19 terms

Class

one of the categories into which qualitative data can be classified

Class frequency

number of observations in the data set that fall into a particular class

class relative frequency

class frequency divided by the total number of observations in the data set C freq/n

class Percentage

class relative frequency * 100

graphical descriptive methods for QUALITATIVE data

Bar graph: height = class (relative) frequency or percentage

Pie chart: size of slice is proportional to the class relative frequency

Pareto Diagram: bar graph ordered from left to right (big to left)

Pie chart: size of slice is proportional to the class relative frequency

Pareto Diagram: bar graph ordered from left to right (big to left)

bar graph

pie chart

pareto diagram

Graphical descriptive methods for QUANTITATIVE Data

Dot Plot

Stem And Leaf Display

Histogram

Stem And Leaf Display

Histogram

dot plot

stem and leaf display

histogram

Central Tendency

tendency to cluster or center about certain numerical values

variability

spread of the data

Numerical descriptive measures

Central tendency

Variability

Variability

measures of central tendency

sample Mean (X+ STREEPJE ERBOVEN)

- Population mean (mu)

Median (middle Number)

Skewed ( mean towards side)

- rightward skewness ( left median - more right mean)

Mode - most frequent set of measurement

- Population mean (mu)

Median (middle Number)

Skewed ( mean towards side)

- rightward skewness ( left median - more right mean)

Mode - most frequent set of measurement

measures of variability / spread of data set

Range = largest x - smallest x

- insensitive with big sets

Sample variance s^2= (som (xi-mean)^2)n-1

sample standard deviation -

- insensitive with big sets

Sample variance s^2= (som (xi-mean)^2)n-1

sample standard deviation -

Measures of relative standing

percentile ranking 90th percentile ( 90% is lower than you)

Lower quartile (Ql) 25 %

middle quartile (M) 50 %

Upper quartile (Qu) 75 %

Z-score = ( x - mean)/standard deviation

Lower quartile (Ql) 25 %

middle quartile (M) 50 %

Upper quartile (Qu) 75 %

Z-score = ( x - mean)/standard deviation

Methods for detecting outliers:

Interquartile range (IQR) = Qu -QL

BOXplot

BOXplot