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MINISTRY OF PRIMARY AND SECONDARY EDUCATION

FORMS 3 - 4

2015 - 2022

ZIMBABWE

STATISTICS SYLLABUS

Curriculum Development and Technical Services P.O. Box MP 133 Mount Pleasant

Harare

© All Rights Reserved 2015

Statistics Syllabus Forms 3 - 4

ACKNOWLEDGEMENT

The Ministry of Primary and Secondary Education wishes to acknowledge the following for their valued contribution in the production of this syllabus:

• The National Statistics Syllabus Panel• Zimbabwe School Examinations Council• Ministry of Higher and Tertiary Education, Science and Technology Development • Publishers• United Nations Children’s Fund (UNICEF) • United Nations Educational, Scientific and Cultural Organization (UNESCO)

i


CONTENTS

ACKNOWLEDGEMENT.................................................................................................................. i

CONTENTS..................................................................................................................................... ii

1.0 PREAMBLE............................................................................................................................... 1

2.0 PRESENTATION OF SYLLABUS............................................................................................. 1

3.0 AIMS.......................................................................................................................................... 1

4.0 SYLLABUS OBJECTIVES........................................................................................................ 2

5.0 METHODOLOGY AND TIME ALLOCATION............................................................................ 2

6.0 TOPICS...................................................................................................................................... 2

7.0 SCOPE AND SEQUENCE......................................................................................................... 3

8.1 FORM THREE........................................................................................................................... 9

8.2 FORM 4...................................................................................................................................... 20

9.0 ASSESSMENT........................................................................................................................... 28

ii


1

1.0 PREAMBLE

1.1 Introduction

The Forms 3 - 4 Statistics syllabus is a two-year learning phase which is designed to promote critical thinking, problem solving, analytical and organisational skills. The subject seeks to equip learners with knowledge which lays a foundation for its application in other learning areas, further studies and for future careers. It creates awareness of their immediate environment, enables them to solve socio-economic problems and make informed decisions.

1.2 Rationale

Statistics is significant to the development of the Zimbabwean society. The knowledge of statistics enables learners to develop statistical skills such as research and analytical competencies essential for sus-tainable development. The importance of statistics can be underpinned in inclusivity and human dignity (Unhu/Ubuntu/Vumunhu) as it plays a pivotal role in careers such as education, medicine, agriculture, meteorology and engineering.

The statistics syllabus enables learners to develop skills in:

• Problem solving • Critical thinking • Decision making • Leadership • Self-management • Communication • Technology and innovation • Enterprise

1.3 Summary of Content

The syllabus is designed to cover Forms 3-4 of second-ary education in statistics which will lay a firm foundation for its application in other learning areas, further studies and career development. The syllabus covers theory and practical activities in data collection, presentation, interpretation, analysis and statistical inferences. Learners’ performance will be evaluated through sum-mative and continuous assessment.

1.4 Assumptions

It is assumed that learners:

• can carry out arithmetic operations• engage in logical thinking• have a basic knowledge of statistics• have prior knowledge of ICT

1.5 Cross Cutting Themes

In order to foster competence development for further studies, life and work, the teaching and learning of Statistics at forms 3 - 4 should integrate the following cross cutting themes:

• Enterprise skills and financial literacy • Digital literacy• Collaboration• HIV and AIDS• Heritage studies• Human Rights• Gender• Environmental issues • Disaster Risk management

2.0 PRESENTATION OF SYLLABUSThe Statistics Forms 3 -4 syllabus is presented as one document. The syllabus has aims, objectives, method-ology and time allocation, topics, scope and sequence, competency matrix and assessment.

3.0 AIMSThe syllabus enables learner to :

3.1 develop an appreciation of the role of statistics in national development

3.2 effectively use ICT tools to solve statistical problems

3.3 apply statistical knowledge and skills in other disciplines

3.4 develop a statistical foundation for further studies

3.5 use statistical data with integrity (Unhu/ Ubun-tu/Vumunhu)

3.6 value heritage, history and culture through research and statistical inferences

3.7 acquire entrepreneurship and leadership skills


2

in an indigenised economy through research and project based learning

3.8 develop critical and logical thinking

4.0 SYLLABUS OBJECTIVESBy the end of the course learners should be able to:

4.1 define statistics and statistical terms 4.2 collect and present data in written, graphical,

diagrammatical and tabular form4.3 draw inferences through manipulation of sta-

tistical data4.4 relate statistical concepts to real life situations 4.5 carry out statistical calculations 4.6 construct statistical arguments through appro-

priate use of precise statements and logical deduction

4.7 use ICT tools in statistical analysis 4.8 carry out statistical research projects

5.0 METHODOLOGY AND TIME ALLOCATION

5.1 Methodology

The following learner centred and participatory methods are recommended in the teaching of Statistics:

• Demonstrations • Discovery • Experimentation• Group work• Question and answer • Problem solving• Discussion• Research and Presentations • Project-based learning• Simulation and modelling

The above suggested methods should be enhanced through the application of multisensory approaches to teaching and learning and principles of individualization, unification, concreteness, stimulation and self-activity

5.2 Time AllocationThe learning area should be allocated 5 periods of 40 minutes each per week.

6.0 TOPICS

6.1 Introduction to Statistics 6.2 Data Collection and Presentation6.3 Measures of Central Tendency6.4 Measures of Dispersion6.5 Sampling6.6 Probability 6.7 Random Variables6.8 Errors 6.9 Index Numbers 6.10 Time Series 6.11 Linear Regression


3

7.0

SCO

PE A

ND

SEQ

UEN

CE

TOPI

C 7

.1.0

IN

TRO

DU

CTI

ON

TO

STA

TIST

ICS

TOPI

C 7

.1.1

DAT

A C

OLL

ECTI

ON

AN

D P

RES

ENTA

TIO

N

9

7.

