98% of all statistics are made up…

98% of all statistics are made up…

AMA Stats Day 2008Louise AddisonTeam Solutions

AMA Stats Day 2008Louise AddisonTeam Solutions

Statistical literacy in the new curriculumStatistical literacy in the new curriculum

Compare and Contrast itCompare and Contrast it

For your curriculum level compare and contrast the statistical literacy strands to identify what is:Only in oldIn bothOnly in new

Looking at progressionsLooking at progressions

L3 Evaluate the effectiveness of different displays in representing the findings of a statistical investigation or probability activity undertaken by others.

L4 Evaluate statements made by others about the findings of statistical investigations and probability activities.

L5 Evaluate statistical investigations or probability activities undertaken by others, including data collection methods, choice of measures, and validity of findings.

L6 Evaluate statistical reports in the media by relating the displays, statistics, processes, and probabilities used to the claims made.

EvaluationEvaluation

LEVEL

E

V

A

L

U

A

T

E

What? Source? Criteria?

3

4

5

6

EvaluationEvaluation

LEVEL

E

V

A

L

U

A

T

E

What? Source? Criteria?

3 Effectiveness of different displays

Undertaken by others

Representing the findings of a statistical investigation or probability activity

4 StatementsMade by others

Findings

5Statistical

Investigations or Probability Activities

Undertaken by others

Data collection methods Choice of measures Validity of findings

6 Statistical ReportsIn the media

Displays Statistics Processes

Probabilities Claims

Exploration 1: Sources

What are your thoughts…

ARE YOU

Compare and contrastCompare and contrast

Your thoughts Your partner’s thoughts Students’ thoughts

Newspaper ArticleNewspaper Article

Parents can predict their children's exam performance simply by looking at their hands, according to research. Psychologists claim that results in English and maths tests are linked to the length of fingers. Pupils with longer ring fingers are said to be more likely to excel in numeracy while those with shorter ring fingers tend to be more adept at literacy.

www.dailymail.co.uk/news/article-456994/Length-fingers-pupil-maths-English.html

Press ReleasePress Release

Finger length helps predict SAT exam results, study shows.

The results of numeracy and literacy tests for seven-year-old children can be predicted by measuring the length of their fingers, shows new research.

In a study to be published in the British Journal of Psychology, scientists compared the finger lengths of 75 children with their Standardised Assessment Test (SAT) scores.

They found a clear link between a child’s performance in numeracy and literacy tests and the relative lengths of their index (pointing) and ring fingers.

Scientists believe that the link is caused by different levels of the hormones testosterone and oestrogen in the womb – and the effect they have on both brain development and finger length.

Journal ArticleJournal Article

A great deal of recent research has focused upon the relationship between a hypothesized index of prenatal testosterone exposure, digit ratio and health, social and cognitive functioning. Many inconsistencies within the pattern of findings have been identified in the relationship between digit ratio and absolute levels of cognitive ability. Recent research has identified a relationship between digit ratio and basic numeric competency. This basic numerical competency has been argued to be influenced by biological factors. The present study extended this finding to academic assessment, namely the Standardized Assessment Tests undertaken in numeracy and literacy by children in the UK at the age of 7. The present study hypothesized that digit ratio would correlate with the relative difference between numeracy and literacy abilities. Digit ratios were calculated for 75 (mainly Caucasian) children aged between 6 and 7 attending a state funded infant school. The digit ratios were then correlated with the results from their National Standard Assessment Tests(SATs). A significant correlation was found as hypothesized.

Compare and contrastCompare and contrast

Image Article Press Release

Journal Article

Exploration 2: Visual statistics

Where is our zoom?Where is our zoom?

Who am I?Who am I?

An artistic detour…

Artist: Chris Jordan

www.ted.com

www.chrisjordan.com

QuickTime™ and aTIFF (Uncompressed) decompressor

are needed to see this picture.

what

am i ?

View 2

Depicts one million plastic cups, the number used on airline flights in the US every six hours.

