Loading in 2 Seconds...

Those who don’t know statistics are condemned to reinvent it… David Freedman

Loading in 2 Seconds...

- 105 Views
- Uploaded on

Download Presentation
## PowerPoint Slideshow about 'Those who don’t know statistics are condemned to reinvent it… David Freedman' - lazzaro

**An Image/Link below is provided (as is) to download presentation**

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript

### Those who don’t know statistics are condemned to reinvent it… David Freedman

### Plotting a histogram:endpoint convention, plot frequencies, make equal intervals etc.

1### Distribution of No of Graphics on web pages (N=1873)

400

300

200

100

0

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

5.0

15.0

25.0

35.0

45.0

55.0

65.0

75.0

85.0

95.0

Mean = 17.93

Median = 16.00

Std. Dev = 17.92

N = 1873

Graphic Count

3### Distribution of Redundant Link % on web pages (N =1861)

1000

800

600

400

200

0

0.0

40.0

80.0

160.0

400.0

200.0

240.0

120.0

280.0

360.0

440.0

320.0

480.0

Mean = 22.1

Median = 14

Std. Dev = 37.33

N = 1861.00

5

1000/ .5

800/ .4

600/ .3

400/ .2

200/ .1

0/ 0

1

3

5

7

9

11

13

15

Frequency

110

430

860

280

180

40

20

10

Probability

.06

.22

.45

.15

.09

.02

.01

.01

No of fonts used on a web-pageFrequency

/probability

1600### Distribution of word count (N=1903)

1400

1200

1000

800

600

400

200

0

0.0

4000.0

2000.0

6000.0

8000.0

18000.0

12000.0

16000.0

10000.0

14000.0

20000.0

Mean = 393.2

Median = 223

Std. Dev = 725.24

Minimum = 0

Maximum = 20,357

7### Distribution of word count (N=1897) top six removed

800

600

400

200

0

0.0

800.0

400.0

1200.0

2000.0

3200.0

1600.0

2400.0

2800.0

3600.0

4000.0

Mean = 368.0

Median = 223

Std. Dev = 474.04

Minimum = 0

Maximum = 4132

500### Distribution of word count (N=1873)

400

300

200

100

0

0.0

800.0

400.0

600.0

200.0

1600.0

1000.0

2200.0

2400.0

1400.0

1800.0

1200.0

2000.0

Mean = 333.4

Median = 220

Std. Dev = 360.30

Minimum = 0

Maximum = 4132

WORDCNT2

8### Distribution of link count on good & bad web-pages

3

0

0

2

0

0

1

0

0

0

0

.

0

4

0

.

0

8

0

.

0

1

2

0

.

0

1

6

0

.

0

2

0

0

.

0

2

4

0

.

0

2

8

0

.

0

Good Sites

Bad Sites

9Making inferences from histograms: Incidence of riots and temperature

3

0

4

0

9

0

1

0

0

1

1

0

5

0

6

0

7

0

8

0

temperature

Mean and Median

Mean is arithmetic average, median is 50% point

Mean is point where graph balances

- Mean shifts around,
- Median does not shift much, is more stable
- Computing Median:
- for odd numbered N
- find middle number
- For even numbered N
- interpolate between middle 2,
- e.g. if it is 7 and 9, then 8 is the median

The SD says how far away numbers

on a list are from their average.

Most entries on the list will be

somewhere around one SD away

from the average. Very few will be

more than two or three SD’s away.

Understanding the standard deviation

Lets start with a list: 1, 2, 2, 3

50%

25%

0%

Histogram is symmetric about 2,

2 is mean,

and 50% to left of 2, 50% to right

50%

25%

0%

List: 1, 2, 2, 3

Average = 2

SD = .8

50%

List: 1, 2, 2, 5

Average =2.5

SD = 1.73

25%

0%

50%

List: 1, 2, 2, 7

Average =3

SD = 2.71

25%

0%

Computing the standard deviation

List: 20, 10, 15, 15

Average = 15

Find deviations from average=

5, -5, 0, 0

Square the deviations:

(5)2 (-5)2 (0)2 (0)2 = 50

divide it by N-1 = 50/3 = 16.67

Square root it= 16.67 = 4.08

Properties of the standard deviation

- The standard deviation is in the same units as the mean
- The standard deviation is inversely related to sample size (therefore as a measure of spread it is biased)
- In normally distributed data 68% of the sample lies within 1 SD

Properties of the Normal Probability Curve

- The graph is symmetric about the mean (the part to the right is a mirror image of the part to the left)
- The total area under the curve equals 100%
- Curve is always above horizontal axis
- Appears to stop after a certain point (the curve gets really low)

11

1 SD= 68%

2 SD = 95%

3 SD= 99.7%

- The graph is symmetric about the mean =
- The total area under the curve equals 100%
- Mean to 1 SD = +- 68%
- Mean to 2 SD = +- 95%
- Mean to 3 SD = +- 99.7%
- You can disregard rest of curve

12

500

400

300

200

100

0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

10.0

Distribution of judges ratings for the Webby AwardsMean = 6.3

Median = 6.3

Std. Dev = 1.98

N = 1867.00

Skewness = -.43

Kurtosis = -.201

It is a remarkable fact that many histograms in real life tend to follow the Normal Curve.

For such histograms, the mean and SD are good summary statistics.

The average pins down the center, while the SD gives the spread.

For histogram which do not follow the normal Curve, the mean and SD are not good summary statistics.

What when the histogram is not normal ...

13

500

400

300

200

100

0

0.0

200.0

800.0

400.0

600.0

2800.0

1000.0

1200.0

1600.0

1800.0

2600.0

1400.0

2000.0

2200.0

2400.0

Distribution of word count on web pages

Std. Dev = 384.83

Mean = 348.3

+- 3 SD = (384 * 3) = 1152

Mean - 1152 = about 30% sample had negative number of links

When SD is influenced by outliers

Use inter quartile range

75th percentile - 25th percentile

Note.

A percentile is a score below which a certain % of sample is

14Measures of Normality

- Visual examination
- Skewness: measure of symmetry

Symmetric

Positively Skewed

Negatively Skewed

15Kurtosis: Does it cluster in the middle?

- Kurtosis is based on a distributions tail.
- Distributions with a large tail: leptokurtic
- Distributions with a small tail: platykurtic
- Distributions with a normal tail: mesokurtic

Large tail

Small tail

Normal Tail

1600### Positively Skewed and Leptokurtic: Word Count

1400

1200

1000

800

600

400

200

0

0.0

2000.0

4000.0

6000.0

8000.0

14000.0

16000.0

20000.0

10000.0

12000.0

18000.0

Mean = 393.2

Median = 223

Std. Dev = 725.24

Skewness = 13.62

Kurtosis = 321.84

N = 1903.00

800### Distribution of word count (N=1897) top six removed

600

400

200

0

0.0

800.0

400.0

1200.0

2000.0

3200.0

1600.0

2400.0

2800.0

3600.0

4000.0

Kurtosis = 16.40

Skewness = 3.49

Mean = 368.0

Median = 223

Std. Dev = 474.04

N = 1897.00

Degree of Freedom

- The number of independent pieces of information remaining after estimating one or more parameters
- Example: List= 1, 2, 3, 4 Average= 2.5
- For average to remain the same three of the numbers can be anything you want, fourth is fixed
- New List = 1, 5, 2.5, __ Average = 2.5

Download Presentation

Connecting to Server..