Resources by 91ÇÑ×Ó - 91ÇÑ×Ó Mon, 08 Jul 2024 03:27:15 +0000 en-US hourly 1 Using the 91ÇÑ×Ó Viewer to explore stories in data – video /resource/using-the-data-viewer-to-explore-stories-in-data/ Tue, 28 Oct 2014 01:32:34 +0000 http://new.censusatschool.org.nz/?post_type=resource&p=5748 This video and script has been designed to help Year 7 and 8 teachers explore data with their students using the 91ÇÑ×Ó Viewer tool on CAS.
It may also be useful professional development for Statistics and Social Science learning areas.

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This video and script has been designed to help Year 7 and 8 teachers explore data with their students using the 91ÇÑ×Ó Viewer tool on CAS.

It may also be useful professional development for Statistics or Social Science learning areas.

It uses the PPDAC cycle to progress through the stages of exploratory data analysis.

If you find this resource helpful please share it with your teaching colleagues.

If you would like further help using the tools on the 91ÇÑ×Ó website or to take part in the 2015/16 census please contact us.

Script for L3/4 Movie CAS 91ÇÑ×Ó Viewer

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91ÇÑ×Ó 2007 data subset (15,000 rows) /resource/censusatschool-2007-data-subset/ Thu, 14 Feb 2013 01:26:29 +0000 http://new.censusatschool.org.nz/?post_type=resource&p=4060 A subset of 15 000 data records from the 2007 91ÇÑ×Ó survey.

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A subset of 15 000 data records from the 2007 NZ 91ÇÑ×Ó survey.

Resource files for teachers or students to use for sampling and analysis using software other than 91ÇÑ×Ós.

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91ÇÑ×Ó 2007 data subset (as .xlsx)

91ÇÑ×Ó 2007 data subset (as .csv)

Full list of 2007 variables and questions

These are the variables (or attributes) in the 2007 survey:

Qualitative Variables

gender = boy/girl

handed = left or right handed or ambidextrous

travel = travel to school today was mainly on

timetravel = time to travel to school today (mins)

getlunch = where got lunch from today

futurejob

sportother/³ÙÄå°ì²¹°ù´Ç = sport / activity

³Ù±ð³¦³ó… = technology you have

cellsource = money for cell phone comes from

²ú°ù±ð²¹°ì´Ú²¹²õ³Ù… = had … for breakfast today

favwebsite = favourite website

favtvshow = favourite tv show

region = location of school within NZ

livingnz / nohokiaotearoa = best thing about living in NZ

betternz / paiakeaotearoa = how to make NZ better

Quantitative Variables

age = age in yrs at 1st Sept, 2007

languages = languages spoken

height = height to nearest centimetre (cm)

rightfoot = length of right foot (cm)

armspan = width of arm span (cm)

hairlength = length of hair (cm)

reaction = reaction time  (secs)

celltxtsend = number of txt messages sent yesterday

celltxtrec = number of txt messages received yesterday

cellcost = monthly cell phone bill

bedtime = bedtime last night

importwarm = importance of global warming

importpollution = importance of reducing pollution

importwater = importance of conserving water

importlifestyle = importance of having a healthy lifestyle

year = school year level

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91ÇÑ×Ó 2009 data subset (15,000 rows) /resource/2009-censusatschool-data-subset/ Thu, 14 Feb 2013 01:23:00 +0000 http://new.censusatschool.org.nz/?post_type=resource&p=4053 A subset of 15 000 records from the 2009 NZ 91ÇÑ×Ó survey in excel format.

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A collation of 91ÇÑ×Ó data from the 2009 NZ survey.

A subset of 15 000 data values is available in an excel spreadsheet.

