangulation is used
Data is in categorical form or is made of observations

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16
Q

Maintaining Validity & Reliability
In Specific Instruments
(in chapter 3)

A

Called Instrumental Reliability & Validity

Determines whether each individual test or questionnaire does what it is supposed to do each time it’s used

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17
Q

Maintaining Validity & Reliability
In Overall Research
(in chapter 6)

A

Called Research Reliability & Validity

Determines whether the project as a whole is doing what you intended and can be replicated

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18
Q

Four Types of Research Validity

A

Internal Validity
Construct Validity
External Validity
Statistical Conclusion Validity

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19
Q

external validity

A 
Extent to which we can generalize results of a research study 
Types- 
Population
Ecological
Temporal
Treatment variation
Outcome

Threat-
Not id target population
Not choosing broad enough sample

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20
Q

Statistical Conclusion Validity

A 
Conclusions about the conversation of IV and DV
-validity is based on research analysis
Threats-
Improper analysis 
Insufficient power
Inaccurate effect size conclusions
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21
Q

Internal Research Validity

A 
accurately identifying causation 
Threats:
Ambiguous Temporal Precedence
Events Outside the Laboratory (History)
Maturation
Effects of Repeat Testing
Regression Effects
Selection
Mortality
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22
Q

Construct Research Validity

A

Measures adequately reflect operationalized construct
Threats:
Inadequate Explanation of Construct
Loose Connection Between Theory & Method
Ambiguous Effects of Independent Variables
Motivations & Reactivity of Participants
Experimenter Effects

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23
Q

Statistical Conclusion Research Validity

A

conclusions about the conversation of the IV and DV
This validity is based on researcher analysis
Threats:
Improper Analysis
Insufficient power
Inaccurate Effect Size Conclusions

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24
Q

research reliability

Study These Flashcards
A

Determined through Replication Studies
To further prove findings, these may be done by yourself or fellow colleagues
To challenge your findings, these may be done by other researchers