Hungry PlanetHungry Planet

For your photo write

5 “I notice” and

5 “I wonder” statements…

I notice, I wonderI notice, I wonder

I notice -

Disagree / Agree - Reason / Explanation

I wonder -

Statement / Evidence / Explanation

Looking at the dataLooking at the data BHUTAN

Population 2185569 People per sq. mile 121 Population

Density People per sq. km 47 Sq. miles 18142

Total Area Sq. km 46988

Population in Urban areas

Percent 9

Human Development Report Index

53.6

Fertility Rate Tota l births per woman 5.0

Male 56.2 Literacy Percent

Female 28.1 USD$ 695

Income Annual

per capita PPP 1300

USD$ 9 Health Care Expenditure

Annual per

capita % o f GDP 3.9 Physicians Per 100 000 p eople 5

Access to safe water

Percent 62

Access to safe sanitation

Percent 70

Caloric Intake Daily, per capita, kcal n/a kcal n/a Caloric Supply from

animal products

Daily, per

capita % o f total n/a Male 60.2

Life Expectancy Female 62.4

Under-nourished Percent, 2001 n/a

Male 34.0 Overweight Percent

Female 44.7 Male 5.3

Obese Percent Female 13.1

Diabetics Percent, >20 years old 3.5

Total 0 Number of McDonalds Per million people 0

lbs. 6.6 Meat Consumption

Annual, per

capita kg 3.0 lbs. n/a Sugar and

Sweetener Supply

Annual, per

capita kg n/a

qts. 0.6 Alcohol comsumption

Annual, per

capita litres 0.6

Cigarette consumption

Annual per capita total n/a

Male n/a Smokers

Percent, age 18+ Female n/a

In Shing kh ey, a rem ot e h illside village o f

a doz e n h om es, Nal im a nd N a mg a y’s fami ly a s se mbl e s in the pr a yer roo m of th eir th ree - s to ry ram m e d - ear th ho use with o ne wee k’s wor th of f o od for their

ex ten ded fami ly of thi r te e n. Coo kin g m et ho d : cla y s to ve fueled by w o od fire.

Foo d pr e serv a tion : na tural dry ing . Fami ly m e m b ers (le ft to righ t, s ta nd ing ): San g a y Ka ndu (3 9, h usb a nd o f Sa ng a y), Sang a y, 35, h old ing Tan di n Wa ng ch uk (7 m ont hs ), Sa ng a y Za m ( 1 2, d a ug hter of Sang a y Kan d u a n d Sa ng a y), Ch at o

Na mga y (1 4, m on k, so n of Sang a y Kan d u a nd Sa ng a y), Cha to Gel ts hin (1 2, so n o f Sa ng a y Ka nd u an d Sa ng a y), (le ft to righ t, s eat e d): Ze ko m (9, d a ugh ter of Nal im a nd N a mg a y), Ba ng a m (al s o cal led

Kinle y, 21, dau gh ter of Nal im a nd Na mga y), Dr u p C hu (5 6, b ro th er o f Nal im) , Ch oe d en (1 6, d a ugh ter of

Sang a y Ka ndu a n d Sa ng a y), Na lim (5 3, fami ly m a triar ch a nd wife of N a mg a y),

Na m ga y (5 7, fa mi ly patria rch a n d h usb a nd of Nal im ), Ge lts h in (9, s o n of

Sang a y Ka ndu a n d Sa ng a y).

Namgay Family

Town / City / Village

Sh ingk he y Village

Village Population 96

Country Bhutan Family Members 13 Adults 1 8+ 6 Children 3 - 17 6 Infants 0 - 2 1 Grains and O ther Starchy Foods

0.25

Dairy Meat, Fish & Eggs 0.08 Frui ts, Vegetables & Nuts

1.46

Condiments 1.27 Snacks and Desser ts

Prepared Foods

Fast Food

Be v erages 0.76 Miscellaneous 1.21 Expenditure 5.03 Expenditure 224.93 Local Currency Ngu ltrum Local Market Value of homegrown food

29.06

AUSTRALIA

Population 19913144 People per sq. mile 7

Population Density People per sq. km 3

Sq. miles 2967124 Total Area

Sq. km 7684816 Population in Urban

areas Percent 92

Human Development Report Index

94.6

Fertility Rate Tota l births per

woman 1.7

Male 100.0 Literacy Percent Femal

e 100.0

USD$ 20822 I ncome

Annual per capita PPP 28260

USD$ 1741 Health Care Expenditure

Annual per capita % o f

GDP 9.2

Physicians Per 100 000 p eople 247

Access to safe water Percent 100

Access to safe sanitation

Percent 100

Caloric I ntake Daily, per capita,

kcal 3054

kcal 1032 Caloric Supply from animal products

Daily, per capita % o f

total 33.8

Male 77.9 Life Expectancy

Female 83 Under-nourished Percent, 2001 n/a

Male 69.7 Overweight Percent Femal

e 60.2

Male 21.2 Obese Percent Femal

e 22.5

Diabetics Percent, >20 years

old 6.8

Total 726 Number of McDonalds Per million people 36.46

lbs. 207 Meat Consumption

Annual, per capita kg 93.9

lbs. 106.04 Sugar and Sweetener Supply

Annual, per capita kg 48.1

qts. 10.9 Alcohol comsumption

Annual, per capita litres 10.3

Cigarette consumption

Annual per capita total 1907

Male 30.7 Smokers

Percent, age 18+ Female 23.1

The Molloy fa mily —Joh n , 43 , Natalie, 4 1 , Emil y, 15 (calle d

Em), and S e an , 5 (we aring his school uniform ,

includ ing a h at for s u n protection) —on the backyard

patio by their pool in Brisbane, o n Australia’s east coast, with on e we e k’s worth of food, i n Jan uar y. Cookin g methods: stov e , microwa ve , and outdoor BB Q grill. Food preservation: r e frige rator -fre e zer . Fa vorite foods —

John: prawns and chocolate . Natalie: fres h fruits and

chees e . Emil y: Mexican food and ho m emad e dips. Sean :

spaghetti Bolog n ese and lollies.

