Ch 2 Basic Assessment & Statistical Concepts

Question 1

Statistics is: (formal definition)

Answer 1

a set of tools and techniques used for describing, organizing, and interpreting information

Question 2

Three purposes of statistics:

Answer 2

describe and display data
explain relationships
make conclusions and inferences based on collected data

Question 3

Statistics are grouped into two categories:

Answer 3

1. Descriptive: used to organize and describe the characteristics of a set of data (what, how often, to whom)
2. Inferential: used to draw inferences from a small group of data (sample) that can be applied to a larger group (population) (correlations, mean comparisons, hyphothesis testing

Question 4

statistics is: (informal, Boccone)

Answer 4

a language used to look at and understand data

Question 5

Variable (definition):

Answer 5

any construct that can assume multiple values

Question 6

two types of variables:

Answer 6

1. Numeric values - quantitative variables

2. Categories - qualitative variables (can be numeric ranges)

Question 7

Discrete data:

Answer 7

units of measurement that cannot be divided or broken down into smaller units (i.e. # of children you have)

Question 8

Continuous data

Answer 8

can be subdivided infinitely as they are more approximations based on available data (time - milliseconds, nanoseconds…)

Question 9

latent variables:

Answer 9

cannot be directly measured, but inferred from the presences of other variables or self-reported by client

Question 10

Measurement involves:

Answer 10

the application of a specific set of procedures to assign quantitative values (numbers) to various objects, traits, behaviors

Question 11

Four Scales of Measurement:

Answer 11

1. Nominal
2. Ordinal
3. Interval
4. Ratio

Question 12

four measurement scale properties (each scale is identified by the presence or absence of a set of properties)

Answer 12

1. Identification
2. Magnitude
3. Equal Intervals
4. Absolute zero point

Question 13

Identification =

Answer 13

Each value on the measurement scale has a unique meaning

Question 14

Magnitude =

Answer 14

Values on the measurement scale have an ordered relationship to one another

Question 15

Equal intervals =

Answer 15

An equal number of scale units exist between each value along the measurement scale

Question 16

Absolute zero point =

Answer 16

The measurement scale has a true absolute zero point below which no values exist

Question 17

Nominal scale of measurement definition and scale property:

Answer 17

used to classify or categorize data into groups that have different names but are not related (ie, names, political parties) - can only name or identify the object being measured
Property = identification

Question 18

Value of nominal data:

Answer 18

its ability to provide us with percentages and frequencies of scores or clients who may fall into particular categories

Question 19

Ordinal scale of measurement definition and scale properties:

Answer 19

variables are rank ordered along continuum so each value has a unique meaning and appears in an ordered relationship to other values (ie, 1st, 2nd, 3rd place…)
Properties = identification, magnitude

Question 20

Interval scale of measurement definition and scale properties:

Answer 20

includes equal intervals which allows definitive statements about an individual’s position on a continuum as well as the positioning relative to others. (ie - IQ scores)
Properties of identification, magnitude and equal intervals. - can add/subtract, but not multiply and create percentages)

Question 21

Ratio scale of measurement definition and scale properties:

Answer 21

For variables measured on a ratio scale, the value of zero represents the absence of the variable being measured and can do all types of mathematical calculations. (ie - weight, can be weightless, but not negative weight)
Properties - identification, magnitude, equal intervals, absolute zero point

Question 22

Frequency distribution =

Answer 22

orders a set of disorganized raw scores and summarizes the number of times each of the different scores occurs within a sample of scores

Question 23

Frequency distribution helps

Answer 23

condense a large set of data into a more manageable display

Question 24

Simple frequency distribution table =

Answer 24

presents data in two columns: individual scores and # of times score occurred

Question 25

Mathematical operations done with frequency distribution:

Answer 25

of individuals or scores
proportions
percentages

Question 26

Two shapes of frequency distributions:

Answer 26

Symmetrical = curve is a mirror image of the other, majority of scores clustered in center of the distribution close to the mean

Asymmetrical = scores are skewed or distorted to one side of the distribution

Question 27

Asymmetrical scores are skewed in what two ways

Answer 27

positively skewed = majority of scores fall on low end of the distribution

negatively skewed = majority of scores fall on the high end of the distribution

the tail tells the tale

Question 28

Central tendency =

Answer 28

statistical measure that indicates the center or middle of the distribution

Question 29

What does central tendency allow for?

Answer 29

Comparisons between groups and individuals

Question 30

Three measures of central tendency?

Answer 30

Mean
Median
Mode
-work best used together for a full picture

Question 31

arithmetic Mean =

Answer 31

sum of all scores divided by the total number of scores - the average or mean; don’t use with extreme outliers

Question 32

Median =

Answer 32

the middle score or the score that divides the distribution exactly in half
(equivalent to the 50th percentile)

Question 33

Mode =

Answer 33

score that has the greatest frequency in a distribution

Question 34

Variability =

Answer 34

quantitative measure that describes how spread out or clustered together scores are in a distribution

Question 35

measures of variability =

Answer 35

statistics that describe the amount of variation in a distribution

Question 36

three measures of variability =

Answer 36

range
standard deviation
variance

Question 37

Range =

Answer 37

difference between the highest and lowest value in a distribution
-used with interval and ratio data

Question 38

standard deviation =

Answer 38

average of amount by which scores vary from the mean

ie - IQ test - standard deviation is 15 in either direction

Question 39

variance =

Answer 39

the mean of the squared deviation scores (used for computational purposes

Question 40

standard scores =

Answer 40

indicate the distance an individual’s raw score is above or below the mean of the reference group in terms of standard deviation units

• tells us how many standard deviations a score is away from the mean

Question 41

standard scores allow for what to be made?

Answer 41

comparisons because the score describe how many SDs an individual’s score is from the mean of that particular distribution

Question 42

4 types of standard scores =

Answer 42

z-scores
t-scores
stanines
percentiles
- all tell us the same thing but in different ways

Question 43

z-score properties =

Answer 43

mean = 0, SD = 1

most common standard score

Question 44

How do you obtain a z-score?

Answer 44

convert a raw score into a number that represents how many SDs the raw score is above or below the mean

+ sign indicates SD is above the mean
- sign indicates SD is below the mean
doesn’t tell if a score is good or bad

iq test example - +1 SD means 1 SD above the mean or 115

Question 45

t-scores properties

Answer 45

mean = 50, SD = 10

Question 46

How to obtain a t-score?

Answer 46

multiply the z-score by 10 then add 50

Question 47

stanines

Answer 47

converts raw scores into one of nine possible scores

- rarely used by same concept - how far something is away from the mean

Question 48

Percentiles =

Answer 48

indicates percentage of people in a reference group that fall at or below the individual’s raw score

• where you fall in relation to the whole group:
  50th percentile = you did better than 50%