Ch3

Question 1

The degree of differences within a set of test scores or among the values of a psychological attribute

Answer 1

Variability

Question 2

Psychology is about variability in the behaviour of individuals

Answer 2

True

Question 3

The behavioural sciences are largely about understanding differences among people, including differences among people in different groups or differences among people in different conditions

Answer 3

True

Question 4

Variability is at the heart of research on the application of research in the behavioural sciences

Answer 4

True

Question 5

Individual differences are also fundamental to psychological measurement. As described earlier measurement is based on the simple, but crucial assumption that psychological differences exist, and can be detected through well design measurement processes.

Answer 5

True

Question 6

The existence and detection of individual differences lie at the heart of test, construction and test evaluation. Psychometric concepts, such as reliability and validity are entirely dependent on the ability to quantify the differences among people

Answer 6

True

Question 7

All research in psychology and all scientific applications of psychology depend on the ability to measure individual differences

Answer 7

True

Question 8

To quantify psychological differences, we begin by assuming that scores on a psychological test or measure will ( or at least can) vary from person to person or from time to time.

Answer 8

True

Question 9

Then, taken from a group of people or a different points in time from the same individuals, instead of test, scores is called a “distribution of scores.”

Answer 9

True

Question 10

A key element in most behavioural research is to quantify precisely the amount of the variability within a distribution of scores

Answer 10

True

Question 11

Variance is a statistical way of quantifying, variability or individual differences in a distribution or set of scores.

Answer 11

True

Question 12

Covariance is a way of quantifying the connection between variability in one set of scores and variability in another set of scores

Answer 12

True

Question 13

Many fundamental concepts in psychological measurement, emerge from the detection and description of distributions of test scores

Answer 13

True

Question 14

The most basic facet of a distribution of scores is “central tendency”

Answer 14

What is the “typical” score in the distribution or what is the score that is most representative of the entire distribution? Mean is the most common

Question 15

The arithmetic “mean” represents the “typical” score in a distribution of scores.

Question 16

Measurement rests on the concept of variability

Answer 16

If our measures are to be useful than they need to be sensitive to psychological viability ( they must reflect the differences in people’s standing on a psychological attribute)

Question 17

We must be able to quantify the variability within a distribution of scores

Question 18

The variance and the standard deviation reflect variability as the degree to which the scores in distribution deviate from the mean of the distribution

Question 19

The numerator of the variance is sometimes called the sum of a squared deviations about the mean.

Answer 19

Sum of squares

Question 20

As an index of variability, the standard deviation has the advantage of reflecting variability in terms of squared deviation scores.

Question 21

The variance and standard deviation are fundamental elements of many psychometric concepts. Their interpretation is not always clear.

Question 22

The size of the variance and consequently the size of the standard deviation is determined by two factors

Answer 22

1. The degree to which the scores in a distribution differ from each other‘s.
2. The metric of the scores in the distribution.

Question 23

The dramatic difference in the two variances arises largely because of the dramatic difference in the metrics of the two sets of a scores

Question 24

Considering the nature of variance and the factors that affect its size, there are four factors to consider when interpreting a variance or standard deviation

Answer 24

Neither one can ever be less than zero

Question 25

At a minimum they can be zero, which indicates that the score is in the distribution do not vary at all

Question 26

Mathematically and conceptually it is impossible to have a negative variance or standard deviation

Question 27

There is no simple way to interpret a variance or standard deviation as large or small

Question 28

The variance of a distribution of scores is most interpretable and meaningful when it is put into some kind of context

Question 29

The distribution with the larger variance has a greater the liability, then the distribution with a smaller variance

Answer 29

True

Question 30

The importance of variance and standard deviation lies, mainly in their effects on other values that are more directly interpretable

Answer 30

The variance and standard deviation or fundamental components of many psychoment concepts and procedures , for example, variance and standard deviation are key to concepts, such as the correlation, coefficient, the reliability, coefficient, confidence, intervals, and test bias

Question 31

It distributions shape can be quantified in terms of its amount of skew.

Answer 31

True

Question 32

Perfectly symmetrical distribution has a skew value of 0

Answer 32

True

Question 33

Asymmetrical or “skewed distributions” have skew values below or above 0.

Question 34

Distributions with relatively few values above the mean are “positively skewed” and have skew values greater than 0.

Question 35

Distributions with relatively view values below the mean are ”negatively skewed” and have skew values below 0.

Question 36

The more dramatically skewed or asymmetric a distribution is the larger it’s skew value will be (above or below 0).

Question 37

Positive or direct association

Answer 37

High score in both variables

Question 38

We are looking for two types of information:
Association between two variables ( between two distributions of scores)

Answer 38

1. The direction of the association ( do people who Upton relatively high scores on one variable tend to obtain relatively high scores on the other?) if so, then, we say that the two variables have a positive or direct association.
   However, if people who obtain relatively high scores on one variable tend to obtain relatively the lowest scores, on the other, we say the two variables, have a negative or inverse association.

Question 39

Contd- Type of information that even like to know about the association between two variables

Answer 39

2. The magnitude of the association.
   Are two variables, very strongy associated, or only the weekly associated

Question 40

Strong associations either positive or negative indicate a high level of consistency between two variables week associations indicate inconsistency.

Question 41

A scatterplot represents the association between two variables, in terms of an upward or downward trend of points

Answer 41

And upward trend (going from lower left to upper right) indicates that the relatively high scores on one variable tend to go along with relatively high scores on the other variable

Question 42

Then a scatter plot has a downward trend, going from upper left to lower right then relatively high scores on one variable tend to go along with relatively those scores on the other variables

Answer 42

Class absences and lower GPA

Question 43

Is scatterplot that has no clear up or downward trend indicates inconsistency between variables 

Answer 43

Scatterplots can be extremely useful when trying to understand the association between two variables

Question 44

Covariance begins building a bridge between the concept of variability and an interpretable quantitative index of covariability

Answer 44

In contrast, covariance is computed from the variability among scores into different distributions

Question 45

The covariance represents the degree of association between the variability in the two distributions of scores

Question 46

The correlation coefficient is intended to provide an easily interpretable index of linear association

Answer 46

True

Question 47

Like the Covariance a correlation coefficient reflects the “direction” of the association between two variables 

Answer 47

A correlation with a value that lies between 0 and +1, tells us that there is a positive association between the two variables. In contrast, the correlation be the value that lies between 0 and -1 tells us that there is a negative association between the two variables.

Question 48

The great benefit of a correlation is that it reflects the magnitude of the association between two variables, much more clearly than does the Covariance.

Question 49

A correlation that is close to 0 reflects a weak association

Question 50

The correlation coefficient is an important part of reliability theory

Question 51

The Pearson correlation is most appropriate for two variables that are on an interval or ratio scale of measurement

Question 52

Total test score variance will depend solely on item variability and the correlation between item pairs. This issue is an important facet of reliability theory.

Question 53

Dichotomous or binary items

Answer 53

Behavioural observations that have been scored dichotomously

Question 54

Tests based on binary items are typically scored by summing or averaging responses across items

Answer 54

True

Question 55

The mean of a binary item is equal to the proportion of positively valenced answers