91ÇÑ×Ó 2009 subset (as .csv)

91ÇÑ×Ó 2009 subset (as .xlsx)

2009 variables, attributes and questions

These are the variables (or attributes) in the 2009 survey: ()

Qualitative Variablesgender = boy/girl

country = country born in

±ð³Ù³ó²Ô¾±³¦â€¦ = ethnic group

handed = left or right handed or ambidextrous

travel = travel to school today was mainly on

bagcarry = how bag is carried

favlearning = favourite school subject

sport = favourite sport to participate

³Ù±ð³¦³ó… = technology you have

´Ç²Ô±ô¾±²Ô±ð²¹³¦³Ù¾±±¹¾±³Ù¾±±ð²õ… = which online activities

fitlevel = fitness level

favtvshow = favourite tv show

region = location of school within NZ

livingnz / nohokiaotearoa = best thing about living in NZ

betternz / paiakeaotearoa = how to make NZ better

holidayloc = favourite holiday location

prefquality = preferred quality

superpower = preferred superpower

Quantitative Variablesage = age in years

languages = languages spoken

height = height to nearest centimeter (cm)

rightfoot = length of right foot (cm)

armspan = width of arm span (cm)

wrist = circumference of wrist (cm)

neck = circumference of neck (cm)

popliteal = popliteal length (cm)

indexfinger = length of index finger (mm)

ringfinger = length of index finger (mm)

timetravel = time to travel to school today (mins)

bagweight = weight of bag (g)

²µ´Ç´Ç»å²¹³Ù… = how good at … are you

reaction = reaction time  (secs)

cellmonths = current cell phone age (months)

bedtime = bedtime last night

waketime = wake up this morning

pulserest = resting pulse rate (beats/min)

importwarm = importance of global warming

Note that the ¾±³¾±è´Ç°ù³Ù… questions are rated from -100 (Not at all Important) to +100 (Very Important).

importpollution = importance of reducing pollution

importrecycling = importance of recycling

importwater = importance of conserving water

importlifestyle = importance of having a healthy lifestyle

importenergy = importance of energy efficiency

importgovern = importance of government

importcomputer = importance of having a computer

year = school year level

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ID Cards /resource/id-cards/ Sun, 23 Dec 2012 04:10:02 +0000 http://new.censusatschool.org.nz/?post_type=resource&p=3680 What would your ID card look like? 91ÇÑ×Ó cards are a useful way for us to understand that each piece of data comes from an individual's response. This activity familiarises students with some variables from 91ÇÑ×Ó.

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What would your ID card look like?

Are you a boy or a girl?  How did you get to school?  How big are your feet?  What is your hair length?

In this activity, one data card is like a person’s ID card.  It tells us useful information about each person.  When students are using data from 91ÇÑ×Ó, it is very important for students to take time to “unpack the variables”.   This activity starts with 35 data cards and gets students familiarise themselves with data types, pose investigative questions, draw dot plots and bar graphs and make summary statements.

Achievement Objectives

Level 2 

S2-1 Conduct investigations using the statistical enquiry cycle:

  • A posing and answering quetsions
  • B gathering, sorting, and displaying category and whole-number data
  • C communicating findings, using data displays

Level 3

S3-1 Conduct investigations using the statistical enquiry cycle:

  • A gathering, sorting, and displaying multivariate cateogory and whole-number data to answer questions
  • B identifying patterns and trends in context, within and between data sets
  • C communicating findings, using data displays.

Resources:

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Armspans /resource/armspans/ Fri, 03 Aug 2012 02:58:27 +0000 http://new.censusatschool.org.nz/?post_type=resource&p=10 Do the armspan lengths of 12-year-old NZ boys tend to be bigger than the armspan lengths of 12-year-old NZ girls?

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Do the armspan lengths of 12-year-old NZ boys tend to be bigger than the armspan lengths of 12-year-old NZ girls?  The focus of this lesson is on comparing two samples and making an inference about populations from samples.  Students’ previous work on boxplots and work on sampling ideas are combined in this activity.

Resources:

Achievement Objectives

  • Level 5
    • S5-1Plan and conduct surveys and experiments using the statistical enquiry cycle
      • B considering sources of variation
      • C gathering and cleaning data
      • D using multiple displays, and re-categorising data to find patterns, variations, relationships, and trends in multivariate data sets
  • Level 6
    • S6-1Plan and conduct investigations using the statistical enquiry cycle
      • D making informal inferences about populations from sample data

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How high can you jump? /resource/how-high-can-you-jump/ Mon, 21 Nov 2011 01:18:23 +0000 http://new.censusatschool.org.nz/?post_type=resource&p=239 While practising for the upcoming basketball tourament, Mary wonders how high she can jump towards the basket. She wants to collect data from her team or class about their jumping ability to see how they compare with her. This resource focuses on the planning part of the enquiry cycle.