SCO

PE A

ND

SEQ

UEN

CE

TOPI

C 7

.1.0

IN

TRO

DU

CTI

ON

TO

STA

TIST

ICS

SUB

TO

PIC

FO

RM 3

FO

RM 4

Intr

oduc

tion

to s

tatis

tics

St

atis

tical

term

s -

Stat

istic

s -

Dat

a -

Freq

uenc

y -

Tally

sys

tem

-

Des

crip

tive

-

Infe

rent

ial

Impo

rtan

ce o

f Sta

tistic

s

Stat

ics

in th

e

- ho

me

- Sc

hool

-

com

mun

ity

Te

chni

ques

of c

olle

ctin

g da

ta

M

etho

ds o

f rep

rese

ntin

g da

ta

10

TOPI

C 7

.1.1

DAT

A C

OLL

ECTI

ON

AN

D P

RES

ENTA

TIO

N

SU

B T

OPI

C

FORM

3

FORM

4

Type

s of

Dat

a

Type

s of

dat

a -

Prim

ary

data

and

sec

onda

ry d

ata

- G

roup

ed a

nd u

ngro

uped

-

Qua

litat

ive

and

quan

titat

ive

- D

iscr

ete

and

cont

inuo

us

Met

hods

of c

olle

ctin

g da

ta

M

etho

ds o

f col

lect

ing

data

: -

Surv

ey

- O

bser

vatio

nal S

tudy

-

Cen

sus

- Ex

perim

ent

Te

chni

ques

of c

olle

ctin

g da

ta:

- O

bser

vatio

n -

Que

stio

nnai

re

- In

terv

iew

s


4

TOPI

C 7

.1.2

DAT

A C

OLL

ECTI

ON

AN

D P

RES

ENTA

TIO

N

TOPI

C 7

.1. 3

MEA

SUR

ES O

F C

ENTR

AL

TEN

DEN

CY

TOPI

C 7

.1.4

MEA

SUR

ES O

F D

ISPE

RSI

ON

11

TOPI

C 7

.1.2

DAT

A C

OLL

ECTI

ON

AN

D P

RES

ENTA

TIO

N

SU

B T

OPI

C

FORM

3

FORM

4

Met

hods

of r

epre

sent

ing

data

Pict

ogra

m

Pi

e ch

art

Ba

r cha

rt

G

raph

s -

Line

gra

phs

- H

isto

gram

s -

Freq

uenc

y po

lygo

n -

Cum

ulat

ive

curv

e

12

TOPI

C 7

.1. 3

MEA

SUR

ES O

F C

ENTR

AL T

END

ENC

Y

SUB

TO

PIC

FO

RM 3

FO

RM 4

Mea

n, m

ode

and

med

ian

of

ungr

oupe

d da

ta a

nd g

roup

ed

data

U

ngro

uped

dat

a -

Mea

n -

Mod

e -

Med

ian

G

roup

ed d

ata

- M

ean

- M

ode

- M

edia

n

13

TOPI

C 7

.1.4

MEA

SUR

ES O

F D

ISPE

RSI

ON

SU

B T

OPI

C

FORM

3

FORM

4

Ran

ge

Id

entif

y hi

ghes

t and

low

est v

alue

s of

ung

roup

ed d

ata

D

efin

e ra

nge

of u

ngro

uped

dat

a

Cal

cula

te ra

nge

of ra

w d

ata

St

ate

adva

ntag

es a

nd d

isad

vant

ages

of u

sing

dat

a


5

TOPI

C 7

.1 5

MEA

SUR

ES O

F D

ISPE

RSI

ON

TOPI

C 7

.1 6

SA

MPL

ING

14

Topi

c 7.

1 5

MEA

SUR

ES O

F D

ISPE

RSI

ON

SU

B T

OPI

C

FORM

3

FORM

4

Mea

sure

s of

rela

tive

posi

tion

U

ngro

uped

dat

a -

Qua

rtile

s -

In q

uarti

le ra

nge

- Se

mi q

uarti

le ra

nge

G

roup

ed d

ata

- Q

uarti

les

of g

roup

ed d

ata

- In

qua

rtile

rang

e -

Sem

i qua

rtile

rang

e -

Perc

entil

es

- D

ecile

s

Varia

nce

and

Stan

dard

de

viat

ion

Va

rianc

e

Stan

dard

dev

iatio

n

Varia

nce

St

anda

rd d

evia

tion

15

Topi

c 7.

1 6

SAM

PLIN

G

SUB

TO

PIC

FO

RM 3

FO

RM 4

Sam

plin

g –

key

term

s

Sam

plin

g

Popu

latio

n

Ran

dom

ness

Sam

ple

Surv

ey

C

ensu

s

Sam

plin

g –

tech

niqu

es

R

ando

m s

ampl

ing

N

on- r

ando

m s

ampl

ing

Bi

ased

sam

plin

g

Rep

rese

ntat

ive

sam

ple

Sam

plin

g –

met

hods

Si

mpl

e ra

ndom

sam

plin

g

Syst

emat

ic s

amp0

ling

St

ratif

ied

sam

0plin

g

Clu

ster

sam

plin

g

Quo

ta s

ampl

ing

C

onve

nien

t Sam

plin

g


6

TOPI

C 7

.1 7

PR

OB

AB

ILIT

Y

TOPI

C 7

.1 8

RA

ND

OM

VA

RIA

BLE

S

16

Topi

c 7.

