Stats 2

Front 1

Characteristics of Data

Back 1

Center

Variation

Distribution

Outliers

Time

Front 2

Center

Back 2

a representative value that indicates where the middle of the data set is located (the average or mean or median)

Front 3

Variation

Back 3

a measure of the amount that the data values vary

Front 4

distribution

Back 4

the nature or shape of the spread of the data over the range of values (such as a bell shape)

Front 5

outliers

Back 5

sample values that lie very far away from the vast majority of the other samples

Front 6

time

Back 6

any change in the characteristics of the data over time

Front 7

a frequency distribution/frequency table

Back 7

shows how data are partitioned among several catagories (or classes) by listing the categories along with the number (frequency) of data values in each of them

Front 8

lower class limits

Back 8

are the smallest numbers that can belong to the different classes (15,19,23,27,31)

Front 9

upper class limits

Back 9

are the largest numbers that can belong to the different classes (18,22,26,30,34)

Front 10

class boundaries

Back 10

are the numbers used to separate the classes, but without the gaps created by class limits (14.5,18.5,22.5,26.5,30.5,34.5)

Front 11

class midpoints

Back 11

are the values in the middle of the classes (16.5,20.5,24.5,28.5,32.5)

Front 12

class width

Back 12

is the difference between two consecutive lower class limits (or two consecutive lower class boundaries) (19-15) = 4 (23-19) = 4
NOTE - the class width is found by subtracting the minimum value of the data from the maximum value of the data and then dividng by the number of classes NOTE: (The minimum amount of classes is 5)\
CLASS WIDTH = (34-15)/5 = 19/5 = 3.8

Front 13

Relative frequency distribution

Back 13

is when the class frequency gets replaced by relative frequency (decimal or percent)

Front 14

Normal Distribution

Back 14

1) the data frequencies start low then increase to one or two high frequencies, and then decrease to a low frequency
2) The distribution is approximately symmetric, with frequencies preceding the maximum being rougly a mirror image of those that follow the maximum

Front 15

Histogram

Back 15

Histogram = is a graph consisting of bars of equal width drawn adjacent to each other. The horizontal scale represents classes of quantitative data values and the vertical scale represents frequencies. The heights of the bars correspond to the frequency values
NOTE - the horizontal scale can be labeled with lower class limits, class boundaries and class mid-points

Front 16

Scatterplot

Back 16

is a plot of paired (x,y) quantitative data with horizontal x-axis and a verticle y-axis (Used to determineif there is a coorelation between the X and the Y data values)

Front 17

Times series graph

Back 17

is a graph of time-series data, which are qunatitative data that have been collected at different points in time, such as monthly or yearly (use when measurements are taken over a period of time)

Front 18

a dot plot

Back 18

a dot plot consists of a graph in which each data value is plotted as a point (or dot) along a horizontal scale of values. Dots representing equal values are stacked

Front 19

stemplot

Front 20

Bar Graph

Back 20

uses bars of equal width to show frequencies of categories of categorical data

Front 21

Pareto chart

Back 21

is a bar graph that the frequencies are organized in decending order (use when you want to arrange the frequencies in decending order

Front 22

pie chart

Back 22

(TRY NOT TO USE PIECHARTS BECAUSE THEY DO NOT REPRESENT ACCURATE DIFFERENCES BETWEEN FREQUENCIES)- is a graph that depicts categorical data as slices of a circle, in which the size of each slice i proportinal to th e frequency count for the category

Front 23

Frequency polygon

Back 23

uses line segments connected to points located directly above class midpoint values. A frequency polygon is very similar to a histogram

Front 24

Ogive

Back 24

depicts cumulative frequencies

Front 25

Graphs that decieve

Back 25

Nonzero graphs, picographs

Front 26

CVDOT

Back 26

Center(median, mode, midrange), Variations(how much does the data spread), Distribution (normal,Skewd Distribution(right skewd distribution, left(lower skewd distribution), Outliers (value far away from the rest), Time

Front 27

measure of center

Back 27

a measure of center is a value at the center or middle of a data set.

Front 28

Mean/arithmetic mean

Back 28

of a data set is the measure of center found by adding the data values and dividing the total by the number of data values. Mean = (sum of all data values/number of data values)

Front 29

the median

Back 29

the Median - of a data set is the measure of center that is the middle value when the original data values are arranged in order of increasing(or decreasing) magnitude. ODD NUMBER = NUMBER IN MIDDLE, EVEN = TWO MIDDLE NUMBER DIVIDE BY 2

Front 30

mode

Back 30

the MODE of a data set is the value that occurs with the greatest frequency, (2 = bimodal, 2+ = multimodal, when no data repeated = no mode

Front 31

mid range

Back 31

the mid range of a data set is found by adding the maximum data value to the minimum values then dividing the sum by 2 (NOTE - the range = max value - min value)

Front 32

RAnge

Back 32

the range of a set of data values is the difference between the maximum data value and the minimum data value

Front 33

The standard deviation of a set of sample value

Back 33

denoted by s, is a measure of how much data values deviate away from the mean.

Front 34

variance

Back 34

of a set of values is a measurement of variation and is equal to the square of the standard deviation

Front 35

COEFFICIENT OF VARIATION

Back 35

for a set of data is expressed as a percent, describes the standard deviation relative to the mean, and is given by the following