lec05 - STATISTICS 13 Lecture 5 Oct 4 2010 Shape of the...

Info iconThis preview shows pages 1–9. Sign up to view the full content.

View Full Document Right Arrow Icon
STATISTICS 13 Lecture 5 Oct 4, 2010
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Review Shape of the data -Bell shaped -Skewed -Bimodal Measures of center – Arithmetic Mean – Median – Mode Effects of outliers and skewness
Background image of page 2
Measures of Variability A quantitative measure that describes the spread or dispersion of the data along the horizontal axis of the data distribution Data sets may have the same center (e.g., mean), but look different because the way the numbers spread out from the center
Background image of page 3

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Measures of Variability (Cont.) Example: two data sets -data set one: 1,2,3,3,4,4,4,4,5,5,5,5,5,5,6,6,6,6,7,7,8,9 -data set two: 3,4,4,5,5,5,6,6,7 -
Background image of page 4
Measures of Variability: (I) Range Range of a sample of n measurements is the difference between the maximum and the minimum : R = Max – Min Example : daily number of phone calls in five days: 5, 2, 14, 3, 6 ; Drawback : depends on only two values among the measurements, very highly affected by outliers
Background image of page 5

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Measures of Variability: (II) Variance Variance of a sample of n measurements is the sum of squared deviation from the sample mean, divided by (n-1) ; It measures how far away the measurements are from their mean. Example : phone calls -data: 5, 2, 14, 3, 6 ;n=5 -mean = -deviations : -squared deviations : -variance: 1 ) ( 2 2 = n x x s i
Background image of page 6
Population vs. Sample Variance of a population of N subjects is the averaged squared variation from the population mean μ ; σ 2 usually is not calculable due to the lack of data of the whole population Variance of a sample of n measurements is the sum of squared deviation from the sample mean, divided by (n-1) N x N x i i 2 2 ) ( µ = = 1 ) ( 2 1 2 1 = = = = n x x s n x x i n i i n i
Background image of page 7

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Why Divided by n-1 ?
Background image of page 8
Image of page 9
This is the end of the preview. Sign up to access the rest of the document.

Page1 / 22

lec05 - STATISTICS 13 Lecture 5 Oct 4 2010 Shape of the...

This preview shows document pages 1 - 9. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online