1 7

PRO

BAB

ILIT

Y SU

B T

OPI

C

FORM

3

FORM

4

Prob

abili

ty –

key

term

s

Prob

abilit

y

Tria

l

Sam

ple

spac

e

Out

com

e

Even

ts

Ex

perim

ent

Expe

rimen

tal a

nd th

eore

tical

pr

obab

ility

Expe

rimen

tal p

roba

bilit

y

Theo

retic

al p

roba

bilit

y

Com

bine

d ev

ents

C

ombi

ned

even

ts

Pr

obab

ility

spac

e

Prob

abilit

y ru

les

C

ondi

tiona

l; pr

obab

ility

17

Topi

c 7.

1 8

RAN

DO

M V

ARIA

BLE

S SU

B T

OPI

C

FORM

3

FORM

4

Type

s of

var

iabl

es

Va

riabl

e

Ran

dom

ness

Dis

cret

e ra

ndom

var

iabl

e

Con

tinue

s ra

ndom

var

iabl

es

Dis

cret

e ra

ndom

var

iabl

e

D

iscr

ete

rand

om v

aria

ble


7

TOPI

C 7

.1 9

ER

RO

RS

TOPI

C 7

.1 1

0 IN

DEX

NU

MB

ERS

18

Topi

c 7.

1 9

ERR

OR

S SU

B T

OPI

C

FORM

3

FORM

4

Estim

atio

n

Estim

atio

n

Mea

sure

men

t

Type

s of

err

ors

Er

rors

-

Abso

lute

-

Rel

ativ

e

Sour

ce o

f erro

rs

- R

ound

ed o

ff -

estim

atio

n

Com

puta

tion

of e

rror

s

Er

rors

-

abso

lute

-

rela

tive

19

Topi

c 7.

1 10

IN

DEX

NU

MB

ERS

SUB

TO

PIC

FO

RM 3

FO

RM 4

Type

s an

d us

es o

f ind

ex

num

bers

inde

x nu

mbe

rs

ba

se y

ear

pr

ice

rela

tive

un

wei

ghte

d an

d w

eigh

ted

aggr

egat

e co

st in

dex

av

erag

e pe

rcen

tage

bas

e pe

riod

Pric

e in

dex

and

expe

nditu

re

inde

x

- Pr

ice

rela

tive

inde

x -

Expe

nditu

re in

dex

- Av

erag

e pe

rcen

tage

-

Wei

ghte

d an

d un

wei

ghte

d av

erag

e

Dem

ogra

phic

rate

s

D

emog

raph

ic ra

tes

- C

rude

dea

th ra

te

- C

rude

birt

h ra

te

- G

row

th ra

te

- St

anda

rdiz

ed ra

tes


8

TOPI

C 7

.1 1

1 T

IME

SER

IES

TOPI

C 7

.1 1

2 L

INEA

R P

RO

GR

ESSI

ON

20

Topi

c 7.

1 11

TIM

E SE

RIE

S SU

B T

OPI

C

FORM

3

FORM

4

Tim

e se

ries

– ke

y te

rms

Ti

me

serie

s

Varia

bles

Perio

d: d

ay/ w

eek/

mon

th/ s

easo

n

Com

pone

nts

of ti

me

serie

s

Seas

onal

Cyc

lic

R

ando

m v

aria

tions

Tren

d

Tim

e se

ries

grap

hs

Tim

e se

ries

grap

hs

21

Topi

c 7.

1 12

LIN

EAR

PR

OG

RES

SIO

N

SUB

TO

PIC

FO

RM 3

FO

RM 4

Dep

ende

nt a

nd in

depe

nden

t va

riabl

es

Va

riabl

es

- D

epen

dent

-

inde

pend

ent

Scat

ter d

iagr

ams

Sc

atte

r dia

gram

s -

Dra

win

g -

Inte

rpre

tatio

n

Line

of b

est f

it

Sc

atte

rgra

m

Li

ne o

f bes

t fit

Eq

uatio

n of

a s

traig

ht li

ne


9

8.1

FOR

M T

HR

EE

8.1.

1 TO

PIC

1: I

NTR

OD

UC

TIO

N T

O S

TATI

STIC

S

22

8.1

FOR

M T

HR

EE

8.1.

1 TO

PIC

1: I

NTR

OD

UC

TIO

N T

O S

TATI

STIC

S SU

B T

OPI

C

LEAR

NIN

G O

BJE

CTI

VES

Le

arne

rs s

houl

d be

abl

e to

: C

ON

TEN

T (A

ttitu

des,

Sk

ills

and

Kno

wle

dge)

SUG

GES

TED

NO

TES

AND

AC

TIVI

TIES

SU

GG

ESTE

D R

ESO

UR

CES

Intr

oduc

tion

to s

tatis

tics

de

fine

stat

istic

al te

rms

stat

eTEH

br

anch

es

of

stat

istic

s

St

atis

tical

term

s:

- St

atis

tics

- D

ata

- Fr

eque

ncy

- Ta

lly s

yste

m

D

escr

iptiv

e

In

fere

ntia

l

D

iscu

ssin

g s

tatis

tical

te

rms

Expl

aini

ng m

eani

ngs

of

term

s

Cou

ntin

g an

d gr

oupi

ng

item

s

C

iting

rele

vant

exa

mpl

es

of b

ranc

hes

of s

tatis

tics

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s

Avai

labl

e o

bjec

ts

Impo

rtan

ce o

f Sta

tistic

s

stat

e th

e im

porta

nce

of

stat

istic

s

ex

plai

n th

e va

lue

of

Stat

istic

s in

life

st

atis

tics

in th

e -

hom

e,

- sc

hool

-

com

mun

ity

D

iscu

ssin

g th

e si

gnifi

canc

e of

sta

tistic

s in

th

e ho

me,

sch

ool a

nd

com

mun

ity

R

esea

rchi

ng o

n th

e ap

plic

atio

n o

f sta

tistic

s in

th

e ho

me,

sch

ool a

nd

com

mun

ity

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s


10

8.1

.2 :

