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Research Methods 1 > RM1 Terminology > Flashcards

RM1 Terminology Flashcards

1
Q

Variable

A

A Characteristic or condition (piece of data) that changes or has different values for different individuals
(ex: weather, hair color, GPA)

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2
Q

Construct

A

An abstract attribute or characteristic that cannot be directly observed
(ex: Love, Anxiety, Prejudice)

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3
Q

Operational Definition

A

A description of the variable/ construct of interest in terms of a specific procedure (set of operations) for measuring an external, observable behavior

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4
Q

Categorical (nominal)

Variable

A

Type of variable that discrete factors that can only take on specific, mutually exclusive qualitative values
(ex: gender, color, political party)

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5
Q

Ordinal Variable

A

Type of variable that are categories organized in an ordered sequence terms of size or magnitude
(ex: years in school)

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6
Q

Continuous (quantitative) Variable

A

Type of variable that can be an interval scale with an absolute zero point (absence of variable), meaningful ratio
ex: height, weight, reaction time

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7
Q

Reliability

A

a key quality in a measure; the degree of consistency with which a test measures a variable/ construct.

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8
Q

Construct Validity

A

a key quality in a measure; the extent to which a test measures what is supposed to be measure

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9
Q

Test- Retest

A

Type of Reliability; When you give someone the same test multiple times, they should get about the same score each time

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10
Q

Interrater

A

Type of Reliability If you have two or more observers watching the same behavior, their measurements
should agree with each other

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11
Q

Internal Consistency

A

Type of Reliability; Within a test, people should respond similarly to questions that measure the
same construct

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12
Q

Descriptive Statistics

A

Organize, summarize, and communicate a group

of numerical observations

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13
Q

Inferential Statistics

A

Use sample data to make inferences about the
properties of the larger population or draw
principled conclusions about the differences
observed in descriptive data

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14
Q

Frequency Distribution

A

An organized tabulation of the number of individuals
located in each category on a scale of measurement
(ex: bar graph, JASP, histogram)

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15
Q

The Mean

A

A measure of Central Tendency that is found by adding
all the scores and dividing by the number of scores
*For continuous scales

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16
Q

The Median

A

A measure of Central Tendency; The middlemost
score, or score that divides the group in half
*For continuous and ordinal scales

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17
Q

The Mode

A

A measure of Central Tendency; Most frequently
occurring score
*For all scales, including nominal
scales

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18
Q

Range

A

A measure of Variability; Difference between highest and lowest scores

19
Q

Variance (s2 or σ2)

A

A measure of Variability; The average of

squared deviations from the mean

20
Q

Standard Deviation (s or σ or SD

A

A measure of Variability; The typical amount that each score varies (deviates) from the mean; the square root of the variance

21
Q

Null Hypothesis (H0)

A

The manipulation/ intervention has no effect. Any observed difference between population and sample
means is a result of sampling error

22
Q

Alternative Hypothesis (H1)

A

The manipulation/intervention has an effect. Any
observed difference between population and
sample means is statistically significant

23
Q

Steps in Hypothesis Testing

A 
Step 1: Set up hypotheses
Step 2: Compute test statistic
Step 3: Find critical values
Step 4: Compare test statistic to critical value
Step 5: Interpret results
24
Q

What is the p-value?

A

The probability that we would see if the sample mean if the null hypothesis is actually true
if this value is less than alpha (<0.05) then we reject the null and conclude there is a statistically significant effect in the study: the evidence tends to support the Alternative

25
Q

Type 1 Error

A

False Positive; where we reject the null, stating there was an effect, when in reality there was not an effect.
less common

26
Q

Type 2 Error

A

False Negative; where we retain the null, thinking there was no effect, when in reality there was actually an effect

27
Q

Effect Size

A

A measure of the absolute magnitude of a treatment effect, independent of the size of the sample(s) being used.

28
Q

Extraneous Variable

A

Any other variables in your study. For example, Participant/Subject variables are the characteristics (demographics) of the participants in the study (age, ethnicity)
Types: Environmental, participant, and time related variables

29
Q

Confounding Variables

A

Extraneous variable that influences responses on the DV and vary systematically with the IV.

30
Q

Between- Subjects Design

A

Research design that has participants experience one, and only one, level of the independent variable. Requires multiple independent groups of participants
AKA independent groups design.

31
Q

Between- Subjects Design: Advantages and Disadvantages

A 
Advantages:
- Each score is independent of
other scores
• Participants less likely to figure
out the purpose of the study
(fewer demand characteristics)
• Useful for any research
comparing treatment groups
Disadvantages:
• Lower power = requires
many participants
• Individual differences
across groups (extraneous
variables) may result in:
– Confounding variables
– Can result in highly variable
scores
32
Q

Within- Subjects Design

A

Research design that The different levels of the independent variable are experienced by all participants in the study. Requires just one group of participants (AKA repeated-measures
design)

33
Q

Within- Subjects Design: Advantages and Disadvantages

A 
Advantages:
-Participants serve as their
own controls, which
eliminates variance due
to individual differences
• More efficient: Fewer
participants needed, and
more sensitivity/power to
detect differences 
Disadvantages:
-Carryover Effects: changes in behavior
or performance caused by the lingering
after-effects of an earlier treatment
condition (an order effect)
• Practice effects: influence on
performance that arises from practicing
a task
• Demand characteristics: An
experimental artifact that allows
participants to form an interpretation of
the experiment's purpose (and
unconsciously change their behavior to
fit that interpretation)
34
Q

Quasi-Experimental Design

A

Type of research design where there are attempts
to minimize threats to internal validity, but because
of the variables under consideration, full control and
manipulation (e.g. random assignment) is impossible
- variables cannot be manipulated practically or ethically (ex gender, ethnicity, exposure to language)

35
Q

Analysis of Variance (ANOVA)

A

Tests claims about mean differences between
two or more populations by using two or more
samples
• The tested hypothesis is very similar to the t-statistic,
but now can be applied when we have
more than two groups
- 3 hypothesis: Main Effect of A, Main Effect of B, and an Interaction

36
Q

Post Hoc Tests

A

Additional statistical tests that are done
after finding a significant F-value to determine exactly
which groups are significantly different from one another
• Developed to control for increases in Type I error
associated with running multiple statistical tests

  • Turkey, Scheffe and Bonferroni
37
Q

One-way ANOVA

A

Type of ANOVA, Tests differences in means
when you have one categorical, between-subjects
IV with at least 2 levels

38
Q

Repeated Measures ANOVA

A

Type of ANOVA, Used when your categorical IV is manipulated within-subjects

39
Q

Two-way (factorial) ANOVA

A

Type of ANOVA, Used when you have multiple IVs, each with 2 or more levels
ex: Gender (Male vs Female) x Sexuality (Straight vs Gay)

40
Q

Chi-square Test for Goodness of Fit

A

Uses frequency data from a sample to test hypotheses about the shape or proportions of a population distribution (as opposed to claims about parameters like means)

41
Q

The Chi-square Test of Independence

A

Uses the frequency data from a sample to evaluate the

relationship between two variables in the population

42
Q

Standard Error

A

the standard deviation of the sampling distribution of a statistic

43
Q

Correlation

A

Type of research that looks at relationships between continuous variables

Research Methods 1 (1 decks)

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