SlideShare a Scribd company logo
Measures of Variation
• Sample range
• Sample variance
• Sample standard deviation
• Sample interquartile range
Sample Range
R = largest obs. - smallest obs.
or, equivalently
R = xmax - xmin
Sample Variance
 
s
x x
n
i
i
n
2
2
1
1





Sample Standard Deviation
 
s s
x x
n
i
i
n
 




2
2
1
1
• it is the typical (standard) difference
(deviation) of an observation from the mean
• think of it as the average distance a data
point is from the mean, although this is not
strictly true
What is a standard deviation?
Sample Interquartile Range
IQR = third quartile - first quartile
or, equivalently
IQR = Q3 - Q1
Measures of Variation -
Some Comments
• Range is the simplest, but is very sensitive to
outliers
• Variance units are the square of the original
units
• Interquartile range is mainly used with skewed
data (or data with outliers)
• We will use the standard deviation as a
measure of variation often in this course
Boxplot - a 5 number summary
• smallest observation (min)
• Q1
• Q2 (median)
• Q3
• largest observation (max)
Boxplot Example - Table 4, p. 30
• smallest observation = 3.20
• Q1 = 43.645
• Q2 (median) = 60.345
• Q3 = 84.96
• largest observation = 124.27
Creating a Boxplot
• Create a scale covering the smallest to largest values
• Mark the location of the five numbers
• Draw a rectangle beginning at Q1 and ending at Q3
• Draw a line in the box representing Q2, the median
• Draw lines from the ends of the box to the smallest
and largest values
• Some software packages that create boxplots include
an algorithm to detect outliers. They will plot points
considered to be outliers individually.
0 10 20 30 40 50 60 70 80 90 100 110 120 130
. . . . .
Min = 3.20
Q1 = 43.645
Q2 = 60.345
Q3 = 84.96
Max = 124.27
Boxplot Example
Boxplot Interpretation
• The box represents the middle 50% of the data,
i.e., IQR = length of box
• The difference of the ends of the whiskers is the
range (if there are no outliers)
• Outliers are marked by an * by most software
packages.
• Boxplots are useful for comparing two or more
samples
– Compare center (median line)
– Compare variation (length of box or whiskers)

More Related Content

PPT
Statistical Measures of Variability Range: The difference between the hi...
PPT
Variable – Any factor that can change in a scientific investigation or experi...
PPT
Chapter04
PPT
Chapter04
PPTX
Revisionf2
PPTX
lecture 3 Slides.pptx
PPTX
BOX PLOT STAT.pptx
PPT
Statistics-Measures of dispersions
Statistical Measures of Variability Range: The difference between the hi...
Variable – Any factor that can change in a scientific investigation or experi...
Chapter04
Chapter04
Revisionf2
lecture 3 Slides.pptx
BOX PLOT STAT.pptx
Statistics-Measures of dispersions

Similar to STATISTICS VARIANCE INTRODUCTORY PRESENTATION.ppt (20)

PPTX
Statistics for machine learning shifa noorulain
PPTX
Box And Whisker Plots
PPTX
3.3 percentiles and boxandwhisker plot
PPT
STATISTICAL MEASURES.ppt
PPTX
Digital lecture measures of variability.pptx
PPT
Chapter 6 slide show notes math 140 summer 2011
PPT
Algebra unit 9.3
PPT
Lesson03_new
PPT
Measures of Variablity.kjc.ppt
PPTX
Measuresof spread
PPTX
Business statistics ( Methods of variablity measurement))
PPTX
Box Plot introduction for beginners.....
PPTX
ProbabilityandStatsUnitAPowerpoint-1.pptx
PPTX
Statistics (Measures of Dispersion)
PDF
The Role of Box Plots in Comparing Multiple Data Sets
PPT
chapter no. 2. describing central tendency and variability .ppt
PPTX
Range, quartiles, and interquartile range
PPT
Lesson03_static11
PPT
2 7 exploratory data analysis
Statistics for machine learning shifa noorulain
Box And Whisker Plots
3.3 percentiles and boxandwhisker plot
STATISTICAL MEASURES.ppt
Digital lecture measures of variability.pptx
Chapter 6 slide show notes math 140 summer 2011
Algebra unit 9.3
Lesson03_new
Measures of Variablity.kjc.ppt
Measuresof spread
Business statistics ( Methods of variablity measurement))
Box Plot introduction for beginners.....
ProbabilityandStatsUnitAPowerpoint-1.pptx
Statistics (Measures of Dispersion)
The Role of Box Plots in Comparing Multiple Data Sets
chapter no. 2. describing central tendency and variability .ppt
Range, quartiles, and interquartile range
Lesson03_static11
2 7 exploratory data analysis
Ad

Recently uploaded (20)