DAT

A C

OLL

ECTI

ON

AN

D P

RES

ENTA

TIO

N

23

8.1

.2 :

DAT

A C

OLL

ECTI

ON

AN

D P

RES

ENTA

TIO

N

SUB

TO

PIC

LE

ARN

ING

OB

JEC

TIVE

S

Lear

ners

sho

uld

be a

ble

to:

CO

NTE

NT

(Atti

tude

s,

Skill

s an

d K

now

ledg

e)

SUG

GES

TED

NO

TES

AND

AC

TIVI

TIES

SU

GG

ESTE

D R

ESO

UR

CES

Type

s of

Dat

a

na

me

the

type

s of

dat

a in

st

atis

tics

co

mpa

re d

iffer

ent t

ypes

of

data

Ty

pes

of d

ata

-

Prim

ary

data

and

se

cond

ary

data

-

Gro

uped

and

un

grou

ped

-

Qua

litat

ive

and

Qua

ntita

tive

-

Dis

cret

e an

d C

ontin

uous

D

iscu

ssin

g th

e ty

pes

of

data

in s

tatis

tics

Expl

aini

ng th

e di

ffere

nce

betw

een

two

give

n ty

pes

of d

ata

C

lass

ifyin

g da

ta

acco

rdin

g to

type

ICT

tool

s

Rel

evan

t tex

ts

Br

aille

mat

eria

l and

eq

uipm

ent

Ta

lkin

g bo

oks

Met

hods

of c

olle

ctin

g da

ta

ex

plai

n m

etho

ds o

f co

llect

ing

data

use

the

met

hods

to c

olle

ct

data

M

etho

ds

of

colle

ctin

g da

ta:

- Su

rvey

-

Obs

erva

tiona

l stu

dy

- C

ensu

s

- Ex

perim

ent

D

iscu

ssin

g an

d de

mon

stra

ting

met

hods

of

col

lect

ing

data

Des

igni

ng a

nd

adm

inis

terin

g:

- Q

uest

ionn

aire

s -

Inte

rvie

w g

uide

s

C

arry

ing

out e

xper

imen

ts

such

as

toss

ing

a co

in o

r th

row

ing

a di

e

O

bser

ving

eve

nts

and

reco

rdin

g ou

tcom

es

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s

Loca

l env

ironm

ent

Met

hods

of r

epre

sent

ing

data

expl

ain

way

s of

re

pres

entin

g un

grou

ped

data

repr

esen

t ung

roup

ed d

ata

in v

ario

us fo

rms

inte

rpre

t sta

tistic

al

diag

ram

s

Pi

ctog

ram

Pie

char

t

Bar C

hart

Ex

plai

ning

way

s of

re

pres

entin

g da

ta

D

raw

ing:

-

Pict

ogra

ms

-

Pie

char

t -

Bar c

hart

Inte

rpre

ting

stat

istic

al

diag

ram

s

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s

Pict

ures

Dra

win

g in

stru

men

ts


11

8.1.

3: M

EASU

RES

OF

CEN

TRA

L TE

ND

ENC

Y

24

8.1.

3: M

EASU

RES

OF

CEN

TRAL

TEN

DEN

CY

SU

B T

OPI

C

LEAR

NIN

G O

BJE

CTI

VES

Le

arne

rs s

houl

d be

abl

e to

: C

ON

TEN

T (A

ttitu

des,

Sk

ills

and

Kno

wle

dge)

SUG

GES

TED

NO

TES

AND

AC

TIVI

TIES

SU

GG

ESTE

D R

ESO

UR

CES

Mea

n, m

ode

and

med

ian

of

ungr

oupe

d da

ta

de

fine

term

s:

- M

ean

-

Mod

e

- M

edia

n

find

the

mod

e of

un

grou

ped

data

find

the

med

ian

of

ungr

oupe

d da

ta

ca

lcul

ate

the

mea

n of

un

grou

ped

data

expl

ain

the

adva

ntag

es

and

disa

dvan

tage

s of

the

mea

sure

s of

cen

tral

tend

ency

sol

ve p

robl

ems

invo

lvin

g m

easu

res

of c

entra

l te

nden

cy

M

ean

M

ode

M

edia

n

D

iscu

ssin

g -

Mea

n -

Mod

e -

Med

ian

C

alcu

latin

g m

ean

and

m

edia

n of

ung

roup

ed d

ata

iden

tifyi

ng m

ode

from

un

grou

ped

data

dis

cuss

ing

the

adva

ntag

es a

nd

disa

dvan

tage

s of

the

mea

sure

s of

cen

tral

tend

ency

solv

ing

prob

lem

s in

volv

ing

mea

sure

s of

cen

tral

tend

ency

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s

Obj

ects

of d

iffer

ent

size

s, c

olou

r or s

hape

s


12

8.1.

4: M

EASU

RES

OF

DIS

PER

SIO

N

25

8.1.

