Data Handling & Probability

[Pages:239]Data Handling & Probability

Grades 10, 11 and 12

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Census@School ? Data Handling and Probability (Grades 10, 11 and 12)

Statistics South Africa, 2013 Pali Lehohla, Statistician-General

Census@School ? Data Handling and Probability (Grades 10, 11 and 12) / Statistics South Africa Published by Statistics South Africa, Private Bag X44, Pretoria 0001

? Statistics South Africa, 2013 Users may apply or process this data, provided Statistics South Africa (Stats SA) is acknowledged as the original source of the data; that it is specified that the application and/or analysis is the result of the user's independent processing of the data; and that neither the basic data nor any reprocessed version or application thereof may be sold or offered for sale in any form whatsoever without prior permission from Stats SA.

Stats SA Library Cataloguing-in-Publication (CIP) Data Census@School ? Data Handling and Probability (Grades 10, 11 and 12) / Statistics South Africa. Pretoria: Statistics South Africa, 2013

238pp ISBN: 978-0-621-41837-8

A complete set of Stats SA publications is available at Stats SA Library and the following libraries:

National Library of South Africa, Pretoria Division National Library of South Africa, Cape Town Division Library of Parliament, Cape Town Bloemfontein Public Library Natal Society Library, Pietermaritzburg Johannesburg Public Library Eastern Cape Library Services, King William's Town Central Regional Library, Polokwane Central Reference Library, Nelspruit Central Reference Collection, Kimberley Central Reference Library, Mmabatho

This publication is available on the Stats SA website: .za

Copies are obtainable from: Printing and Distribution, Statistics South Africa

Tel: Email:

(012) 310 8093 (012) 310 8619 inadp@.za millies@.za

Foreword

H G Wells, sometimes called the father of modern science fiction, opined that at the turn of the 21st Century numeracy will be as important to humanity as is the ability to read and write. That Statistics South Africa (Stats SA) is committed towards building society wide statistical capacity therefore comes as no surprise in that it fulfils the demand that this prophecy of H G Wells inspired. By looking outside-in StatsSA took a conscious decision to create a programme that focuses on schools and the public to engender the love for statistics and its use. Statistical evidence is a critical decision support that creates possibilities for rational behaviour, decision making and development of society.

A practical way in which StatsSA undertakes and commits to execute this strategy is by embarking on a range of catalytic projects under ISIbalo, a legacy programme created by South Africa at the 57th Session of the International Statistical Institute (ISI), hosted in Durban, South Africa in August of 2009. The 2009 Census@School (C@S) project, first undertaken in 2001 in support of popularising Census 2001, was a repeat project undertaken nationally, in all provinces. Data were collected from a sample of 2 500 schools selected from the Department of Basic Education's database of approximately 26 000 registered schools (EMIS database). The predecessor project was so successful that one of the learners added that before Census@Schools she did not know how tall she was, thus fulfilling albeit anecdotally awareness of how data are gathered and its benefits to individuals and society. In addition and importantly, data collected provides contextual material for teachers and learners for teaching and learning of data handling, and promoting statistical literacy relating to a variety of subjects.

The first series of Mathematics Study Guide on Data Handling and Probability for the Senior Phase (Grades 7?9) using the 2009 C@S data was developed in 2011. Stats SA has achieved yet another milestone by developing a Further Education and Training (FET) (Grades 10?12) Mathematics Study Guide on Data Handling and Probability, as a contribution towards teaching and learning support material. Examples and exercises are based on the 2009 C@S and Census 2011 data. It is anticipated that teachers and learners would interact with data that was collected from their real-life situations and thus make learning interesting and enjoyable. A fast growing and innovative way of getting into schools is the Soccer4Stats series which bring the love for Mathematics and Statistics through gaming and this will be added as part of the essential material for building capacity. Johnny Masegela, Black Sunday of Orlando Pirates came with up with this innovation that has inspired not only South African schools but the world.

This milestone has been achieved through the collaboration and support from the national and provincial Departments of Basic Education with regard to the Census@School project.

Pali Lehohla Statistician-General

CENSUS@SCHOOL

CONTENTS

Chapter 1 Chapter 2 Chapter 3 Chapter 4 Chapter 5 Chapter 6 Chapter 7

Grade 10 Data Handling Grade 11 Data Handling Grade 12 Data Handling Grade 10 Probability Grade 11 Probability Grade 12 Probability Worked Solutions to Exercises Chapter 1 Chapter 2 Chapter 3 Chapter 4 Chapter 5 Chapter 6

Page 1 Page 38 Page 68 Page 95 Page 127 Page 152 Page 185 Page 185 Page 191 Page 200 Page 206 Page 216 Page 224

CENSUS@SCHOOL

1

Grade 10 Data Handling

In this chapter you will: ? Revise the language of data handling ? Determine measures of central tendency of lists of data, of data in frequency tables and data in

grouped frequency tables ? Determine quartiles and the five number summary ? Determine percentiles ? Determine measures of dispersion (range and inter-quartile range) ? Illustrate the five number summary with a box and whisker diagram

WHAT YOU LEARNED ABOUT DATA HANDLING IN GRADE 9

In Grade 9 you covered the following data handling concepts: ? Collecting data : including distinguishing between samples and populations ? Organising and summarising data : using tallies, tables and stem-and-leaf

displays; determining measures of central tendency (mean, median, mode); determining measures of dispersion (range, extremes, outliers) ? Representing data : drawing and interpreting bar graphs, double bar graphs, histograms, pie charts, broken-line graphs, scatter plots. ? Interpreting data : critically reading and interpreting two sets of data represented in a variety of graphs. ? Analysing data : critically analysing data by answering questions related to data collection methods, summaries of data, sources of error and bias in the data ? Reporting data by drawing conclusions about the data; making predictions based on the data; making comparisons between two sets of data; identifying sources of error and bias in the data; choosing appropriate summary statistics (mean, median, mode, range) for the data and discussing the role of extremes and outliers in the data

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