Malloy Family

To w n / City / V illa g e Brisb an e

To w n / City / V illa g e Po p u lat io n

15 0 8 1 61

Co u n t ry Au s t ra lia

Fa mi ly Me m be rs 4

Adul t s 1 8+ 2

Chil dr e n 3 - 17 2

I nfa nts 0 - 2 0

Gra in s a nd Othe r St ar ch y F o o d s

24 . 76

Da iry 19 . 01

Me at, Fis h & Eg g s 84 . 31

Fru its , Ve g e t ab le s & Nu t s

66 . 78

Co n d im en t s 23 . 50

S na ck s a nd D e ss er t s 17 . 67

Pre pa re d F o o d s 3. 2 9

Fa st Food

Be ver ag e s 63 . 94

Misc el la n eo us 0. 4 9

Ex pe ndi tu re 30 3 .7 5

Ex pe ndi tu re 38 8 .2 2

Lo c a l Cu rre ncy Au s Dollar s

Exploration 3 - WHO Stats

Life ExpectancyLife Expectancy

Life Expectancy at birth (years)Life Expectancy at birth (years)

Rational for use Definition Associate terms Data Sources Methods of Estimation Disaggregation

Life expectancy at birth (years)Life expectancy at birth (years)

Rationale for use Life expectancy at birth reflects the overall mortality level of a

population. It summarizes the mortality pattern that prevails across all age groups - children and adolescents, adults and the elderly.Definition

Average number of years that a newborn is expected to live if current mortality rates continue to apply.Associated terms

A life table presents a set of tabulations that describe the probability of dying, the death rate and the number of survivors for each age or age group. Accordingly, life expectancy at birth is an output of a life table.Data sources

Vital registration, census and surveys: Age-specific mortality rates required to compute life expectancy at birth.

Methods of estimation WHO has developed a model life table based on about 1800 life

tables from vital registration judged to be of good quality. For countries with vital registration, the level of completeness of

recorded mortality data in the population is assessed and mortality rates are adjusted accordingly. Where vital registration data for 2003 were available, these were used directly to construct the life table. For countries where the information system provided a time series of annual life tables, parameters from the life table were projected using a weighted regression model, giving more weight to recent years. Projected values of the two life table parameters were then applied to the modified logit life table model, where the most recent national data provided an age pattern, to predict the full life table for 2003.In case of inadequate sources of age-specific mortality rates, the life table is derived from estimated under-5 mortality rates and adult mortality rates that are applied to a global standard (defined as the average of all the 1800 life tables) using a modified logit model.

Disaggregation By sex, location (urban/rural, major regions/provinces). Comments The lack of complete and reliable mortality data, especially

for low income countries and particularly on mortality among adults and the elderly, necessitates the application of modelling (based on data from other populations) to estimate life expectancy. WHO uses a standard method as explained above to estimate and project life tables for all Member States using comparable data. This may lead to minor differences compared with official life tables prepared by Member States.

Stating the obviousStating the obvious

What conclusions would you like students to draw from the following graphs?

What questions would you like them to ask?

LinksLinks

http://www.who.int/whosis/whostat2007_10highlights.pdf

WHO – WHO Statistical Information System reports for 2005 - 2008

http://www.who.int/whosis/en/

Exploration 4 -THINKits

CONNECT IT

Are there any relationships

and / or connections

you can see in the data?

USE IT

What could you use this

data to show?

KEY IDEAS OF IT

What conclusions can you draw

from this data? WHERE IS IT GOING

What can you

extrapolate from this data?

REMEMBER IT

What is memorable about this

dat a?

CREATE IT

Create a s tory to describe

what yo u see in the data.

COMPARE &

CONTRAST IT

What is another data set that you

co uld com pare / contrast w ith this dat a se t?

EXPLAIN IT

Describe what you s ee in the

data.

PLAN IT

Use t he PPDAC cycle to

analys e this data.

LOOK AT IT

ANOTHER WAY

What does t his data not show?

REFLECT ON IT

What have yo u learnt from

analys ing this dat a?

BRAINSTORM IT

What do yo u not ice?

POS ITIVES &

NEGATIVES

OF IT

What are the limitati ons / just ifica tions of this dat a?

DISSEC T IT

What is t he so urce of this

dat a?

EVALUATE IT

How reliabl e is this dat a?

QUESTION IT

What ques tions

does this data answer? What

ques tions does it rais e?

Exploration 5 - What do the following quotes and cartoons say about statistics?

The scholarship studentThe scholarship student

Which of these relate to statistical literacy?

KC’sKC’s

KC’sKC’s

StrandsStrands

The end…The end…

Resources / Links:

www.aucksecmaths.wikispaces.com as of early next week :)

Email:

l.addison@auckland.ac.nz