4: M

EASU

RES

OF

DIS

PER

SIO

N

SUB

TO

PIC

LE

ARN

ING

OB

JEC

TIVE

S

Lear

ners

sho

uld

be a

ble

to:

CO

NTE

NT

(Atti

tude

s,

Skill

s an

d K

now

ledg

e)

SUG

GES

TED

NO

TES

AND

AC

TIVI

TIES

SU

GG

ESTE

D R

ESO

UR

CES

Ran

ge

id

entif

y hi

ghes

t and

low

est

valu

es o

f ung

roup

ed d

ata

de

fine

rang

e of

ung

roup

ed

data

calc

ulat

e ra

nge

of ra

w d

ata

stat

e ad

vant

ages

and

di

sadv

anta

ges

of u

sing

ra

nge

R

ange

id

entif

ying

hig

hest

and

lo

wes

t val

ues

of

ungr

oupe

d da

ta

C

alcu

latin

g ra

nge

for r

aw

data

Dis

cuss

ing

adva

ntag

es

and

disa

dvan

tage

s of

us

ing

rang

e

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s

Mea

surin

g in

stru

men

ts

Mea

sure

s of

rela

tive

posi

tion

de

fine

quar

tiles

arra

nge

num

bers

in

asce

ndin

g or

der

de

term

ine

quar

tiles

calc

ulat

e:

- in

terq

uarti

le ra

nge

-

sem

i-int

erqu

artil

e ra

nge

-

from

ung

roup

ed d

ata

ex

plai

n th

e m

eani

ng o

f in

terq

uarti

le ra

nge

Q

uarti

les

In

terq

uarti

le ra

nge

Se

mi-i

nter

quar

tile

rang

e

Fi

ndin

g qu

artil

es fr

om

ungr

oupe

d da

ta

C

alcu

latin

g:

- in

terq

uarti

le ra

nge

- se

mi i

nter

quar

tile

rang

e

disc

ussi

ng th

e si

gnifi

canc

e of

in

terq

uarti

le ra

nge

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s

Mea

surin

g in

stru

men

ts

Varia

nce

and

stan

dard

de

viat

ion

Def

ine:

- v

aria

nce

- sta

ndar

d de

viat

ion

calc

ulat

e:

- va

rianc

e of

ung

roup

ed

data

-

stan

dard

dev

iatio

n of

un

grou

ped

data

expl

ain

the

sign

ifica

nce

of:

- va

rianc

e

- st

anda

rd d

evia

tion

Va

rianc

e

St

anda

rd d

evia

tion

Cal

cula

ting

varia

nce

and

stan

dard

dev

iatio

n

D

iscu

ssin

g th

e si

gnifi

canc

e of

var

ianc

e

and

stan

dard

var

iatio

n

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s

Loca

l env

ironm

ent


13

8.1.

5: S

AM

PLIN

G

26

8.1.

5: S

AMPL

ING

SU

B T

OPI

C

LEAR

NIN

G O

BJE

CTI

VES

Le

arne

rs s

houl

d be

abl

e to

: C

ON

TEN

T (A

ttitu

des,

Sk

ills

and

Kno

wle

dge)

SUG

GES

TED

NO

TES

AND

AC

TIVI

TIES

SU

GG

ESTE

D R

ESO

UR

CES

Sam

plin

g - k

ey te

rms

ex

plai

n th

e ke

y te

rms:

-

sam

ple

and

sam

plin

g

- po

pula

tion

-

rand

omne

ss

- su

rvey

-

cens

us

di

ffere

ntia

te b

etw

een:

-

popu

latio

n an

d sa

mpl

e

- ce

nsus

and

sur

vey

Sa

mpl

ing

Po

pula

tion

Ran

dom

ness

Sam

ple

Surv

ey

C

ensu

s

D

iscu

ssin

g th

e m

eani

ngs

of th

e fo

llow

ing

key

term

s:

- sa

mpl

e an

d sa

mpl

ing

-

popu

latio

n

- ra

ndom

ness

-

surv

ey

- ce

nsus

Com

parin

g:

- Po

pula

tion

and

sam

ple

- C

ensu

s an

d su

rvey

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s

Sam

plin

g te

chni

ques

diffe

rent

iate

bet

wee

n ra

ndom

and

non

-rand

om

sam

plin

g

di

ffere

ntia

te b

etw

een

repr

esen

tativ

e an

d bi

ased

sa

mpl

es

gi

ve s

ourc

es o

f bia

s

ex

plai

n w

ays

of

over

com

ing

bias

dedu

ce a

dvan

tage

s an

d di

sadv

anta

ges

of th

e sa

mpl

ing

tech

niqu

es

id

entif

y si

tuat

ions

in w

hich

ra

ndom

and

non

-rand

om

sam

plin

g ca

n be

use

d

R

ando

m s

ampl

ing

Non

-rand

om s

ampl

ing

Bias

ed s

ampl

e

Rep

rese

ntat

ive

sam

ple

Li

stin

g di

ffere

nces

be

twee

n ra

ndom

and

no

n-ra

ndom

sam

plin

g

Dis

tingu

ishi

ng b

etw

een

bias

ed a

nd

repr

esen

tativ

e sa

mpl

e

Iden

tifyi

ng s

ourc

es o

f bi

as

D

iscu

ssin

g w

ays

of

over

com

ing

bias

Dis

cuss

ing

adva

ntag

es

and

disa

dvan

tage

s of

sa

mpl

ing

tech

niqu

es

C

iting

situ

atio

ns in

whi

ch

rand

om a

nd n

on-ra

ndom

sa

mpl

ing

can

be u

sed

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s

Raf

fles


14

8.1.

6 : P

RO

BA

BIL

ITY

27

8.1.

