chapter 3/week 3

Question 1

what do you start with first in the research process

Answer 1

research question
(concise, specific, and testable question)

Question 2

variables

Answer 2

Concepts are converted into variables by translating or mapping them into a set of values

In experimental language there are dependent (DV) and independent (IV) variables

Question 3

DV

Answer 3

The variable that serves as our primary focus, that we’re trying to describe, predict, or explain, is the dependent variable – denoted by “y”

Question 4

IV

Answer 4

The variable that serves as a predictor or hypothesized cause (the variable we manipulate in an experiment) is called an independent variable, denoted by “x”

Question 5

variables w regression type models

Answer 5

In correlational language with regression type models we label IV “predictor variable” and DV “outcome or criterion variable”

Predictors are not independent variables because they do not cause a change in the outcome variables but they can help us explain some off the variance in the outcome variable

Question 6

Operational Definitions
How do you measure it?

Answer 6

Precisely how the concept is measured or manipulated in a study
Concrete, situation-specific, observable terms
Specificity of the construct help us better communicate what we mean in scientific communication and replication

We can operationally define a concept in many different ways

Question 7

Measures used in behavioral research:

Answer 7

Observational measures
Physiological measures
Self-report measures

Question 8

Observational measures

Answer 8

Involve the direct observation of behavior

Researchers can either directly observe or use audio and video recordings

Ex: depression – facial affect; content analysis of speech patterns

Question 9

Self report measures

Answer 9

Involve people’s replies to questionnaires and interviews

Can measure:
Thoughts (cognitive self-reports)
Feelings (affective self-reports)
Actions (behavioral self-reports)

Question 10

Physiological and Neuroscientific measures

Answer 10

Involve the measurement of internal processes that are not directly observable
Involves the use of specialized equipment to measure heart rate, brain activity, hormonal changes, and other responses

Ex: depression – laterality of EEG brain wave activity

Question 11

Psychometrics

Answer 11

the field devoted to the study of psychological measurement

Question 12

Converging operations

Answer 12

using several measurement approaches to measure a particular variable

Question 13

Scales of Measurement definition

Answer 13

properties of a measure that reflect the degree to which scores obtained on that measure reflect the characteristics of real numbers

Question 14

Scales of Measurement list

Answer 14

scales:

nominal
ordinal
interval
ratio

Question 15

variable breakdown

Answer 15

variable –> qualitative –> nominal or ordinal

variable –> quantitative –> interval or ratio

Question 16

nominal scale

Answer 16

the numbers that are assigned to participants’ behaviors or characteristics are essentially labels

Categorical variable

Qualitative classification

No mathematical operations

Pie chart used

Example:
Gender, marital status, blood type, favorite color, nationality

Question 17

ordinal scale

Answer 17

involves the rank ordering of a set of scores that reflect participants’ behaviors or characteristics

The rank ordering of people’s behaviors or characteristics

The intervals between the ranks are not necessarily equal

No mathematical operations

Example:
Educational level, olympic medals, pain scale, movie reviews

Question 18

interval scale

Answer 18

type where a smallest value does not exist, 0 is not possible, or 0 does not represent absence of quantity measure

1. Equal differences: the differences between any two consecutive values is the same
2. No true zero point: zero does not mean “none”

Addition and subtractions allowed, but you cannot multiply or divide

Example:
IQ scores, SAT scores, temperature

Question 19

ratio scale

Answer 19

involves real numbers that can be added, subtracted, multiplied, and divided; Type where 0 is the smallest meaningful value, 0 can be attained, and 0 represents absence of what is being measured

1. Most advanced level of measurement: intervals are equal
2. There is a true zero point: zero means zero

All mathematical operations are allowed

Example:
Weight, number of errors in a test, annual income, scores in a game

Question 20

Importance of scales of measurement

Answer 20

Determines the amount of information provided by a particular measure

Involves the kinds of statistical analyses that can be performed on the data

Question 21

Measurement Error
equation

Answer 21

Observed score = true score + measurement error

Question 22

observed score

Answer 22

score you found in your study/research/with your conditions

Question 23

true score

Answer 23

the score that the participant would have obtained if the measure were perfect and were able to measure without error

Question 24

measurement error

Answer 24

factors that distort the true score

Question 25

Scores of Measurement Error

Answer 25

1. participant transient states 2. participant stable attributes 3. situational factors 4. characteristics of the measure 5. data entry error

Question 26

Participant Transient States

Answer 26

Temporary, unstable state of the participant The participant may be in a bad day, with a bad mood, health, tired, or just anxious at the time of the measurement

Question 27

Participant Stable Attributes

Answer 27

Enduring traits of the participant, such as illiteracy, paranoia, or oppositional personality

