SURFing with Statistics New Zealand

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SURFing with Statistics New Zealand. Statistics Teachers' Day 30 November 2007. Nathaniel Pihama and Deborah Brunning Statistics New Zealand. What you will see today. SURF for Schools The Statistics New Zealand website Table Builder ..and some ideas on how to use them!. - PowerPoint PPT Presentation

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SURFing with Statistics New Zealand

Nathaniel Pihama and Deborah Brunning

Statistics New Zealand

Statistics Teachers' Day30 November 2007

What you will see today

• SURF for Schools

• The Statistics New Zealand website

• Table Builder

..and some ideas on how to use them!

The First SURF: a Synthetic Unit Record File for Schools

Overview:

• Confidentiality – Big Picture

• SURF???– What is it?– How and why did we make a SURF?

• What teachers and students can do with the SURF

What is a Unit Record File?

Other names• Data set• Unit Record Data set• Microdata

Example: A Dataset:Name Gender No.Sibs Age;yrsAmy F 1 14Ben M 2 13Cher F 1 15

Confidentiality

Safe

UnsafeUseless Useful

The pocket

Raw dataset

Non release

Confidentialised Unit Record Files

Confidentiality methods include:Categorical Data• Global recoding• Local recoding

• Numerical Data • top/bottom coding, • capping,• rounding,

Before Top and Bottom Coding

0

2

4

6

8

0 10 20 30 40 50 60 70 80 90

Salary: k$/yr

FreqAfter Top and Bottom Coding

0

2

4

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0 10 20 30 40 50 60 70 80 90

Salary: k$/yr

Freq

What is the SURF?

• Data from 200 synthetic respondents.

• Target population is those aged 15-45 in paid employment.

• 7 variables

personid gender

qualification age hours income marital ethnicity

1 female school 15 4 87 never european

2 female vocational 40 42 596 married european

3 male none 38 40 497 married maori

4 female vocational 34 8 299 never european

5 female school 45 16 301 married european

6 male degree 45 50 1614 married european

7 female none 36 12 201 other european

What does the SURF look like?

The first 7 of 200 complete unit records

SURF- the variables

How to start SURFing?• The gender gap (Level 3 and 4)

» Do more females have higher qualifications than males?

» Is this different from how it was in the past?

• Am I average? (Level 4) » What defines the average person?

• Under pressure? (Level 5)» Are people who have never been married different

from married people?

• Equal Pay! (Level 6) » Are males and females paid equally?

• Money for nothing (Level 7) » Investigating hours worked by employees in a

company• Should I do a degree? (Level 8)

» Investigation into whether getting a degree helps improve earning power

http://www.stats.govt.nz/schools-corner

• A large company is concerned that it has too many employees who do not work a 40-hour week.

• You have been hired to investigate the working patterns of the employees.

Task -Money for Nothing

Further Analysis- Hours by Gender

SURF CURF

Related variables – Hours by Marital Status

SURF CURF

Related variables – Hours by Age GroupSURF CURF

How ‘school friendly’ is SURF????

• SURF Excel spreadsheet

• Records are in random order – First 30 records could be used for manual

data analysis

• Use ExcelHow???????

Add Age_10 variable

Add random numbers (then paste special as values)

An example of how to take a stratified sample

Use filter – copy and paste records

Sort on random numbers

Filter function

Pivot Tables

Pivot Tables

Box plots !!!!

QUARTILE functionSORT by Marital

Regression and Residuals• Trend line in a scatter plot

– Good for quick visual check

– Provides equation & R-sq

– But no residuals

• Plot the data (XY scatter)

(tidy plot up)

• Add TrendlineChart menu > Add trendline

Options tab

y = 17.058x + 0.3487

R2 = 0.6323

0

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0 20 40 60 80

Hours

Inco

me

Regression and Residuals

• Using Excel functions

– SLOPE(), INTERCEPT(), RSQ()

Copy cell ref into formula bar

Regression and Residuals- Easy to create predicted values and residuals

(can copy formula and use $)

Regression and Residuals- Plot the residuals

-600

-400

-200

0

200

400

600

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1000

1200

Hours

Res

idu

als

The Statistics New Zealand Website

Stats NZ Products and Services• Schools Corner

– Full of resources based on the curriculum.

• Information releases – Hot Off the Press – Full of highlights, commentary, technical notes and tables!

• New Zealand in Profile– Quick stats of New Zealand for 2007

• Analytical reports– Contain in depth analysis, background and technical

information

• Table Builder– Customisable tables of released survey data

Stats NZ Products and Services• Schools Corner

– Full of resources based on the curriculum.

• Information releases – Hot Off the Press – Full of highlights, commentary, technical notes and tables!

• New Zealand in Profile– Quick stats of New Zealand for 2007

• Analytical reports– Contain in depth analysis, background and technical

information

• Table Builder– Customisable tables of released survey data

Stats NZ Products and Services• Schools Corner

– Full of resources based on the curriculum.

• Information releases – Hot Off the Press – Full of highlights, commentary, technical notes and tables!

• New Zealand in Profile– Quick stats of New Zealand for 2007

• Analytical reports– Contain in depth analysis, background and technical

information

• Table Builder– Customisable tables of released survey data

Stats NZ Products and Services• Schools Corner

– Full of resources based on the curriculum.

• Information releases – Hot Off the Press – Full of highlights, commentary, technical notes and tables!

• New Zealand in Profile– Quick stats of New Zealand for 2007

• Analytical reports– Contain in depth analysis, background and technical

information

• Table Builder– Customisable tables of released survey data

Battle for the ‘greener suburb’:

an example of using case data from Table Builder

• Problem – the statement of the research questions

• Plan – planning the procedures used to carry out the study

• Data – the data collection process

• Analysis – the summaries and analyses of the data to answer the questions posed

• Conclusion – the conclusions about what has been learned.

The statistical investigation cycle:(Wild and Pfannkuch, 1999)

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

• Comparing the ‘traveling to work’ habits of area units within Auckland.

• Which area has the ‘greener’ workers?– Walking / Running / Cycling

– Public transport

– Carpooling?

– Working at home?

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!

   

• So this is some of what Statistics New Zealand has to offer for teachers.

• Do you know about: – Statzing?– CensusAtSchool?– Statistics and Research?

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