Psy-test & Ass-ch 3

Question 1

What are descriptive statistics

Answer 1

Organising and summarising datas using numbers and graphs

Data summary
Bar graph, histogram, pic chart and et.
Shape of graph and Skegness

Measures of central tendency
Mean -median-mode

Measures of variability
Range, variance, standard deviation

Question 2

Inferential statistics

Answer 2

Using sample data to make an inference to draw a conclusion of the population

Use probability to determine how confident we can be that the conclusions we make are correct. ( confidence intervals and margins of error
Conclusion are deduced from dataset
How are things (abilities, traits) are related to one another ( e.g test scores, behaviour, success)

Question 3

Coefficient of correlation

Answer 3

Is central to testing and measurement.

Determines the strength of the relationship between two things (variables)

Question 4

The correlation coefficient

Answer 4

Reflects relationship between two variables

Question 5

Ranges of the correlation coefficient

Answer 5

-1 strongly negative
0
+1 strongly positive

0. 4 weak
1. -0.6 moderate
2. 7 strong correlation
3. 0 perfect

Doesn’t imply cause

Question 6

Give a basic Definition of Reliability in Psychometrics

Answer 6

Consistency in Measurement. (Not necessarily good or bad).

Question 7

How does Context influence reliability?

Answer 7

A test may be reliable in one context, but not another

Question 8

What is a Reliability Coefficient?

Answer 8

A reliability coefficient is an index of reliability, a proportion that indicates the ratio between the true score variance on a test and the total variance.

Question 9

How can we represent the concept of reliability in an equation?

Answer 9

X = T + E
Where X is the score
T is the true score
E is error

Question 10

What is the Variance?

Answer 10

Variance is the Standard Deviation Squared and can be broken down into components: total variance, true variance & error variance.

Question 11

What is true variance?

Answer 11

Variance from true difference is true variance. True differences are assumed to be stable, to yeild consistent scores on repeated administrations of the same test as well as on equivalent forms of test

Question 12

What is error variance?

Answer 12

Error Variance is Variance from irrelevant, random sources.. BEcause error variance may increase or decrease a test score by varying amounts, consistency of the test score, and thus reliability, can be affected.

Question 13

How does a systematic source of error influence variability?

Answer 13

A Systematic source of error would not effect consistency, it does not change the variability of the distribution or affect reliability.

Question 14

List the possible sources of Error Variance

Answer 14

The possible sources of error variance are:
Test construction, 
Test Administration,
Test Scoring & Interpretation,
Other sources of error also exist.

Question 15

How can test construction influence error variance?

Answer 15

Test construction influences the extent to which a testtaker’s score is affected by the content sampled on the test and by the way in which the item is constructed.

Question 16

What is item sampling or content sampling in relation to error variance?

Answer 16

Item sampling or Content Sampling refers to the variation among items within a test as well as to variation among items between tests.

Question 17

What is one of the key challenges faced by test developers in relation to test construction?

Answer 17

A challenge in test development is to maximise the proportion of the total variance that is true variance and to minimise the proportion of the total variance that is error variance.

Question 18

How can Test Administration influence Error Variance?

Answer 18

Sources of error variance that occur during test administration may influence the testtaker’s attention or motivation.

Question 19

What are some examples of factors that can have untoward influence during test administration?

Answer 19

Factors that can influence test administration include:
Test Environment (i.e. room temperature, lighting, ventilation noise),
Testtaker variables (emotional problems, physical discomfort, drug/medication effects, lack of sleep);
Examiner-related variables (physical appearance & demeanor, presence or absence of examiner, departure from the prescribed procedure, providing non--verbal cues in oral exams).

Question 20

How can Test Scoring & Interpretation become a source of error variance?

Answer 20

If subjectivity is involved in scoring (e.g. in the case of nonobjective-type personality tests, tests of creativity, essay tests), then the scorer can be a score of error variance.

Question 21

How can problems in scoring agreement be addressed to reduce error variance?

Answer 21

Problems in scoring agreement can be addressed through rigorous training designed to make the consistency, or reliability, of various scores as nearly perfect as can be.

Question 22

Reliability

Answer 22

Consistency in measurement; only refers to something that is consistent (not necessarily consistently good or bad-just consistent)

• different types of degrees of reliability
• the proportion of the total variance attributed to true variance

Question 23

Reliability Coefficient

Answer 23

in an index of reliability, a proportion that indicates the ratio between the true score variance on a test and the total variance

Question 24

Observed score

Answer 24

Observed Score (X) = True Score (T) + Error (E)

X = T + E

Question 25

Error

Answer 25

refers to the component of the observed score that does not have to do with the testtaker’s true ability or trait being measured

Question 26

Variance

Answer 26

• statistic useful in describing sources of test score variability
• the standard deviation squared
• Variance is broken into 2 components: true variance and error variance
• Variance equals true variance plus Error variance,

Question 27

Standard deviation

Answer 27

equal to the square root of the averaged squared deviations about the mean; a measure of variability equal to the square root of variance

Question 28

True variance

Answer 28

Arian will from true differences

Question 29

Error variance

Answer 29

variance from irrelevant random sources

Question 30

Total variance

Answer 30

the total variance in an observed distribution (a2) equals the sum of the true variance (a2th) plus the error variance (a2e)

a2 = a2th + a2e

Question 31

Measurement error

Answer 31

all of the factors associated with the process of measuring some variable, other than the variable being measured
-categorized as either random or systematicl

Question 32

Random error

Answer 32

a source of error in measuring a targeted variable caused by unpredictable fluctuations and inconsistencies of other variables in the measurement process (ex: noise)..

Question 33

Systematic error

Answer 33

Systematic error, “. .

Question 34

Systematic error

Answer 34

a source of error in measuring a variable that is typically constant or proportionate to what is presumed to be the true value of the variable being measured

Question 35

Sources of error variance.

Answer 35

• test construction
• test administration
• test scoring and interpretation

Question 36

Test construction source of error variance

Answer 36

variation may consist within items on a test or between tests

Question 37

Test Scoring and Interpretation Source of Error Variance

Answer 37

• computer testing reduces error in test scoring
• many tests still require expert interpretation (ex: projective tests)
• subjectivity in scoring can enter into behavioral assessment

Question 38

Other sources of error

Answer 38

• surveys and polls (contain disclaimer as to the margin of error associated w/ findings)
• sampling error
• methodological error

Question 39

Sampling error

Answer 39

the extent to which the population of voters in the study actually was representative of voters in the election

Question 40

Exploratory data analysis

Answer 40

It is the first part of your data ,l

Involves things like : establishing the data’s under structure, identifying mistakes and missing data, establishing the key variables, spotting anomalies, checking assumptions, testing hypothesis in relation in specific model..