6 : P

RO

BAB

ILIT

Y SU

B T

OPI

C

LEAR

NIN

G O

BJE

CTI

VES

Le

arne

rs s

houl

d be

abl

e to

: C

ON

TEN

T (A

ttitu

des,

Sk

ills

and

Kno

wle

dge)

SUG

GES

TED

NO

TES

AND

AC

TIVI

TIES

SU

GG

ESTE

D R

ESO

UR

CES

Prob

abili

ty –

key

term

s

D

efin

e ke

y te

rms

- pr

obab

ility

-

trial

-

sam

ple

spac

e -

outc

ome

-

even

t -

expe

rimen

t

Pr

obab

ility

Tria

l

Sam

ple

spac

e

Out

com

e

Ev

ent

Ex

perim

ent

D

iscu

ssin

g th

e fo

llow

ing

prob

abilit

y ke

y te

rms:

-

prob

abilit

y

- tri

al

- sa

mpl

e sp

ace

- ou

tcom

e

- ev

ent

- ex

perim

ent

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s

Expe

rimen

tal a

nd th

eore

tical

pr

obab

ility

desc

ribe:

-

exp

erim

enta

l pr

obab

ility

-

theo

retic

al p

roba

bilit

y

de

duce

pro

babi

litie

s fro

m

resu

lts o

f exp

erim

ents

iden

tify

situ

atio

ns w

here

ex

perim

enta

l or t

heor

etic

al

prob

abilit

ies

are

used

Ex

perim

enta

l pro

babi

lity

Theo

retic

al p

roba

bilit

y

D

iscu

ssin

g th

eore

tical

an

d ex

perim

enta

l pr

obab

ilitie

s

C

iting

situ

atio

ns w

here

ex

perim

enta

l or

theo

retic

al p

roba

bilit

ies

are

used

Car

ryin

g ou

t ex

perim

ents

suc

h as

to

ssin

g a

coin

and

th

row

ing

a di

e

Com

putin

g pr

obab

ilitie

s of

eve

nts

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s

Spi

nnin

g w

heel

Coi

ns

D

ice

Sing

le e

vent

s

ca

lcul

ate

prob

abilit

ies

of

sing

le e

vent

s

co

mpu

te p

roba

bilit

ies

of

com

plem

enta

ry e

vent

s

pr

obab

ility

spac

e

com

plem

enta

ry e

vent

s

C

arry

ing

out

expe

rimen

ts o

f sin

gle

even

ts

C

ompu

ting

prob

abilit

ies

of c

ompl

emen

tary

ev

ents

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s

Coi

ns

D

ice

Balls

Play

ing

card

s


15

8.1.

7: R

AN

DO

M V

AR

IAB

LES

29

8.1.

7: R

AND

OM

VAR

IAB

LES

SUB

TO

PIC

LE

ARN

ING

OB

JEC

TIVE

S

Lear

ners

sho

uld

be a

ble

to:

CO

NTE

NT

(Atti

tude

s,

Skill

s an

d K

now

ledg

e)

SUG

GES

TED

NO

TES

AND

AC

TIVI

TIES

SU

GG

ESTE

D R

ESO

UR

CES

Type

s of

rand

om v

aria

bles

de

fine

: -

varia

ble

-

rand

omne

ss

- ra

ndom

var

iabl

e

st

ate

the

type

s of

rand

om

varia

bles

desc

ribe

the

prop

ertie

s of

: -

disc

rete

rand

om

varia

bles

-

cont

inuo

us ra

ndom

va

riabl

es

Va

riabl

e

R

ando

mne

ss

D

iscr

ete

rand

om v

aria

bles

Con

tinuo

us

rand

om

varia

bles

D

iscu

ssin

g ty

pes

of

rand

om v

aria

bles

Dis

cuss

ing

the

prop

ertie

s of

dis

cret

e ra

ndom

var

iabl

es a

nd

cont

inuo

us ra

ndom

va

riabl

es

C

ondu

ctin

g ex

perim

ents

to

sho

w ra

ndom

ness

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s Ba

lls o

f di

ffere

nt c

olou

rs

M

etre

rule

, Clo

thin

g, fo

ot

wea

r, sc

ale

and

cloc

k


16

8.1.

8: E

RR

OR

S

30

8.1.

8: E

RR

OR

S SU

B T

OPI

C

LEAR

NIN

G O

BJE

CTI

VES

Le

arne

rs s

houl

d be

abl

e to

: C

ON

TEN

T (A

ttitu

des,

Sk

ills

and

Kno

wle

dge)

SUG

GES

TED

NO

TES

AND

AC

TIVI

TIES

SU

GG

ESTE

D R

ESO

UR

CES

Estim

atio

n

us

e th

e ap

prox

imat

ion

sign

defin

e th

e te

rm

estim

atio

n

estim

ate

quan

titie

s

m

easu

re q

uant

ities

Es

timat

ion

Mea

sure

men

t

D

iscu

ssin

g es

timat

ion

Estim

atin

g qu

antit

ies

Mea

surin

g qu

antit

ies

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s

R

uler

s, s

cale

, mea

surin

g cy

linde

rs

Type

s of

err

ors

de

fine

an e

rror

st

ate

the

type

s of

erro

rs

di

stin

guis

h be

twee

n ab

solu

te e

rror a

nd

rela

tive

erro

r

stat

e so

urce

s of

erro

rs

Er

rors

-

Abso

lute

-

Rel

ativ

e

So

urce

s of

erro

rs

- R

ound

ing

off

- Es

timat

ion

D

iscu

ssin

g th

e ty

pes

of

erro

rs

D

iffer

entia

ting

abso

lute

er

ror f

rom

rela

tive

erro

r

Mea

surin

g qu

antit

ies

and

givi

ng re

sults

to a

n ap

prop

riate

deg

ree

of

accu

racy

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s R

uler

s,

scal

es a

nd c

lock

s


17

8.1.

9: I

ND

EX N

UM

BER

S

31

8.1.