25
research preocess
``` Identify Problem or Question Create Hypothesis Statement Complete Written Literature Review Plan Research Study Collect Sample of Participants Conduct the Experiment Analyze Data Interpret Results Debrief as Needed Write Research Report to Present Results ```
26
Experimental Research Goals
Determine causal relationships Manipulate one variable (IV) to change the outcome of another (DV) Measure desired variables in an accurate manner Remain free of bias & attempt to rule out experimenter point of view Determine differential results Control for other potential problematic (extraneous) variables
27
experimental research
Attempt to establish the existence of a cause and effect relationship between two variables by manipulating one and measuring the second and controlling all others
28
The Experimental Approach | advantages
Casual description and explanation ability to manipulate variables control
29
The Experimental Approach | disadvantages
Doesn’t test effects of non-manipulated variables artificiality views subjects as objects
30
Designing an Experiment
What is your experimental hypothesis? What is your null hypothesis? Why do you think your experimental hypothesis will be supported? What is your IV and how will you operationalize it? What is your DV and how will you operationalize it? What does your sample size need to be? How would you determine whether a participant was in the treatment or control group? What would statistically significant results mean? What would it mean if your results were not statistically significant? What measurement level is your data and what statistical test would you use to analyze your data?
31
Experimental Research Settings
Field Experiments Laboratory Experiments Internet Experiments
32
Treatment
The intervention given to participants or the group of participants who get the intervention
33
condition
The group of participants or their data points, either the control or treatment
34
factor
When data is split by something other than a true intervention or outside experimenter control
35
level
The number of groups in the factor or IV
36
Design Components
D:Structures and procedures used in constructing research designs Control or Comparison Groups Pretest Treatment Component Posttest Treatment Component Within- and/or Between-Subject IVs Inclusion of 1+ Theoretically Interesting IVs Measurement of 1+ Theoretically Interesting DVs
37
The Research Design
D:The outline, plan, or strategy used to investigate the research hypothesis ``` Can be between or within and weak or strong Includes: How to collect valid & reliable data How to analyze the collected data Whether or not a pretest is needed How to maintain a control group How to assign participants to the groups ```
38
The Research Variable
D: The aspect of a testing condition that is altered by differing conditions ``` The concepts that are being measured & studied The 2 (or more) constructs that you believe are related The level of relationship between variables provides support for or against the theory generated by the experiment ```
39
Main Experimental variables
``` -Independent Variable Causes changes to DV -Dependent Variable Effected due to IV -Extraneous Variable Could also explain the experimental outcome -Confounded Variable Cannot be separated from the IV -Mediating Variable Explains the relationship -Moderating Variable Influences the strength of the relationship ```
40
Environmental control
Experimenter must maintain a controlled environment during data collection period
41
Extraneous variation control
Each data collection period must be strictly controlled and made identical in all ways
42
Control variable(s)
Any variables that may confuse the results, need to be controlled for, either ruling them in or out
43
Control condition
Having a group of participants that do not get any treatment for more evidence of causation
44
Control Strategies: | Beginning Your Experiment
``` Initial Preparation Random Assignment Matching Holding Variable Constant Build Extraneous Variable into Study Design Yoked Control Equating Participants Precision Control Frequency Control ```
45
Control Strategies: | Conducting Your Experiment
-Control in the Laboratory -Precision in Instrumentation -Counterbalancing Randomized Intrasubject Complete Incomplete -Participant Effects Double-Blind Placebo Method Deception Participant Interpretation -Experimenter Effects Recording Errors Experimenter Attribute Errors Experimenter Expectancy Errors
46
Control Strategies: | Before & After
Pilot Study | Replication Study
47
Between-Subjects Design
D: an experimental research design in which separate groups of participants are being compared to determine the level of differential changes Groups are produced by random assignment, the groups are composed of different people, & the different groups are exposed to different levels of the independent variable Also known as Randomized Designs
48
Assumptions of Between-Subject Designs
Independent groups Comparable subjects in each group Random assignment & Matching can help with this Similar sample sizes in each group
49
Statistical Examples of Between-Subject Design Scenarios -ind t test
Differences exist in organizational skills between college students studying business versus fine arts. DV: organizational skills IV: college major (business, fine arts)
50
Statistical Examples of Between-Subject Design Scenarios -simple ANOVA
Women get asked out on a different number of dates based on whether they are blondes, brunettes, or red heads. DV: number of times asked out on date IV: hair color (blonde, brown, red)
51
Within-Subjects Designs
D: an experimental research design in which the same group of participants are tested repeatedly to determine the level of differential changes All research participants are members of all experimental conditions in the experiment Also known as Repeated Measures Designs
52
Varying Types of Within-Subject Designs | Temporal
used to determine whether participants are changing in a certain factor over time ex: do study skills get better with repeated sessions of tutoring and training
53
Varying Types of Within-Subject Designs | conditional
used to determine whether participants are diff in a certain factor across varying conditions ex: do students learn better in a hot classroom or a cold classroom? do people prefer white, red, or rose wine
54
Assumptions of Within-Subject Designs
Dependent groups All subjects present for all stages of research Learning & Maturation controlled for Counterbalancing & Time controls can help with this
55
Statistical Examples of Within-Subject Design Scenarios -dep ttest
Bowling scores will decrease from year one of playing to year two. DV: bowling scores IV: playing year (year one, year two)
56
Statistical Examples of Within-Subject Design Scenarios -repeated measures ANOVA
Pretest, posttest, and one-year follow-up scores on a behavioral observation measure will display an ongoing increase in productivity. DV: productivity measure IV: data collection time (pre, post, follow-up)
57
Mixed Model Design
D: an experimental design that continues the between subject and within subject design components Typically involves pretesting and posttesting both the control and treatment conditions to verify the absence of learning or maturation effects
58
Weak Experimental Designs
D: experimental designs that do not control well for extraneous variables and/or provide weak evidence of cause and effect ``` Between-Subjects Option: Posttest-Only Design with Nonequivalent Groups Within-Subjects Option: One-Group Pretest-Posttest Design Other Option (neither w/in or btw): One-Group Posttest-Only Design ```
59
Strong Experimental Designs
D:experimental designs that effectively control well for extraneous variables and provide strong evidence of cause and effect random assignment and comparable groups ``` Between Subject Options: Posttest-Only Control-Group Design Within Subject Option: Within-Subjects Posttest-Only Design Other Option: Pretest-Posttest Control-Group Design ```

Research Methods (3 decks)

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