Chapters 1-4

Front 1

experimental group

Back 1

does not receive treatment

Front 2

dependent variable

Back 2

is observed for changed

Front 3

operational definition

Back 3

defines a construct in terms of a measurable response

Front 4

nominal scale

Back 4

labels observations so they can fall into different catergories

Front 5

ordinal scale

Back 5

ranks observations in terms of size and magnitude

Front 6

interval scale

Back 6

the difference between two number on a scale. Yet it is not meaningful

Front 7

ratio scale

Back 7

Has a meaningful zero point and therefore reflect magnitudes

Front 8

discrete variable

Back 8

an finite number of values between any two values. No numbers can be found between neighboring values ( no real limits)

Front 9

continuous variable

Back 9

can take on infinite numbers of values

Front 10

frequency distribution

Back 10

is a record of the number of individuals located in each category on the scale of measurement

Front 11

continuous variable

Back 11

each score actually corresponds to an interval on the scale. The boundaries that separate the intervals are called real limits

Front 12

real limits

Back 12

separate two adjacent scores is located exactly halfway between the score each score has two real limits

Front 13

upper limit

Back 13

top of the interval; and the one interval is also the lower real limit of the next higher interval

Front 14

lower limit

Back 14

the bottom of the interval

Front 15

histogram

Back 15

vertical bars above each score
1. height of the bar correspond to the frequency.
2. the width of the bar extends to the real limits of the score

Front 16

bar graph

Back 16

a vertical bar drawn above each score or category
1. the height of the bar corresponds to the frequency
2. There is a space separating each bar from the next.

Front 17

interpolation

Back 17

it is a method for finding intermediate values. Values located between tow specific numbers. It is only an estimation. Assumed to be a regular linear change

Front 18

central tendency

Back 18

is a statistical measure that identifies the single most score for an entire distribution

Front 19

mode

Back 19

the score that has the greatest frequency observable

Front 20

median

Back 20

the 50th percentile. Exactly 50% of the individuals in a distribution have scores at or below the median

Front 21

mean

Back 21

arithmetic average; computed by adding up all the score in the distribution and dividing by the number of scores

Front 22

skewed distribution

Back 22

mode is located toward the side where the scores pile up and the mean will be pulled toward the extreme scores in the tail. Median will be located between these two variables

Front 23

range

Back 23

the distance between the largest scores and the smallest score in a distribution. Id the smallest and the lowest score and the range is determined by range= high- low +1

Front 24

interquartile range

Back 24

is the distance between the first quartile and the 3rd quartile. interquartile range= Q3 - Q1

Front 25

deviation

Back 25

is the distance from the mean
deviation score = x = - mean

Front 26

average deviation

Back 26

is the average of the absolute value of the deviation scores

Front 27

population variance

Back 27

average squared deviation

Front 28

standard deviation

Back 28

variance = average squared deviation = sum of squared deviation / number of scores

Front 29

sum of squares

Back 29

is the sum of the squared deviation scores.

Front 30

degree of freedom

Back 30

df= n-1

Front 31

parameter

Back 31

is a measurement that describes a characteristic of a POPULATION

Front 32

descriptive statistical

Back 32

summarize and simply data

Front 33

inferential statistics

Back 33

technique that uses sample data to make general statements about a population

Front 34

statistic

Back 34

describes a characteristic of a SAMPLE

Front 35

distribution

Back 35

a set of scores

Front 36

raw score

Back 36

an original measurement or value in a distribution

Front 37

random selection

Back 37

every person has the same chance of being selected

Front 38

Science

Back 38

based on observation, empirical

Front 39

variability

Back 39

provides a quantitative measure of the differences between scores in a distribution and describes the degree scores are spread out or clustered together.

Front 40

The two purposes for measuring variability are:

Back 40

1) to describe a distribution score long distance spread out or close together
2)measures how well an individual or group of scores are spread to represent the distribution

Front 41

range = URL-LRL

Back 41

upper real level - lower real limit (X max - X min) = range

Front 42

3 different measure of variability

Back 42

range, standard deviation and variance

Front 43

X max - X min

Back 43

alternative range not necessary to use real limits

Front 44

Because the RANGE does not consider all the score in the distribution

Back 44

it often does not give a accurate description of the variability for the ENTIRE distribution

Front 45

considered a crude and unreliable way to measure variability

Back 45

range

Front 46

defined in terms of distance

Back 46

variability

Front 47

tells how much distance to expect between one score and the mean

Back 47

variability describing distribution

Front 48

standard deviation

Back 48

commonly used and most important measure of variability.