Unit 1 Flashcards
1
Q
what kind of process is the experimental method?
A
a research process that involves following scientific guidelines to test hypotheses and establish causal relationships between variables
2
Q
what are the 3 kind of variables?
A
- Independent variable
- Dependent variable
- Extraneous and confounding variable
3
Q
what are the main advantages of the experimental method?
A
- give researchers a high level of control
- standardised procedures, experiments can be replicated, and their reliability can be tested
- allows cause and effect relationships to be determined
- the conclusions of these experiments allow useful applications to the real world
4
Q
what is manipulation?
A
something is purposefully changed by the researcher in the environment
5
Q
what is control used to?
A
to prevent outside factors from influencing the study outcome
6
Q
what makes us more confident that the manipulation caused the outcome?
A
when something is manipulated and controlled and then the outcome happens
7
Q
what does random assignment mean?
A
that if there are groups or treatments in the experiment, participants are assigned to these groups or treatments, or randomly
-> flip of a coin
8
Q
what does random assignment mean un terms of equality?
A
no matter who the participant is, he/she has an equal chance of getting into all of the groups or treatments in an experiment
9
Q
what does the process of random assignment ensure?
A
that the groups or treatments are similar at the beginning of the study
-> more confidence that the manipulation “caused” the outcome
10
Q
what is required in order to determine cause and effect?
A
there must be at least two groups to compare the experimental group and the control group (experimental conditions)
11
Q
what allows the researcher to see how much of an impactthe intervention had on the participants?
A
Comparing the experimental group to the control group
12
Q
What are confounding variables?
A
Unknown, uncontrolled variables that interfere with the relationship between the independent and dependent variable
13
Q
Why are confounding variables problematic?
A
They can falsely suggest a cause-and-effect relationship or hide a real one
14
Q
How can you control for confounding variables?
A
Through random assignment, matching, or statistical control
15
Q
What is Type I error?
A
A false positive – concluding an effect exists when it doesn’t
16
Q
What is a type II error?
A
A false negative – failing to detect an effect that actually exists
17
Q
How can you reduce Type I and Type II errors?
A
By increasing sample size and using appropriate significance levels
18
Q
What is temporal sequencing?
A
X must come before Y to establish a cause-and-effect relationship
-> important to prove that cause happens before the effect
19
Q
What is a non-spurious relationship?
A
relationship between X and Y cannot occur by chance alone and must be genuine
-> ensured by controlling confounding variables and ensuring the observed effect is not due to coincidence
20
Q
What does it mean to eliminate alternate causes?
A
ensuring no other variables are responsible for the relationship between X and Y
-> by using control groups, random assignment, and statistical controls
21
Q
What are uncontrolled variables?
A
alternative explanations for your results
-> effect the reliability of your arguments
22
Q
How can research make a definitive statement about the ffects of the treatment upon the dependent variable?
A
by eliminating the effects of confounding variables
23
Q
When does differential influence occur?
A
when the influence of an extraneous variable is different for the various comparison groups
e.g. if one group mainly females and other mainly males - gender can gave differential effect on outcome
24
Q
When is differential influence unlikely to occur?
A
if the comparison groups are the same on al lextraneous variables at the start of the experiment
25
What do we want groups to be in experiments?
the same or "equivalent"
26
What do we want the only systematic difference between the groups in an experiment to be?
the variation of the independent variable
27
What is the total variance?
variability in the measurement of the dependent variable
-> due to influence of IV, extraneous variables and random factors
28
What are the two components of total variance?
- systematic variance: primary and secondary
- error variance
29
# total variance
What does systematic variance represents?
the portion of total variance that is related to the variables under study and can be predicted by the researcher
-> variability in participant's behavior measured
30
What does systematic variance includes?
variance associated with
- the independent variable (primary systematic variance)
- predictable extraneous variables (secondary systematic variance)
31
What is the primary systematic variance?
the independent variable
32
What is the secondary systematic variance?
predictable extraneous variables
33
What does secondary systematic variance refer to?
to the portion of variance in the participants heart rate for example that is attributable to other predictable factors aside from the manipulation of the IV
-> may arise from factors such as age, gender, fitness level, underlying health conditions
34
How do secondary systematic variances influence the outcomes of a study?
not directly manipulated by the researcher but may still systematically influence the outcome through other variables
35
What does error variance represent?
the portion of total variance that cannot be explained by the variables under study or by systematic factors
-> includes random fluctuations and measurement errors that are inherent in any research study
36
What does error variance includes?
sources of variability such as measurement error, individual differences among participants, uncontrolled environmental factores and so on
37
What will all the variance in the DV (total variance) be caused by in an ideal situation?
the single variable we are interested in studying, the IV
-> this variance is called primary systematic variance, caused by the IV
38
How possible is it for the primary systematic variance to equal the total in real life?
almost impossible
39
What does the researcher aim to achieve in a real situation?
that the proportion of secondary systematic and error variance is appropriate for the purposes being pursued
40
What principle does the researcher follow when designing an experiment?
the MAX-MIN-CON principle
41
What is the perfect experiment and what is the real-life experiment like?