9: I

ND

EX N

UM

BER

S

SUB

TO

PIC

LE

ARN

ING

OB

JEC

TIVE

S

Lear

ners

sho

uld

be a

ble

to:

CO

NTE

NT

(Atti

tude

s,

Skill

s an

d K

now

ledg

e)

SUG

GES

TED

NO

TES

AND

AC

TIVI

TIES

SU

GG

ESTE

D R

ESO

UR

CES

Type

s an

d us

es o

f ind

ex

num

bers

de

fine

: -

inde

x nu

mbe

r -

pric

e re

lativ

e -

base

yea

r -

wei

ghte

d a

nd u

n-w

eigh

ted

aggr

egat

e co

st in

dex

ca

lcul

ate

pric

e re

lativ

e nu

mbe

rs u

sing

bas

e ye

ar

pric

e

in

terp

ret a

giv

en p

rice

rela

tive

inde

x nu

mbe

r

iden

tify

appl

icat

ions

of

pric

e re

lativ

e in

dex

num

bers

in

dex

num

bers

base

yea

r

pric

e re

lativ

e

un

wei

ghte

d an

d w

eigh

ted

aggr

egat

e co

st in

dex

Aver

age

perc

enta

ge b

ase

perio

d

D

iscu

ssin

g in

dex

num

ber t

erm

s

Col

lect

ing

pric

es o

f di

ffere

nt it

ems

such

as

brea

d, s

ugar

, coo

king

oi

l, sa

lt, s

oap

over

a

spec

ified

per

iod

C

ompu

ting

the

pric

e re

lativ

e in

dex

num

bers

Dis

cuss

ing

app

licat

ion

of in

dex

num

ber

D

ebat

ing

on c

ost o

f liv

ing

and

adju

stm

ents

of

wag

es

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s Pr

ice

flier

s

R

esou

rce

pers

on

Pr

ice

Flie

rs


18

8.1.

10:

TIM

E SE

RIE

S

32

8.1.

10:

TIM

E SE

RIE

S

SUB

TO

PIC

LE

ARN

ING

OB

JEC

TIVE

S

Lear

ners

sho

uld

be a

ble

to:

CO

NTE

NT

(Atti

tude

s,

Skill

s an

d K

now

ledg

e)

SUG

GES

TED

NO

TES

AND

AC

TIVI

TIES

SU

GG

ESTE

D R

ESO

UR

CES

Tim

e se

ries

– ke

y te

rms

de

fine:

-

time

serie

s

- va

riabl

e

- pe

riod

id

entif

y tim

e se

ries

data

Ti

me

serie

s

Va

riabl

e

Pe

riod:

day

/wee

k/m

onth

/ se

ason

O

bser

ving

and

an

alyz

ing

exam

ples

of

time

serie

s gr

aphs

Expl

aini

ng v

aria

bles

an

d pe

riod

Iden

tifyi

ng ti

me

serie

s da

ta

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s

Res

ourc

e pe

rson

Com

pone

nts

of ti

me

serie

s

iden

tify

the

com

pone

nts

of ti

me

serie

s

Se

ason

al

C

yclic

Ran

dom

var

iatio

ns

Tr

end

di

scus

sing

com

pone

nts

of ti

me

serie

s

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s

Ti

me

serie

s re

cord

s


19

8.1

11:

LIN

EAR

REG

RES

SIO

N

33

8.1

11:

LIN

EAR

REG

RES

SIO

N

SUB

TO

PIC

LE

ARN

ING

OB

JEC

TIVE

S

Lear

ners

sho

uld

be a

ble

to:

CO

NTE

NT

(Atti

tude

s,

Skill

s an

d K

now

ledg

e)

SUG

GES

TED

NO

TES

AND

AC

TIVI

TIES

SU

GG

ESTE

D R

ESO

UR

CES

Dep

ende

nt a

nd in

depe

nden

t va

riabl

es

de

fine

varia

bles

expl

ain

depe

nden

t and

in

depe

nden

t var

iabl

es

Va

riabl

es

- de

pend

ent

- in

depe

nden

t

D

escr

ibin

g va

riabl

es

D

iscu

ssin

g de

pend

ent

and

inde

pend

ent

varia

bles

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s

Fl

yers

Scat

ter d

iagr

ams

co

llect

raw

dat

a

id

entif

y de

pend

ent a

nd

inde

pend

ent v

aria

bles

plo

t sca

tter d

iagr

ams

inte

rpre

t sca

tter

diag

ram

s

use

scat

ter d

iagr

ams

to

mak

e st

atis

tical

infe

renc

e

Sc

atte

r dia

gram

s -

draw

ing

- in

terp

reta

tion

G

athe

ring

raw

dat

a

Id

entif

ying

dep

ende

nt

and

inde

pend

ent

varia

bles

Plot

ting

scat

ter d

iagr

ams

Inte

rpre

ting

scat

ter

diag

ram

s

Usi

ng s

catte

r dia

gram

s to

mak

e st

atis

tical

in

fere

nces

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s D

raw

ing

tool

s


20

8.2

1: D

ATA

CO

LLEC

TIO

N A

ND

PR

ESEN

TATI

ON

8.2

FOR

M 4

34

FORM

FO

UR

8.

