Statistics CH 2 - Methods for describing sets of data

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PLAY

Terms in this set (...)

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)
bar graph
pie chart
pareto diagram
Graphical descriptive methods for QUANTITATIVE Data
Dot Plot

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
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
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 -
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
Methods for detecting outliers:
Interquartile range (IQR) = Qu -QL

BOXplot

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