- perfect experiment: total variance = treatment variance
- real-life experiment: total variance = treatment variance + confound variance + error variance
42
What is the MAX-MIN-CON principle about?
* MAXimizing the systematic or desirable variance,
* MINimizing the error variance
* CONtrolling the effect of the extraneous variables.
43
What should the researcher do to maximize experimental variance?
should make experimental conditions as different as possible
44
What values should we focus on according to the objectives of the research?
the values of the independent variable:
- extreme values: refer to the minimum and maximum values of a given characteristic
- intermediate values: having three different groups refer to the range of values between its minimum and maximum levels in an experimental study
45
What does Maximizing the systematic or desirable variance involve?
reducing the variability in the measurement of the DV that is not attributable to the IV or other controlled factors
46
What are 4 of the strategies to maximize the systematic or desirable variance and therefore minimize error variance?
- Standardized testing
- Random Assignment
- Counterbalancing
- Reliable Measurement Tools
47
What is ensured in Standardized Testing?
That all participants have same standardized conditions
48
What is Counterbalancing?
if study involves multiple conditions or repeated measures, counterbalancing the order of presentation --> can help minimize order effects and other sources of variability unrelated to IV
49
What does it mean to use reliable measurement tools?
using reliable and valid measurement instruments for assessing the dependent variable
-> can help reduce measurement error
50
What does it mean to CONtrole the effect of the extraneous variables?
extraneous variables can potentially affect DV
-> controlling for extraneous values involves taking steps to either eliminate their influence or hold them constant across experimental conditions
51
What are 2 ways to CONtrole the effect of extraneous variables?
- Matching
- Holding Variables Constant
52
What is Matching?
Matching participants on relevant characteristics BEFORE assigning them to experimental conditions
-> balances extraneous variables
53
What does it mean to hold variables constant?
may involve controlling environmental conditions, using standardized procedures or providing consistent instructions to participants
-> ensures that they do not vary systematically and confound the results
54
What are common techniques to betweengroups and withingroups strategies?
Elimination, Constancy, single-blind and double-blind, systematization of extraneous variables and statistical control
55
What is the difference between Within-group and Between-group?
- Within: Everybody (repeated measures)
- Between: Comparison BETWEEN groups
56
What does Elimination involve?
removing or excluding certain variables or conditions from study to isolate the effects of IV on DV
57
What is Elimination useful for?
controlling environmental values
e.g. eliminating ambient noise by soundproofing laboratory
58
What does Constancy mean?
keeping extraneous variables constant to ensure that they do not vary or change during the course of the research
59
What is a single-blind study?
participants are unaware of the objectives and experimental condition
-> we control the expectatives of the subject
60
What is a Double-blind study?
neither participants nor researchers know experimental condition
-> we control the expecatives of the subject and experimenter
61
What is systematization of extraneous variables?
experimenter turns an extraneous variable into an IV
62
# Statistical control
what is Partial correlation?
statistical technique used to measure the relationship between two variables while controlling for the influence of one or more additional variables
-> known as covariates
63
# Statistical control
What is the Analysis of Covariance?
ANCOVA is a statistical techique used to compare group means while statistically controlling for the effects of one or more additional variables
64
Which control technique do we use for between or groups comparison situations?
Balancing
65
What process does Balancing refer to?
process of ensuring that the groups being compared are similar or equivalent with respect to certain characteristics or variables that could potentially influence the outcome of the study
66
What is matching in control techniques?
Matching involves pairing participants in different groups based on specific characteristics (e.g., age, gender, socioeconomic status) to reduce potential confounding effects and create comparable groups
67
How is matching used in experimental design?
Participants are matched based on a key variable (e.g., baseline scores)
68
What is blocking in control techniques?
Blocking involves grouping participants into homogeneous subsets (blocks) based on a block variable (e.g., weight, proficiency level) before randomly assigning them to treatment conditions
69
How do blocking and matching differ in grouping participants?
