Support for School Statistics from Statistics NZ

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Support for School Statisticsfrom Statistics NZ

mike.camden@stats.co.nzStatistics New Zealand

Auckland Maths Assoc, University of AucklandTue 25 Nov 08

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Achievement objectives for today:

Participants will:Use Stats NZ resources to

deliver curriculum objectivesFeel more confident and have more fun

with teaching the stats in Mathematics and Statistics in the NZ Curriculum

Find out (if time)what do (some Stats NZ) statisticians really do!

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Activities with www.stats.govt.nz:After an introductory ramble:Schools corner

StatZing!SURFs 1, 2, 3CensusAtSchool (a mention)

Table Builder (= TB); esp Census dataInfoshare:

Time series galoreHot Off The Presses (= HOTPs):

HOTPs and Statistical LiteracyQuickStats:

about your place etcThen: what do (some) statisticians really do!

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Curriculum and Stats NZ Resources 1:

The threads in the Stats and Probability strand:Statistical investigation

phenomena involving: multivariate (case) datasets time-series datasets

Statistical literacyreports with words, numbers, graphsrisk

Probabilitydistributionsdependence etc

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Curriculum and Stats NZ Resources 2:The threads … and resources for them:Statistical investigation Schools Corner,StatZing!

phenomena involving: HOTPs multivariate (case) datasets: SURFs,TB,CaS

time-series datasets: InfoshareStatistical literacy NZ in Profile

reports with Quickstats words, numbers, graphs: HOTPsrisk, relative risk: HOTPs, Tables

Probabilitydistributions: Tables dependence etc: Tables; 2 way

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Curriculum and Stats NZ Resources 3:Some are

designed for schoolsSome are

(a big one) inadvertently useful for schools!EG: The HOTPs (Hot Off The Presses):EG: a rich source of real (we hope) info:

New Zealand Income Survey: June 2008 quarter (a big one) Highlights  |  Commentary  |  Technical notes  |  Erratum  |  Tables  | 

Stat Literacy: Evaluate stat reports (L 6,7,8)

Statistical Enquiry Cycle: PPDAC … PPDAC … PPDAC … PPDAC … PPDAC …

Stat investigation: Story, Data Time series

Stat investigation: Methodology: defining questions, sampling methods, errors (samp and non) etc etc etc etc

Probability: One-way tables Two-way tables

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Why be nice to schools??Stats NZ: The World:

We need our clients to be informed & positiveSchool stats is a vital way to achieve this

Respondents: People Businesses

Users: Public Professional Technical

Dataset

Data

Information

DatasetDataset

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Two groups with converging interests:

TheOfficial Stats

sectorThe

Mathematics and Statistics Education Community

Vision: an informed society using statistics.

Curriculum: students will be: thinking mathematically and statistically; solving problems, modelling situations.

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A small problem:Unit-record multivariate datasets:Teachers need them!Official Stats agencies have lots but can’t release them!

Some smart solutions:CensusAtSchool (sort-of)SURFs for Schools: 1, 2, 3Tables by geographical Area

DatasetDataset

Dataset

SURF 1

SURF 2

SURF 3

Area Unit Males06 Females06 Tot06Henderson North 2,487 2,817 5,304Henderson South 1,956 2,070 4,023Tangutu 1,404 1,554 2,955Woodglen 2,013 2,193 4,203Glen Eden East 3,237 3,372 6,609New Lynn North 1,173 1,233 2,406New Lynn South 1,185 1,287 2,472

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Census at school 2009New dates:

3 March 2009 until 9 April 2009Register online:

http://www.censusatschool.org.nz/2007/register/If you have previously registered, OK.

Confirmation in November.Funded:

X% by Stats NZ(1-X)% by MoE

Expertise:Lots of it; from UoA

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New for 2009Teachers get their class results back

if they choose.Early in year so 2009 data

can be used for 2009 teaching.New questions: from consultations:

Dept of Stats UoA, MoE, Stats NZ, teachers nationwideQuestionnaire critiqued

by StatsNZ Questionnaire design team

www.censusatschool.org.nz

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1 Schools Corner: StatZing!, SURFs

2 Table Builder

3 Infoshare4 Releases by title: HOTPs

5 QuickStats

www.stats.govt.nz

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Find Info by/f

or …

StatZing! Latest Sec (Economics)

SURF 2

SURFs

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SURFs for Schools

Synthetic Unit Record Files:Multivariate datasets from Stats NZ surveys

1. Income supplement from the 2004 Household Labour Force Survey

2. 2001 Household Savings Survey3. Coming soon – 2006 Census

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2001 Household Savings Survey SURF

Based on a survey that collected information including income, assests, debt,net worth.

