Tests And Appraisals In Counseling Midterm: Chapter 3

Front 1

A numerical representation of information is a

Back 1

Statistic

Front 2

Weight is an example of this type of variable

Back 2

Continuous

Front 3

List 2 types of quantitative variables

Back 3

Discrete, continuous

Front 4

These variables can not be directly measured, but are inferred

Back 4

Latent

Front 5

These variables can be observed and directly measured

Back 5

Observable

Front 6

These variables are numeric in nature

Back 6

Quantitative

Front 7

These variables are nonnumeric in nature

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Qualitative

Front 8

These numeric variables measure "how many" -- they cannot be subdivided

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Discrete

Front 9

These numeric variable measure "how much"

Back 9

Continuous

Front 10

List 4 scales of measurement

Back 10

Nominal, Ordinal, Interval, Ratio

Front 11

This type of scale of measurement has discrete, qualitative variables

Back 11

Nominal

Front 12

This scale of measurement has qualities including magnitude, equal intervals, and absolute 0

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Ratio

Front 13

This scale of measurement has qualities including magnitude and equal intervals

Back 13

Interval

Front 14

This scale of measurement only has the quality of magnitude

Back 14

Ordinal

Front 15

This scale of measurement has no special qualities, but includes things like names or lists of words.

Back 15

Nominal

Front 16

A Likert scale or rank ordered scale is an example of this type of scale of measurement

Back 16

Ordinal

Front 17

Temperature is an example of this type of scale of measurement

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Interval

Front 18

Age, height, and weight scales are examples of this type of scale of measurement

Back 18

Ratio

Front 19

You can multiply or divide items on this type of scale of measurement

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Ratio

Front 20

You can add and subtract items on this type of scale of measurement, but cannot multiply or divide

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Interval

Front 21

List 4 general ways in which researchers and test developers describe statistics

Back 21

Frequency,
Central Tendency,
Variability,
Relationships

Front 22

This is a way to show a disorganized set of scores and place them in order, showing how many (people) obtained each of the scores

Back 22

Frequency Distribution

Front 23

This type of graph uses vertical lines and bars to portray the distribution of test scores.

Back 23

Histogram

Front 24

This variation of a histogram replaces bars with lines connecting the midpoint of each class interval.

Back 24

Frequency Polygon

Front 25

This graph gives us a better idea of the shape of the distribution as well as the frequency of scores

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Smoothed Frequency Polygon (or frequency curve)

Front 26

A frequency curve (smoothed frequency polygon) that is not symmetrical is called a

Back 26

Skewed curve

Front 27

In this skewed curve, the majority of data falls on the lower end of the scale

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Positively skewed curve

Front 28

In this skewed curve, the majority of data falls on the upper end of the scale

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Negatively skewed curve

Front 29

Three common measures of central tendency are the

Back 29

Mean,
Median,
Mode

Front 30

The average score in a distribution is referred to as the

Back 30

Mean

Front 31

Given these numbers, calculate the mean, median, and mode:
78,85,86,90,98,100,100,102,110,115,142,146,165

Back 31

Mean = 109
Median = 100
Mode = 100

Front 32

In descriptive statistics, this type of central tendency has two modes

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Bi-modal

Front 33

This measure of central tendency is the middle score, or the score that divides the distribution in half

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Median

Front 34

For symmetrical distributions, these 3 measures of central tendency are equal

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Mean
Median
Mode

Front 35

In central tendency measures, this is the score that appears most frequently

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Mode

Front 36

Calculate the range of these numbers:
1,2,2,3,3,3,4,4,5,5,6,6,40

Back 36

39

Front 37

Range is an example of the measurement of these types of descriptive statistics

Back 37

Variability

Front 38

This measure describes the average distance of test scores from the mean

Back 38

Standard deviation

Front 39

This curve has the following properties:
*bell shaped,
*bilaterally symmetrical,
*mean, median and mode are equal to each other
*Asymptotic tails
*Unimodal
*100% of the scores fall between -3 and +3 standard deviations from the mean

Back 39

Normal Curve (aka normal distribution or bell curve)

Front 40

68% of a population within a normal curve falls between what standard deviations

Back 40

-1 and +1 standard deviations

Front 41

This measure of relationship indicates that two variables move in the same direction

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Positive correlation

Front 42

This measure of relationship indicates that two variables move in opposite directions

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Negative correlation

Front 43

A complete absence of a relationship between 2 variables is indicated by this number

Back 43

0

Front 44

A perfect positive relationship between two variables has this correlation coefficient

Back 44

+1

Front 45

A perfect negative relationship between two variables has this correlation coefficient

Back 45

-1

Front 46

The number of violent crimes committed is strongly positively correlated with the number of ice cream sales at a given time. Does this mean that one causes the other?

Back 46

No. Correlation does not mean causation.

Front 47

Linear relationships between two continuous variables are measured using this type of correlation coefficient

Back 47

Pearson Product Moment Correlation (r)

Front 48

A variant of Pearson's r used for finding the association between two ordinal variables and does not require a linear relationship between variables is

Back 48

Spearman's Rho (r)

Front 49

Likert scales often use this type of correlation coefficient measure

Back 49

Spearman's Rho (r)

Front 50

The degree of association between two nominal variables is assessed by this correlation coefficient measure

Back 50

Phi Coefficient

Front 51

This is used to assess the size and direction of a relationship between variables

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Correlation

Front 52

This statistical method is used in the analysis of relationships among variables for predictive purposes

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Regression

Front 53

In measurements of relationship, this is used to predict the value of one variable based on the value of another single variable

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Simple linear regression

Front 54

In measurements of relationship, this is used to predict the value of one variable based on the value of two or more independent variables

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Multiple regression

Front 55

This analyzes the relationship among variables for purposes of reducing the number of necessary variables

Back 55

Factor Analysis

Front 56

Creat demographic questionnaire for study with 5 questions/statements including: 2 nominal, 1 ratio, 1 ordinal, and 1 interval scale. Identify each type.

Back 56

Nominal:
Relationship Status, Gender

Ordinal: Rate your interest in taking this test on a scale from 1 to 5 . . .

Interval:
What was your temperature in Fahrenheit degrees on your last doctor's visit

Ratio:
What is your current weight

Front 57

Difference between regression, factor analysis, and spearman's rho. Explain how you would determine which analysis to conduct and provide an example of each.

Back 57

The all are measurement methods involving relationships between variables, however they are used for different purposes. Regression measures correlation strength and direction of a relationship between variables. There are different types of regression (Simple linear and Multiple Regression) analysis; all are used for predictive purposes.
(example - if there is a strong positive correlation between IQ and grades, I could take one of the two variables and figure out the other (dependent) variable based on that.

Spearman's Rho is a way to calculate the correlation coefficient (used in regression). It is used to find the relationship between ordinal variables and doesn't require a linear relationship between the variables. You would use Spearman's Rho to figure out if a correlation between 2 ordinal variables exists.
Factor Analysis is used to simplify variables. You would use it to reduce the number of questions necessary on a given test while still yielding accurate results.