- Blocking: Groups all participants who share a characteristic into the same block.
- Matching: Creates pairs of participants who share the same characteristic.
- Key Difference: In blocking, all with a shared trait are grouped together, while matching forms n/2 pairs.
70
What are 2 control techniques for withingroup situations?
| (INTRA-NET)
- subject as their own control
- counterbalancing
71
What is subject as their own control within groups?
participants are exposed to different conditions or treatments and their responses are measured across these conditions
72
What does Counterbalancing involve and what are the steps?
involves systematically varying the order in which different conditions or treatments are administered to participants
-> each condition presented as an equal number of times
-> types: wihin subject and intragroup
73
# Counterbalancing
what are all participants in a within-subject design exposed to?
the same treatments
-> goal is to measure changes over time or changes resulting from different treatments for outcomes such as attitudes, learning or performance
74
What can we divide the DV into?
Univariable and Multivariable
75
What can we divide the IV into?
Unifactorial and Multifactoral
76
what is an unifactorial design?
A research design that focuses on only one Independent Variable (IV) to see its effect on the Dependent Variable (DV).
e.g. Studying how caffeine (IV) affects concentration (DV).
77
What can unifactorial design between groups be divided into?
- randomized group design:
1. two groups desing
2. multigroup design
- randomized balance design:
1. random block design
2. random match design
78
What can the unifactorial design within groups be divided into?
- 2 measures on DV
- K measure design
79
What is a Two Groups Design Post Treatment Measure?
a research design where two groups are compared after one group receives a treatment and only one measurement is taken afterward
80
What is a Two Groups Design with Pre and Post Measure?
It is a research design where measurements are taken before and after the treatment for both the Experimental Group and the Control Group to observe changes over time
81
What is the first step in a Two Groups Design with Pre- and Post-Measurement?
Selection of a sample (preferably random) that is large enough for chance to take effect
82
Why is random assignment important in this design?
to ensure that the two groups are truly equivalent before the treatment, minimizing bias
83
What is the purpose of pre-treatment measurement?
To verify that both groups are truly equivalent before the treatment is applied
84
What is measured in a Two Groups Design with Pre- and Post-Measurement?
The behavior of subjects in both groups before and after the treatment
85
# Two Groups Design with Pre- and Post-Measurement
What comparisons are made in this design?
- Pre-treatment measurements of each group to check equivalence.
- Pre- and post-treatment measurements within each group to assess the effect.
- Post-treatment measurements between groups to test the hypothesis
86
# Two Groups Design with Pre- and Post-Measurement
How are the results analyzed in this design?
By comparing the data from both groups using the most appropriate statistical methods
87
How do you check that the groups' measures are equivalent in a Two Groups Design with Pre- and Post-Measurement?
By comparing the pre-treatment means of the dependent variable (DV) for both groups using the appropriate statistical analysis
88
# two groups with pre and post treatment
What happens if you find differences in the pre-treatment means?
You can apply blocking (to control for these differences), use ANCOVA (Analysis of Covariance) to adjust for initial differences, or create pairs of participants with similar pre-treatment scores for more accurate comparisons
89
What is a Multigroup Design?
It is a research design with one independent variable (IV) that has more than two conditions, meaning at least three groups or more are compared
90
How many conditions does a multigroup need?
at least 3
91
What happens when the population of an experiment is very heterogeneous or the availability is too small?
random assignment is an insufficient control procedure to ensure the initial equivalence of the groups
92
What is recommended in moments when there is a suspected extraneous variable that may influence the dependent variabe?
to use the homogenous block technique or the blocking technique instead of random assignment when forming the groups
93
What is the difference between Blocking and Matching?
Assignment
94
How do we employ a within group unifactoral?
- one group who receives all the levels of IV on a sequential pattern
- two experimental conditions
- measures as a comparison to test the effectivity of the treatment
95
What are the differneces between balancing and counterbalancing?
- Balancing focuses on equalizing participant characteristics (Sample).
- Counterbalancing focuses on managing sequence effects (Treatment order).
96
What is Complete Counterbalancing?
Every possible order of conditions is tested (n! combinations)
97
What is Incomplete Counterbalancing?
Only a subset of possible orders is used, often in a Latin Square design
98
When should you use Incomplete Counterbalancing?
When too many conditions make complete counterbalancing impractical
99
What is the Latin Square design in counterbalancing?
A method where each condition appears in each position exactly once, ensuring balance without testing all possible orders