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Mary has proposed three survey questions to gain information about how high students can jump. The activity critiques the questions and encourages students to devise better questions so that Mary could get data that is both clean and reliable. Students follow through by choosing appropriate tables and displays for their data collected.

Resources:

Achievement Objectives

  • Level 4 Plan and conduct investigations using the statistical enquiry cycle:

                        A determining appropriate variables and data collection methods,

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Tell it like it is! /resource/tell-it-like-it-is/ Wed, 23 Feb 2011 02:08:45 +0000 http://new.censusatschool.org.nz/?post_type=resource&p=857 What can we conclude from some data and displays that we are given?

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One of the most important aspects of statistics is writing your conclusion.  It can be compared to reading the last chapter in a book or writing your final paragraph in an essay.

What we can conclude from some data we are given?  Often students have plenty of practise drawing graphs and calculating statistics. This activity concentrates on the C part of the PPDAC cycle and provides and opportunity and writing frame for students to write conclusions about students who filled out the C@S online survey.

Resources:

Achievement Objectives

  • Level 5
    • S5-1Plan and conduct surveys and experiments using the statistical enquiry cycle
      • F presenting a report of findings

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Bear hugs 3 /resource/bear-hugs-3/ Wed, 23 Feb 2011 01:07:20 +0000 http://new.censusatschool.org.nz/?post_type=resource&p=853 Do boys have longer arm spans than girls?

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Do boys have longer arm spans than girls?

A comparative analysis investigating the lengths of armspans of boys and girls. Students use a variety of displays and summative statistics and are led through how to write appropriate conclusions.

Resources:

See Bear Hugs 1 and Bear Hugs 2 for previous iNZight instructional videos

Achievement Objectives

  • Level 5
    • S5-1Plan and conduct surveys and experiments using the statistical enquiry cycle
      • B considering sources of variation
      • D using multiple displays, and re-categorising data to find patterns, variations, relationships, and trends in multivariate data sets
      • E comparing sample distributions visually, using measures of centre, spread, and proportion

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Bear hugs 2 /resource/bear-hugs-2/ Sun, 20 Feb 2011 13:01:10 +0000 http://new.censusatschool.org.nz/?post_type=resource&p=253 Do our arms get longer as we get older? An introduction to bivariate data and scatterplots.

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This activity expands on Bear hugs 1 in which we investigate the length of our armspans. Students explore the relationship between arm span and age and are introduced to scatterplots, strength of relationships and variability within data sets.

Resources:

See Bear Hugs 1 and Bear Hugs 3 for previous iNZight instructional videos.

Achievement Objectives

  • Level 5
    • S5-1Plan and conduct surveys and experiments using the statistical enquiry cycle
      • B considering sources of variation
      • D using multiple displays, and re-categorising data to find patterns, variations, relationships, and trends in multivariate data sets
      • E comparing sample distributions visually, using measures of centre, spread, and proportion

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Bear Hugs 1 /resource/bear-hugs-1/ Mon, 21 Feb 2011 01:47:25 +0000 http://new.censusatschool.org.nz/?post_type=resource&p=248 Does the average student have arms long enough to give a bear with a circumference of 160cm a hug?

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To give an awesome bear hug you need really long arms so that your arms get all the way around the person you are hugging.

Does the average student have arms long enough to give a bear with a circumference of 160cm a hug?

In this activity you will explore how long the average arm span is and if it is bigger than the 160cm required to hug a bear. Students use data from the ‘Nosey parker’ activity (24 students from the C@S website) to construct appropriate displays and calculate and interpret sample statistics. They assess the distribution shape and use their analysis to make an inference about the population of students’ armspans.

Resources:

Achievement Objectives

  • Level 5
    • S5-1Plan and conduct surveys and experiments using the statistical enquiry cycle
      • B considering sources of variation
      • D using multiple displays, and re-categorising data to find patterns, variations, relationships, and trends in multivariate data sets
      • E comparing sample distributions visually, using measures of centre, spread, and proportion

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