Stats Chapter 1

Front 1

Statistics

Back 1

branch of math that focuses on the organization, analysis and interpretation of a group of numbers

Front 2

Descriptive statistics

Back 2

Procedure for summarizing a group of scores or otherwise maknig them more comprehensible

Front 3

Interential statistics

Back 3

Procedure for drawing conclusion based on the scores collectd in a reseach study buy going beyond them

Front 4

Variable

Back 4

Characteristic that can have different values

Front 5

Values

Back 5

Possible number or category that a score can have

Front 6

Score

Back 6

Particular person's value on a variable.

Front 7

Numeric variable

Back 7

variable whose values are numbers (as opposed to a nominal variable). AKA: Quantitative Variable

Front 8

Equal-interval variable

Back 8

variable in which the numbers stand for approximately equal amounts of waht is being measured

Front 9

Ratio scale

Back 9

an equal-interval variable is measured on a ratio scale if it has an ABSOLUTE ZERO POINT, meaning that the value of zero on the ariable indicates a complete absence of the variable

Front 10

Discrete variable

Back 10

variable that has specific values and that cannot have values between these specific values. (i,2,3..)

Front 11

Continuous variable

Back 11

variable for which, in theory, there are an infinite number of values between any two numbers (1.3343 etc.)

Front 12

Rank-oder variable

Back 12

numeric variable in which the valeues are ranks, such as class standing or place finished in a race. AKA: Ordinal Variable (1st, 2nd... not detailed numbers)

Front 13

Nominal variable

Back 13

Variable with values that are categories (that is, they are names rather than numbers). AKA: Categorical variable

Front 14

Levels of measurment

Back 14

Types of underlying numerical information provided by a measure, such as equal-interval, rank-order, and nominal (categorical)

Front 15

Frequency table

Back 15

listing of number of individuals having each of the different values for a particular variable

Front 16

Interval

Back 16

range of values in a grouped frequency table that are grouped together. (for ex. if the interval size is 10, one of the intervals might be from 10-19)

Front 17

Grouped frequency table

Back 17

frequency table in which the number of individuals (frequency) is given for each interval of values

Front 18

Histogram

Back 18

barlike graph of a frequency distribution in which the values are plotted along the horizontal axis and the height of each bar is the frequency of that value; the bars are usually placed next to each other without spaces, giving the appearance of a city skyline

Front 19

Frequency distribution

Back 19

pattern of frequencies over the various values; what a frequency table, histogram or frequency polygon describes

Front 20

Unimodal distribution

Back 20

frequency distribution wiht one value clearly hving a larger grequency than any other (1 big point)

Front 21

Bimodal distribution

Back 21

Frequency distribution with 2 approximately equal frequencies, each clealry large than any of the others (2 big points)

Front 22

Multimodal distribution

Back 22

frequency distribution with 2 or more high frequencies seperated by a lower frequency; a bimodal distribution is the special case of two high frequencies (2 high seperated by a low)

Front 23

Rectangular distribution

Back 23

Frequency distribution in which all values have approximatley the same frequency

Front 24

Symmetrical distribution

Back 24

distribution in which the pattern of frequenceis on the left and right side are mirror images of each other (even curve up and down)

Front 25

Skewed distribution

Back 25

distribution in which the scores pile up on one side of the middle and are spread out on the other side; distribution tht is not symmetrical

Front 26

Floor effect

Back 26

situation in which many scoare pile up at the low end of a distribution (creating skewness) b/c it is not possible to have any lower score.

Front 27

Celing effect

Back 27

sitatuion in which many scorees pile up at the high end of a distribution (creating skewness) b/c it is not possible to have a higher score

Front 28

normal curve

Back 28

specific, mathematically defined, bell-shaped frequency distribution that is symmetrical and unimodal distributions observed in nature and in research commonly approximate it.

Front 29

Kurtosis

Back 29

Extent to which a frequency distribution deviates from a normal curve in term of wheather its curve in the middle is more peaked or flat thatn the normal curve