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Simple Probability Problem • Imagine I randomly choose 2 people from this class. What is the probability that both are in the same laboratory section?

Simple Probability Problem

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Simple Probability Problem. Imagine I randomly choose 2 people from this class. What is the probability that both are in the same laboratory section?. (true mean). (sample mean). (sample variance). (true variance). Sample vs Population. Populations Parameters and Sample Statistics. - PowerPoint PPT Presentation

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Page 1: Simple Probability Problem

Simple Probability Problem

• Imagine I randomly choose 2 people from this class. What is the probability that both are in the same laboratory section?

Page 2: Simple Probability Problem

xx

2 2xS

(true mean)

(true variance)

(sample mean)

(sample variance)

Sample vs Population

Page 3: Simple Probability Problem

Populations Parameters and Sample Statistics

• Population parameters include its true mean, variance and standard deviation (square root of the variance):

2

1

2

1

)(1

lim

1lim

xxN

xN

x

N

iiN

N

iiN

• Sample statistics with statistical inference can be used to estimate their corresponding population parameters to within an uncertainty.

Page 4: Simple Probability Problem

Populations Parameters and Sample Statistics

• A sample is a finite-member representation of an ‘infinite’-member population.

• Sample statistics include its sample mean, variance and standard deviation (square root of the variance):

2

1

2

1

)(1

1

1

xxN

S

xN

x

N

iix

N

ii

Page 5: Simple Probability Problem

-100 -50 0 50 100 150 2000

500

1000

1500

2000

2500

3000

3500

4000

4500

Cou

nts

Values

SamplesDistribution

x

Normally Distributed Populationusing MATLAB’s command randtool

Page 6: Simple Probability Problem

xS

x

-100 -50 0 50 100 150 2000

2

4

6

8

10

12

14

16

18

Cou

nts

Values

SamplesDistribution

Random Sample of 50

Page 7: Simple Probability Problem

-100 -50 0 50 100 150 2000

5

10

15

20

25

Cou

nts

Values

SamplesDistribution

xx

xS

x

xS

x

Another Random Sample of 50

Page 8: Simple Probability Problem

The Histogram

10 digital values: 1.5, 1.0, 2.5, 4.0, 3.5, 2.0, 2.5, 3.0, 2.5 and 0.5 V

resorted in order: 0.5, 1.0, 1.5, 2.0, 2.5, 2.5, 2.5, 3.0, 3.5, 4.0 V

Time record Histogram of digital data

N = 9 occurrences; j = 8 cells; nj = occurrences in j-th cell

The histogram is a plot of nj (ordinate) versus magnitude (abscissa).

Figure 7.3 Figure 7.4

analog,discrete, and digital signals

Page 9: Simple Probability Problem

Proper Choice of Δx

High K small Δx The choice of Δx is critical to the interpretation of the histogram.

Figure 7.5

Page 10: Simple Probability Problem

Histogram Construction Rules

To construct equal-width histograms:

1. Identify the minimum and maximum values of x and its range

where xrange = xmax – xmin.

2. Determine K class intervals (usually use K = 1.15N1/3).

3. Calculate Δx = xrange / K.

4. Determine nj (j = 1 to K) in each Δx interval. Note ∑nj = N.

5. Check that nj > 5 AND Δx ≥ Ux.

6. Plot nj versus xmj,where xmj is the midpoint value of each interval.

Page 11: Simple Probability Problem

Figure 7.7

Frequency DistributionThe frequency distribution is a plot of nj /N versus magnitude. It is very similar to the histogram.

Page 12: Simple Probability Problem

Histograms and Frequency Distributions in LabVIEW

‘digital’case

‘continuous’case