part ii sigma freud and descriptive statistics chapter 3 vive la différence: understanding...
TRANSCRIPT
![Page 1: Part II Sigma Freud and Descriptive Statistics Chapter 3 Vive La Différence: Understanding Variability](https://reader035.vdocument.in/reader035/viewer/2022081506/5697bfbd1a28abf838ca1cfc/html5/thumbnails/1.jpg)
Part IISigma Freud and
Descriptive Statistics
Chapter 3
Vive La Différence:Understanding Variability
![Page 2: Part II Sigma Freud and Descriptive Statistics Chapter 3 Vive La Différence: Understanding Variability](https://reader035.vdocument.in/reader035/viewer/2022081506/5697bfbd1a28abf838ca1cfc/html5/thumbnails/2.jpg)
Why Variability Is Important
• How different scores are from one particular score (usually the mean)?– Spread– Dispersion
![Page 3: Part II Sigma Freud and Descriptive Statistics Chapter 3 Vive La Différence: Understanding Variability](https://reader035.vdocument.in/reader035/viewer/2022081506/5697bfbd1a28abf838ca1cfc/html5/thumbnails/3.jpg)
Measures of Variability
• Three types of variability – Range – Standard Deviation– Variance
• Typically reported together– Average– Variability
![Page 4: Part II Sigma Freud and Descriptive Statistics Chapter 3 Vive La Différence: Understanding Variability](https://reader035.vdocument.in/reader035/viewer/2022081506/5697bfbd1a28abf838ca1cfc/html5/thumbnails/4.jpg)
Computing the Range
• Most general estimate of variability
• Two types:– Exclusive Range
• r = h - l
– Inclusive Range• r = h – l + 1
![Page 5: Part II Sigma Freud and Descriptive Statistics Chapter 3 Vive La Différence: Understanding Variability](https://reader035.vdocument.in/reader035/viewer/2022081506/5697bfbd1a28abf838ca1cfc/html5/thumbnails/5.jpg)
Computing the Range
• Data: 98, 86, 77, 56, 48
h 98 highest score - l - 48 lowest score
r 50 range
![Page 6: Part II Sigma Freud and Descriptive Statistics Chapter 3 Vive La Différence: Understanding Variability](https://reader035.vdocument.in/reader035/viewer/2022081506/5697bfbd1a28abf838ca1cfc/html5/thumbnails/6.jpg)
Types of Range-Like Things
• Range• Mid-range – midpoint of range• Interquartile range – range between 1st & 3rd
quartiles• Semi-interquartile range – midpoint of
interquartile range • Studentized range – range expressed in
standard deviations
![Page 7: Part II Sigma Freud and Descriptive Statistics Chapter 3 Vive La Différence: Understanding Variability](https://reader035.vdocument.in/reader035/viewer/2022081506/5697bfbd1a28abf838ca1cfc/html5/thumbnails/7.jpg)
Computing Standard Deviation
• Standard deviation (s or SD) - most frequently reported measure of variability
• s or SD = average amount of variability in a set of scores
![Page 8: Part II Sigma Freud and Descriptive Statistics Chapter 3 Vive La Différence: Understanding Variability](https://reader035.vdocument.in/reader035/viewer/2022081506/5697bfbd1a28abf838ca1cfc/html5/thumbnails/8.jpg)
Computing Standard Deviationby Hand
1. List each score
8
887665543
![Page 9: Part II Sigma Freud and Descriptive Statistics Chapter 3 Vive La Différence: Understanding Variability](https://reader035.vdocument.in/reader035/viewer/2022081506/5697bfbd1a28abf838ca1cfc/html5/thumbnails/9.jpg)
Computing Standard Deviationby Hand
2. Compute the Mean
8
887665543
60X 10n
606
10
XX
n
![Page 10: Part II Sigma Freud and Descriptive Statistics Chapter 3 Vive La Différence: Understanding Variability](https://reader035.vdocument.in/reader035/viewer/2022081506/5697bfbd1a28abf838ca1cfc/html5/thumbnails/10.jpg)
Computing Standard Deviationby Hand
3. Subtract the mean from each score
8 8 – 6 = +2
8 8 – 6 = +28 8 – 6 = +27 7 – 6 = +16 6 – 6 = 06 6 – 6 = 05 5 – 6 = -15 5 – 6 = -14 4 – 6 = -23 6 – 3 = -3
Sum 0
![Page 11: Part II Sigma Freud and Descriptive Statistics Chapter 3 Vive La Différence: Understanding Variability](https://reader035.vdocument.in/reader035/viewer/2022081506/5697bfbd1a28abf838ca1cfc/html5/thumbnails/11.jpg)
Computing Standard Deviationby Hand
4./5. Square each individual difference and sum