PDF
.pdf is not working space design for the following data for the following dat...
PPTX
advance b rammar.pptxfdgdfgdfsgdfgsdgfdfgdfgsdfgdfgdfg
PPTX
MODULE 8 - DISASTER risk PREPAREDNESS.pptx
PPTX
Qualitative Qantitative and Mixed Methods.pptx
PPTX
Introduction to Knowledge Engineering Part 1
PPTX
Introduction to machine learning and Linear Models
PPTX
01_intro xxxxxxxxxxfffffffffffaaaaaaaaaaafg
PDF
Business Analytics and business intelligence.pdf
PDF
Mega Projects Data Mega Projects Data
PDF
TRAFFIC-MANAGEMENT-AND-ACCIDENT-INVESTIGATION-WITH-DRIVING-PDF-FILE.pdf
PPTX
Introduction to Basics of Ethical Hacking and Penetration Testing -Unit No. 1...
PPTX
AI Strategy room jwfjksfksfjsjsjsjsjfsjfsj
PPTX
oil_refinery_comprehensive_20250804084928 (1).pptx
PPT
Reliability_Chapter_ presentation 1221.5784
PDF
Foundation of Data Science unit number two notes
PDF
Recruitment and Placement PPT.pdfbjfibjdfbjfobj
PPTX
IB Computer Science - Internal Assessment.pptx
PPT
ISS -ESG Data flows What is ESG and HowHow
PPTX
The THESIS FINAL-DEFENSE-PRESENTATION.pptx
.pdf is not working space design for the following data for the following dat...
advance b rammar.pptxfdgdfgdfsgdfgsdgfdfgdfgsdfgdfgdfg
MODULE 8 - DISASTER risk PREPAREDNESS.pptx
Qualitative Qantitative and Mixed Methods.pptx
Introduction to Knowledge Engineering Part 1
Introduction to machine learning and Linear Models
01_intro xxxxxxxxxxfffffffffffaaaaaaaaaaafg
Business Analytics and business intelligence.pdf
Mega Projects Data Mega Projects Data
TRAFFIC-MANAGEMENT-AND-ACCIDENT-INVESTIGATION-WITH-DRIVING-PDF-FILE.pdf
Introduction to Basics of Ethical Hacking and Penetration Testing -Unit No. 1...
AI Strategy room jwfjksfksfjsjsjsjsjfsjfsj
oil_refinery_comprehensive_20250804084928 (1).pptx
Reliability_Chapter_ presentation 1221.5784
Foundation of Data Science unit number two notes
Recruitment and Placement PPT.pdfbjfibjdfbjfobj
IB Computer Science - Internal Assessment.pptx
ISS -ESG Data flows What is ESG and HowHow
The THESIS FINAL-DEFENSE-PRESENTATION.pptx
Ad

STATISTICS VARIANCE INTRODUCTORY PRESENTATION.ppt

  • 1. Measures of Variation • Sample range • Sample variance • Sample standard deviation • Sample interquartile range
  • 2. Sample Range R = largest obs. - smallest obs. or, equivalently R = xmax - xmin
  • 3. Sample Variance   s x x n i i n 2 2 1 1     
  • 4. Sample Standard Deviation   s s x x n i i n       2 2 1 1
  • 5. • it is the typical (standard) difference (deviation) of an observation from the mean • think of it as the average distance a data point is from the mean, although this is not strictly true What is a standard deviation?
  • 6. Sample Interquartile Range IQR = third quartile - first quartile or, equivalently IQR = Q3 - Q1
  • 7. Measures of Variation - Some Comments • Range is the simplest, but is very sensitive to outliers • Variance units are the square of the original units • Interquartile range is mainly used with skewed data (or data with outliers) • We will use the standard deviation as a measure of variation often in this course
  • 8. Boxplot - a 5 number summary • smallest observation (min) • Q1 • Q2 (median) • Q3 • largest observation (max)
  • 9. Boxplot Example - Table 4, p. 30 • smallest observation = 3.20 • Q1 = 43.645 • Q2 (median) = 60.345 • Q3 = 84.96 • largest observation = 124.27
  • 10. Creating a Boxplot • Create a scale covering the smallest to largest values • Mark the location of the five numbers • Draw a rectangle beginning at Q1 and ending at Q3 • Draw a line in the box representing Q2, the median • Draw lines from the ends of the box to the smallest and largest values • Some software packages that create boxplots include an algorithm to detect outliers. They will plot points considered to be outliers individually.
  • 11. 0 10 20 30 40 50 60 70 80 90 100 110 120 130 . . . . . Min = 3.20 Q1 = 43.645 Q2 = 60.345 Q3 = 84.96 Max = 124.27 Boxplot Example
  • 12. Boxplot Interpretation • The box represents the middle 50% of the data, i.e., IQR = length of box • The difference of the ends of the whiskers is the range (if there are no outliers) • Outliers are marked by an * by most software packages. • Boxplots are useful for comparing two or more samples – Compare center (median line) – Compare variation (length of box or whiskers)