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SURFing with Statistics New Zealand Nathaniel Pihama and Deborah Brunning Statistics New Zealand Statistics Teachers' Day 30 November 2007.

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Presentation on theme: "SURFing with Statistics New Zealand Nathaniel Pihama and Deborah Brunning Statistics New Zealand Statistics Teachers' Day 30 November 2007."— Presentation transcript:

1 SURFing with Statistics New Zealand Nathaniel Pihama and Deborah Brunning Statistics New Zealand Statistics Teachers' Day 30 November 2007

2 What you will see today SURF for Schools The Statistics New Zealand website Table Builder..and some ideas on how to use them!

3 The First SURF: a Synthetic Unit Record File for Schools

4 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

5 What is a Unit Record File? Other names Data set Unit Record Data set Microdata

6 Confidentiality: where does it pop up? Raw data- set Trim data -set Tables galore “Analytical output” Papers etc Old: tables New(ish); microdata

7 Confidentiality In Confidentiality, Stats NZ (and the OSS) has two aims: Data Utility Statistical Disclosure Control, Disclosure Risk Management, Safety: Are they at loggerheads?? Our job is to ensure they’re not!

8 Confidentiality Safe Unsafe UselessUseful The pocket Raw dataset Non release

9 CURF: Confidentialised Unit Record Files HLFS/NZIS CURF 2004 New Zealand Income Survey 2004 Household Labour Force Survey June variables records 130 variables Researchers (Government, Academic) records records

10 Confidentialised Unit Record Files Confidentiality methods include: Categorical Data Global recoding Local recoding Numerical Data top/bottom coding, capping, rounding,

11 What is the SURF? Data from 200 synthetic respondents. Target population is those aged in paid employment. 7 variables

12 personidgenderqualificationagehoursincomemaritalethnicity 1femaleschool15487nevereuropean 2femalevocational marriedeuropean 3malenone marriedmaori 4femalevocational348299nevereuropean 5femaleschool marriedeuropean 6maledegree marriedeuropean 7femalenone othereuropean What does the SURF look like? The first 7 of 200 complete unit records

13 SURF- the variables

14 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

15 PPDAC cycle Problem Plan Data Analysis Conclusion

16 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

17 The company needs summary statistics for the hours worked by employees each week. The company’s database has data on the hours worked by its employees Problem

18 Take a representative sample of 35 employees. Calculate appropriate sample statistics and draw appropriate statistical graphs. Write a conclusion. Is the company’s concern valid? Plan

19 Data SRS, systematic, or stratified on age group (10-year groups?) Proportions for Strata Age group (years)CountProportion Total

20 SURF and CURF Analysis

21 Further Analysis- Hours by Gender SURFCURF

22 According to the SURF analysis… majority (>=75%)of males work 40 or more hours per week At least 25% of females work 40 or more hours per week The lower quartile for males is higher than the median for females A high proportion of men do work a 40 hour week, but the company should consider the reasons why such a small proportion of women work a 40 hour week. Conclusion for Money for Nothing

23 SURF majority (>=75%) of males work 40 or more hours per week At least 25% of females work 40 or more hours per week CURF Majority (>=50%) of males work 40 or more hours per week At least 25% of females work 42 hours or more per week SURF vs CURF

24 Related variables – Hours by Marital Status SURFCURF

25 Related variables – Hours by Age Group SURFCURF

26 How ‘school friendly’ is SURF???? SURF  Excel spreadsheet Records are in random order –First 30 records could be used for manual data analysis Use Excel How???????

27 Add Age_10 variable Add random numbers (then paste special as values) An example of how to take a stratified sample

28 Use filter – copy and paste records Sort on random numbers

29 Filter function

30 Pivot Tables

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32 Box plots !!!! QUARTILE function SORT by Marital

33 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 Trendline Chart menu > Add trendline Options tab

34 Regression and Residuals Using Excel functions – SLOPE(), INTERCEPT(), RSQ() Copy cell ref into formula bar

35 Regression and Residuals - Easy to create predicted values and residuals (can copy formula and use $)

36 Regression and Residuals - Plot the residuals

37 The Statistics New Zealand Website

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40 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

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45 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

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47 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

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49 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

50 Battle for the ‘greener suburb’: an example of using case data from Table Builder

51 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)

52 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?

53 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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67 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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