8 8 – 6 = +2 +2 x +2 = +4
8 8 – 6 = +2 +2 x +2 = +48 8 – 6 = +2 +2 x +2 = +47 7 – 6 = +1 +1 x +1 = +16 6 – 6 = 0 0 x 0 = 06 6 – 6 = 0 0 x 0 = 05 5 – 6 = -1 -1 x -1 = +15 5 – 6 = -1 -1 x -1 = +14 4 – 6 = -2 -2 x -2 = +43 6 – 3 = -3 +3 x +3 = +9
Sum 0 28
![Page 12: Part II Sigma Freud and Descriptive Statistics Chapter 3 Vive La Différence: Understanding Variability](https://reader035.vdocument.in/reader035/viewer/2022081506/5697bfbd1a28abf838ca1cfc/html5/thumbnails/12.jpg)
Computing Standard Deviationby Hand
6. Divide the sum by n – 1
7. Compute the square root of 3.11
2( ) 28 283.11
1 10 1 9
X X
n
3.11 1.76SD
![Page 13: Part II Sigma Freud and Descriptive Statistics Chapter 3 Vive La Différence: Understanding Variability](https://reader035.vdocument.in/reader035/viewer/2022081506/5697bfbd1a28abf838ca1cfc/html5/thumbnails/13.jpg)
Using Excel’s STDEV.S Function
![Page 14: Part II Sigma Freud and Descriptive Statistics Chapter 3 Vive La Différence: Understanding Variability](https://reader035.vdocument.in/reader035/viewer/2022081506/5697bfbd1a28abf838ca1cfc/html5/thumbnails/14.jpg)
The Computation of the Standard Deviation Using the STDEV.S Function
Using Excel’s STDEV Function
![Page 15: Part II Sigma Freud and Descriptive Statistics Chapter 3 Vive La Différence: Understanding Variability](https://reader035.vdocument.in/reader035/viewer/2022081506/5697bfbd1a28abf838ca1cfc/html5/thumbnails/15.jpg)
Why n – 1?
• The standard deviation is intended to be an estimate of the POPULATION standard deviation– We want it to be an unbiased estimate– Subtracting 1 from n artificially increases the SD
• A conservative estimate of the population
![Page 16: Part II Sigma Freud and Descriptive Statistics Chapter 3 Vive La Différence: Understanding Variability](https://reader035.vdocument.in/reader035/viewer/2022081506/5697bfbd1a28abf838ca1cfc/html5/thumbnails/16.jpg)
Comparing the STDEV.S and STDEV.P Functions
![Page 17: Part II Sigma Freud and Descriptive Statistics Chapter 3 Vive La Différence: Understanding Variability](https://reader035.vdocument.in/reader035/viewer/2022081506/5697bfbd1a28abf838ca1cfc/html5/thumbnails/17.jpg)
Things to Remember…
• Standard deviation is the average distance from the mean
• The larger the standard deviation, the greater the variability
• Standard deviation is sensitive to extreme scores (it is just an Average after all)
![Page 18: Part II Sigma Freud and Descriptive Statistics Chapter 3 Vive La Différence: Understanding Variability](https://reader035.vdocument.in/reader035/viewer/2022081506/5697bfbd1a28abf838ca1cfc/html5/thumbnails/18.jpg)
Computing Variance
• Variance = standard deviation squared
![Page 19: Part II Sigma Freud and Descriptive Statistics Chapter 3 Vive La Différence: Understanding Variability](https://reader035.vdocument.in/reader035/viewer/2022081506/5697bfbd1a28abf838ca1cfc/html5/thumbnails/19.jpg)
Using Excel’s VAR.S Function
![Page 20: Part II Sigma Freud and Descriptive Statistics Chapter 3 Vive La Différence: Understanding Variability](https://reader035.vdocument.in/reader035/viewer/2022081506/5697bfbd1a28abf838ca1cfc/html5/thumbnails/20.jpg)
Comparing the VAR.S and VAR.P Functions
![Page 21: Part II Sigma Freud and Descriptive Statistics Chapter 3 Vive La Différence: Understanding Variability](https://reader035.vdocument.in/reader035/viewer/2022081506/5697bfbd1a28abf838ca1cfc/html5/thumbnails/21.jpg)
Standard Deviation or Variance
• Standard deviation is stated in original units• Variance is stated in units that are squared
• Which is easier to interpret???
![Page 22: Part II Sigma Freud and Descriptive Statistics Chapter 3 Vive La Différence: Understanding Variability](https://reader035.vdocument.in/reader035/viewer/2022081506/5697bfbd1a28abf838ca1cfc/html5/thumbnails/22.jpg)
Measures of variability help understand what a distribution of data points looks like.
Use to distinguish distributions from one another and describe a collection of data points.
Summary