300 synthetic people representing the 5000+ people who responded to the survey.

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2001 Household Savings Survey SURF

Variables include:

–Gender–Employment–Qualification–Ethnicity–Partnered–Age

–Age of Partner –Total income–Wages/Salary income–Total debt–Total networth

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19

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Using the SURF

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Teacher page for each activity

•Curriculum links

•Possible answers

•Available as a PDF document

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What can we improve?

For teachers For students

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Census: SURF 3

Under development; final checkingBased on

2006 Census of Population and DwellingsContains unit record datasets for each of New

Zealand’s 16 main Regional Authorities300 synthetic people who represent everyone

that responded for each region

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Census: SURF 3Variables included

– Sex – Work and Labour force status– Qualification– Ethnicity– Income– Age Group– Mode of transport to work– Hours worked– Cigarette smoking behaviour– Access to a cellphone/mobile phone– Access to the internet

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Preserved relationships

Variable Pers

onal

Inco

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Wor

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stat

us

Sex

Qua

lific

atio

n –

high

est

Mai

n m

eans

of

trave

l to

wor

k

Hour

s w

orke

d in

em

ploy

men

t per

w

eek

Ethn

icity

Ciga

rette

sm

okin

g be

havi

our

Age

Acce

ss to

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rnet

Acce

ss to

a

Cellp

hone

/Mob

ile

Phon

e

Access to a Cellphone/Mobile Phone x x xAccess to internet x x xAge x x x x x x xCigarette smoking behaviour x xEthnicity x x x x xHours worked in employment per week xMain means of travel to work xQualification – highest x x xSex x xWork and labour force status

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Limitations: SURF 3: Census

Synthetic dataNot all relationships and patterns are preservedJoining tables together

does not represent the whole of New Zealand

However, you can compare regions!

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Battle for the ‘greener suburb’:an example using case data

Compare the ‘traveling to work’ habits of geographic areas.Which area has the ‘greener’ workers?

– Walking / Running / Cycling– Public transport– Carpooling???– Working at home?

(Graphic from CensusAtSchool)

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Battle for the ‘greener suburb’:where to find the data

We want a data source that contains information about modes of travel to work by area units.

Luckily, we have the 2006 Census of Population and Dwellings on Table Builder!

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2 Table Builder

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2006 Pop Census

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Selected tables

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Age by Sex; soon …

Trav

el to

Wor

k

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35

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40

41

42

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Counts: People by City of usual residence,

Main Means of Travel to Work: 2006 Census

0 50,000 100,000

Worked at Home

Did Not Go To Work Today

Drove a Private Car, Truckor Van

Drove a Company Car,Truck or Van

Passenger in a Car, Truck,Van or Company Bus

Public Bus

Train

Motor Cycle or Pow erCycle

Bicycle

Walked or Jogged

Other

Not Elsew here Included

Manukau City

Auckland City

Waitakere City

North Shore City

Travel to work in the four Auckland cities

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Travel to work in Kapiti and Wellington

0%

10%

20%

30%

40%

50%

Worked atHome

Did Not GoTo WorkToday

Drove aPrivate Car,Truck or Van

Drove aCompanyCar, Truck

or Van

Passengerin a Car,

Truck, Vanor Company

Bus

Public Bus Train Motor Cycleor Power

Cycle

Bicycle Walked orJogged

Other NotElsewhereIncluded

Kapiti Coast District

Wellington City

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Table Builder: Datasets on Area Units:Population: Census 2006 vs

Population: Census 2001for Area Units of Waitakere City

0

2000

4000

6000

8000

0 2000 4000 6000 8000

Sturges North

Here's data for 10 Area Units:Area Unit Tot01 Tot06Sturges North 2283 5772Kingdale 3480 3537Fairdene 4410 4554Whenuapai West 1836 1842Herald 1656 1698Hobsonville 3342 3378Westgate 705 1092Royal Road West 2424 2664West Harbour 4569 4932Lucken Point 4656 5238

At this pointthe screen-shotsstop.But there’s a2-slide summary …

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www.stats.govt.nz for schools: short guide: p1Schools Corner SURF (No. 2) About the data source | The dataset | Activities

