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Statistical Inference L3, Bootstrap, L2, L1 progression Formal and informal Continuing implementation of new NCEA standards Team Solutions Steel • Hogan • Cathcart • McNaughton • Barks • Johnson
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Statistical Inference

Feb 25, 2016

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Statistical Inference. L3, Bootstrap, L2, L1 progression Formal and informal Continuing implementation of new NCEA standards Team Solutions Steel • Hogan • Cathcart • McNaughton • Barks • Johnson. What may happen in this session. Data Questions and PPDAC Bootstrap idea - PowerPoint PPT Presentation
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Page 1: Statistical Inference

Statistical InferenceL3, Bootstrap, L2, L1 progression

Formal and informal

Continuing implementation of new NCEA standards

Team SolutionsSteel • Hogan • Cathcart • McNaughton • Barks • Johnson

Page 2: Statistical Inference

What may happen in this session.• Data• Questions and PPDAC• Bootstrap idea• Bootstrap confidence interval• (CLT, normal and CI )• Contextual information• Census at School resources• Level 2, level 1, Year 9 and 10.

Page 3: Statistical Inference

What are we learning?

• The bootstrap idea and how it is used to make an inference (now called formal inference).

• The importance of contextual information for this standard 3.10

• A possible lesson sequence• How to justify √n• Where there are a lot of resources

Page 4: Statistical Inference

• The big idea of this standard is to make a useful inference from a sample about a population.

Data

Page 5: Statistical Inference

The Population• The only definite thing we know about the

population is we never know anything definite about the population!

• And there would be no need for statistics

• But, if we did, we could check to see if our statistical ways work. Let’s do that!

Page 6: Statistical Inference

The Vineyard

Page 7: Statistical Inference

ProblemBefore the harvest I want to estimate the total harvest weight reasonably accurately to plan processing.

The population is 10,000 bunches of grapes. There are 500 vines and each vine is managed to have 10 shoots and each shoot grows two bunches of grapes.

Page 8: Statistical Inference

The PlanThe plan is to pick a random sample of bunches and weigh each bunch. There are 13 rows 50m long so 6 random numbers between 1 and 650 were chosen.

The bunches of grapes in a metre long section were picked from the vines at these places and weighed.

Page 9: Statistical Inference

The Sample DataI have the weights of 212 bunches of grapes.

Page 10: Statistical Inference

AnalysisThe median weight is 87.5 grams.The IQR is 109 – 70.5 =38.5

So the Y12 median estimate for the vineyard is 87.5 ± 1.5 x 38.5/√212 =[83.5, 91.5]I am pretty sure confident that this interval will contain the median.

Page 11: Statistical Inference

ConclusionPopulation parameter median is very likely to be contained in this interval;[83.5, 91.5].

I am pretty sure the vineyard harvest will be between 835kg and 915kg. I have stainless vats for 800kg so there will be a small surplus which I can ferment in a 200L plastic drum.

Page 12: Statistical Inference

Bootstrap for a better estimateI have the weights of 212 bunches of grapes.

Page 13: Statistical Inference

Bootstrap

• The idea behind a bootstrap is to mimic the sample many times.

• This is best simulated.

• A computer is needed.

• The distributions of means/medians of all the mimic samples reflect the population.

Page 14: Statistical Inference

The distribution of 200 resamples of size 212.

Bootstrap, likely to be between 860kg to 945kg with 95% confidence.

Page 15: Statistical Inference

What controls the spread of the means?

• From the left, sample sizes 3, 5, 8, 12 and 40.

• Here I am varying the sample size.

Page 16: Statistical Inference

√n

0 5 10 15 20 25 30 35 40 450

10

20

30

40

50

60

70

80

f(x) = 125.406063050883 x -̂0.511925070490753R² = 0.964533465734864

width

Sample size

Spre

ad

Spread α 1/√(sample size)

Page 17: Statistical Inference

Key Ideas• List all the ideas of statistics Years 9 to 13

• Order the development of these

Page 18: Statistical Inference

Resources!• http://3rs.ccac.ca/en/research/reduction/experimental-de

sign.html • • http://www.corwin.com/upm-data/29173_Millsap___Cha

pter_2.pdf• http://curiouscat.com/bill/101doe.cfm• http://stattrek.com/experiments/what-is-an-experiment.a

spx• http://en.wikipedia.org/wiki/Design_of_experiments• http://webspace.ship.edu/cgboer/experiments.html• http://www.stat.auckland.ac.nz/~iase/publications/icots8/

ICOTS8_4B2_ENGEL..pdf• http://statistics.about.com/od/Applications/a/Example-Of-

Bootstrapping.htm• http://www.stat.rutgers.edu/home/mxie/rcpapers/bootstr

ap.pdf

Page 19: Statistical Inference

Resources!

Page 21: Statistical Inference

This is not the end, it is not even the beginning of the end, it is only the end of the beginning!

Puzzle time

Who on Earth said that and when?