Question 28

Situational Factors

Answer 28

Characteristics of the researcher or the lab, time, and conditions of the place

Question 29

Characteristics of the Measure

Answer 29

Measurement fatigue – long difficult, or painful measures

Question 30

Data entry error

Answer 30

Mistakes in recording a participant’s score

Question 31

Ways to Decrease Measurement Error

Answer 31

reliability validity

Question 32

total variance equation

Answer 32

Total variance = true-score variance + error variance

Question 33

reliability

Answer 33

the consistency or dependability of the measure the proportion of the total variance that is associated with participants’ true scores Reliability = true-score variance / total variance

Question 34

Assessing Reliability

Answer 34

Researchers estimate reliability by assessing the extent to which two or more measurement of the same behavior, object, or even yield similar scores Most common ways to measure reliability: Test-retest reliability Inter-item reliability (internal consistency) Inter-rater reliability

Question 35

Correlation Coefficients

Answer 35

Researchers usually use a correlation coefficient to make those estimates Correlation coefficient – expresses the strength of the relationship between two measures - Can range from -1.00 to +1.00 - Correlation of .00 indicates no relationship between the variables The sign indicates whether the relationship between the variables is positive or negative (inverse)

Question 36

Test-Retest Reliability

Answer 36

consistency of participants’ responses on a measure Administer measure on two separate occasions Exampline the correlation between the scores obtained on the two occasions Correlation > 0.70 indicates acceptable reliability Useful only if the attribute being measured should not change over time

Question 37

Inter-item reliability

Answer 37

assesses the degree of consistency among the items on a scale Tells us whether all of the items on a scale are measuring the same thing. If not, summing scores across all the items creates measurement error and lowers reliability indices of it: - item-total correlation - split-half reliability - cronbach's alpha coefficient (α)

Question 38

Item-total correlation

Answer 38

the correlation between a particular item and the sum of all the other items on the scale

Question 39

Split-half reliability

Answer 39

divide the items on a scale into two sets and examine the correlation between the set

Question 40

Cronbach’s alpha coefficient (α)

Answer 40

equivalent to the average of all possible split half reliabilities - Most frequently used - Adequate inter item reliability if α exceeds 0.70 - .85 – ideal

Question 41

Inter-rater Reliability

Answer 41

the consistency among two or more researchers who observe and record participants’ behavior Examine the degree of agreement among two or more people who observe and record participants' behavior

Question 42

Ways of increasing the reliability of behavioral measure:

Answer 42

Standardize administration of the measure Clarify instructions and questions Train observers Minimize errors in coding and entering data

Question 43

validity

Answer 43

accuracy of what the measure is supposed to measure (goals) the degree to which a measurement procedure actually measures what it is intended to measure rather than measuring something else (or nothing at all) To what extent does the variability in scores on the measure reflect variability in the characteristic or behavior we are trying to assess? ex: Face validity, construct validity, convergent validity, discriminant validity, criterion-validity, concurrent validity, predictive validity

Question 44

validity chart

Answer 44

validity --> face validity and construct validity contract validity --> convergent validiity and discriminant validity and criterion-validity criterion-validity --> concurrent validity and predictive validity

Question 45

face validity

Answer 45

the extent to which a measure appears to assess what it’s supposed to capture - Just because something has face validity doesn’t mean that is valid - Many measures without face validity are valid - Some measurements are designed to lack face validity so as to disguise the purpose of the test

Question 46

construct validity

Answer 46

the extent to which a measure of a hypothetical construct relates as it should to other measures Hypothetical constructs

Question 47

Hypothetical constructs

Answer 47

entities that cannot be directly observed but are inferred on the basis of empirical evidence Ex: Intelligence, motivation, self-esteem, attachment style

Question 48

3 ways to Assess Construct Validity

Answer 48

convergent (or divergent) validity discriminant validity criterion-related validity

Question 49

Convergent (or divergent) Validity

Answer 49

a measure correlates with other measures that it should correlate with Embarrassability should be positively correlated with shyness but negatively correlated with self-confidence

Question 50

discriminant validity

Answer 50

a measure does NOT correlate with other measures that it should not correlate with Embarrassability should not correlate with IQ

Question 51

criterion related validity

Answer 51

the extent to which a measure allows us to distinguish among participants on the basis of a particular behavioral criterion Researchers examine whether behavioral outcomes are related to scores on the measure as expected

Question 52

Two Forms of Criterion-Related Validity

Answer 52

concurrent validity predictive validity

Question 53

concurrent validity

Answer 53

scores on a measure are related as expected to a criterion that is assessed at the time the measure is administered Example: an embarrassability scale (administered today) predicts stage fright in the current situation

Question 54

predictive validity

Answer 54

scores on a measure are related as expected to a criterion that is assessed in the future Example: an embarrassability scale (administered today) predicts whether students sign-up for public speaking classes next semester

Question 55

Test bias

Answer 55

occurs when a particular measure is not equally valid for everyone - The question is no whether various groups score differently on the test - Rather, test bias is present when the validity of a measure is slower for some groups than for others