(copy the dataset and paste into your spreadsheet) StatZing! (the latest Activities) Find by …(find old StatZing!s etc)Table Builder 2006 Population Census Selected tables Travel to Work Expand (find the Areas you want)

Tick (use the ticks above and to left) Click the Table icon Actions, download to XL format (then copy and paste into your spreadsheet package) Age by Sex for 1996, 2001, 2006 (then as above)

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www.stats.govt.nz for schools: short guide: p2Infoshare Browse Work, Income and Spending Linked Employer-Employee Dataset Age and ANZIC96 (ANZ Industry Classification 1996) Select a few items, and for Time, Select All Go Pivot clockwise, to get data into a column Save as xls (copy the dataset and paste into your spreadsheet)Releases by Title (Takes you to Hot Off The Presses) NZ Income Survey NZ Income Survey; June 2008 (then explore these:) Highlights|Commentary|Technical notes|Erratum|Tables QuickStats about a Place(and also see QuickStats about a Subject, and NZ in Profile) Place List (and find your suburb) (and use the 12 tabs).

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What Statisticians do all day: an eg:The new Immigration Survey:

Pop: 36,620 approved immigrants in 2004Sample: 7,125 of them

We find Estimates (via ‘resampling’) with Sample Errors (= half the confidence interval)

Immigration survey: Labour Force ActivityLabour force status:Employed Looking for work

Immigration approval category Number Samp err Number Samp errSkilled Primary Applicant 11,630 510 220 90Skilled Secondary Applicant 5,130 350 410 130Business 1,210 100 40 30Family partner 4,770 150 240 80Pacific 1,120 160 70 10Notes: This is an example: values are not necessarily the actual ones. table is incomplete Samp Err is sample error: approximately 2 times the standard error found by jackknife. Number is the estimate, from the sample, o of the total number of people in the cell, for the population studied. The confidence interval for the estimate is: Number ± Sample error.

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Sample Error vs Estimate:

Sample Error vs Estimatefor cells from a LISNZ table

jackknife

0

100

200

300

0 1000 2000

Hmmmmmm: what does that show?

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Sample Error (up) vs Estimate (across):Sample Error vs Estimatefor cells from a LISNZ table

jackknife, binomial 1

0

100

200

300

0 1000 2000

Sample error has lots of variation: Can we explain some of it? How? What function might it fit? For the lower (blue) points, what did we forget?

Standard Deviationfrom binomial model = √ (p (1-p) N)

Sample Error fromthe data by Jackknife(ie resampling)

For cells from the Immigration Survey NZ

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Some consultation:

We asked Pat: You need to multiply by the 2 value:Sample Error = z * Standard Error = 1.96 * Standard Error

They forgot to multiply by 2

(or 2 ish)

Why are they so dumb in Wellington??

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Sample Error vs Estimate:

Sample Error vs Estimatefor cells from a LISNZ table

Jackknife, binomial 2

0

100

200

300

0 1000 2000

Hmmmmmm: how does that look?

Sample Error fromthe data by Jackknife(ie resampling)

Sample Errorfrom binomial model = z * √ (p (1-p) N)

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To confidentialise, we added noise: ± 4

Sample Error vs Estimatefor cells from a LISNZ table

jackknife

0

100

200

300

0 1000 2000

Noise fromconfidentialising is about this big:

Noise from samplingvaries, but is this big

Does the noise from confidentialising matter?

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What do we do all day?

In a Stats office In a Stats classroom

Find a problem that mattersFind some Data (Evidence)Talk, scratch headsDo some graphsTry models using MathsMake mistakesConsult with wise headsDo more graphsMake decisionsCommunicate results in: words, numbers, graphs

Find a problem that mattersFind some Data (Evidence)Talk, scratch headsDo some graphsTry models using MathsMake mistakesConsult with wise headsDo more graphsMake decisionsCommunicate results in: words, numbers, graphs

We hope you enjoy statistical discovery as we do!!

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Gender Balance in Waitakere:

Females vs Males for Area Units of Waitakere Cit

2006 Census

0

1000

2000

3000

0 1000 2000 3000

Y+X line

Herald

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The Maths and Stats teacher’s vital role:If the next cohorts of adults

can handle statistical evidence and thinking:That’ll be nice for Statistics NZ!

which produces: social, economic and environmental stats

That’s utterly essential for solutions to NZ’s and the Earth’s challenges.

Enjoy!!