2 1:

DAT

A C

OLL

ECTI

ON

AN

D P

RES

ENTA

TIO

N

SUB

TO

PIC

LE

ARN

ING

OB

JEC

TIVE

S

Lear

ners

sho

uld

be a

ble

to:

CO

NTE

NT

(Atti

tude

s,

Skill

s an

d K

now

ledg

e)

SUG

GES

TED

NO

TES

AND

AC

TIVI

TIES

SU

GG

ESTE

D R

ESO

UR

CES

Tech

niqu

es o

f col

lect

ing

data

desi

gn q

uest

ionn

aire

s an

d in

terv

iew

gui

des

c

ondu

ct a

sur

vey

stat

e ad

vant

ages

and

di

sadv

anta

ges

of e

ach

tech

niqu

e

ob

serv

atio

n

ques

tionn

aire

inte

rvie

ws

D

esig

ning

qu

estio

nnai

res

for d

ata

colle

ctio

n

C

ondu

ctin

g a

surv

ey

usin

g da

ta c

olle

ctin

g te

chni

ques

Dis

cuss

ing

adva

ntag

es

and

disa

dvan

tage

s of

ea

ch d

ata

colle

ctio

n te

chni

que

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s

Loc

al e

nviro

nmen

t

Met

hods

of r

epre

sent

ing

data

expl

ain

way

s of

re

pres

entin

g gr

oupe

d da

ta

re

pres

ent g

roup

ed d

ata

in v

ario

us fo

rms

inte

rpre

t gra

phs

of

grou

ped

data

G

raph

s

- Li

ne g

raph

s -

His

togr

ams

-

Freq

uenc

y po

lygo

n

- C

umul

ativ

e fre

quen

cy

curv

e

Ex

plai

ning

way

s of

re

pres

entin

g da

ta

C

onst

ruct

ing

grap

hs

from

dat

a co

llect

ed in

the

envi

ronm

ent

In

terp

retin

g lin

e gr

aphs

, hi

stog

ram

, fre

quen

cy

poly

gon

and

cum

ulat

ive

frequ

ency

cur

ve

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s

Dra

win

g in

stru

men

ts


21

8.2.

2 : M

EASU

RES

OF

CEN

TRA

L TE

ND

ENC

Y

35

8.2.

2 : M

EASU

RES

OF

CEN

TRAL

TEN

DEN

CY

SUB

TO

PIC

LE

ARN

ING

OB

JEC

TIVE

S

Lear

ners

sho

uld

be a

ble

to:

CO

NTE

NT

(Atti

tude

s,

Skill

s an

d K

now

ledg

e)

SUG

GES

TED

NO

TES

AND

AC

TIVI

TIES

SU

GG

ESTE

D R

ESO

UR

CES

Mea

n, m

ode

and

med

ian

of

grou

ped

data

Com

pute

est

imat

es o

f m

edia

n an

d m

ean

of

grou

ped

data

find

the

mod

al c

lass

of

grou

ped

data

solv

e pr

oble

ms

invo

lvin

g m

easu

res

of c

entra

l te

nden

cy

m

ean

m

ode

m

edia

n

C

ompu

ting

estim

ates

of

med

ian

and

mea

n of

gr

oupe

d da

ta

St

atin

g th

e m

odal

cla

ss

of g

roup

ed d

ata

solv

ing

prob

lem

s in

volv

ing

mea

sure

s of

ce

ntra

l ten

denc

y

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s

Loca

l env

ironm

ent


22

8.2.

3: M

EASU

RES

OF

DIS

PER

SIO

N

36

8.2.

3: M

EASU

RES

OF

DIS

PER

SIO

N

SUB

TO

PIC

LE

ARN

ING

OB

JEC

TIVE

S

Lear

ners

sho

uld

be a

ble

to:

CO

NTE

NT

(Atti

tude

s,

Skill

s an

d K

now

ledg

e)

SUG

GES

TED

NO

TES

AND

AC

TIVI

TIES

SU

GG

ESTE

D R

ESO

UR

CES

Mea

sure

s of

rela

tive

posi

tion

of g

roup

ed d

ata

fin

d qu

artil

es fr

om

cum

ulat

ive

frequ

ency

cu

rves

calc

ulat

e:

- in

ter-q

uarti

le ra

nge

-

sem

i-int

erqu

artil

e ra

nge

inte

rpre

t the

sig

nific

ance

of

the

inte

r-qua

rtile

and

se

mi-i

nter

quar

tile

rang

e

fin

d pe

rcen

tiles

and

de

cile

s fro

m c

umul

ativ

e fre

quen

cy c

urve

s

Rel

ate

deci

les

to

perc

entil

es

Q

uarti

les

of g

roup

ed d

ata

Inte

rqua

rtile

rang

e

Se

mi-i

nter

quar

tile

rang

e

Perc

entil

e

D

ecile

s

U

sing

cum

ulat

ive

frequ

ency

cur

ves

to

estim

ate

mea

sure

s of

re

lativ

e po

sitio

n

Cal

cula

ting

the:

-

Inte

rqua

rtile

rang

e

- Se

mi-i

nter

quar

tile

rang

e

D

iscu

ssin

g th

e si

gnifi

canc

e of

: -

Inte

rqua

rtile

rang

e

- Se

mi I

nter

quar

tile

rang

e

Find

ing

deci

les

and

perc

entil

es fr

om

cum

ulat

ive

frequ

ency

cu

rves

Com

parin

g de

cile

s an

d pe

rcen

tiles

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s

37

Varia

nce

and

stan

dard

de

viat

ion

Cal

cula

te e

stim

ates

of

varia

nce

and

stan

dard

de

viat

ion

of g

roup

ed

data

expl

ain

the

sign

ifica

nce

of v

aria

nce

and

stan

dard

de

viat

ion

of g

roup

ed

data

solv

e pr

oble

ms

invo

lvin

g va

rianc

e an

d st

anda

rd

devi

atio

n fo

r gro

uped

da

ta

Va

rianc

e

St

anda

rd d

evia

tion

Cal

cula

ting

estim

ates

of

varia

nce

and

stan

dard

de

viat

ion

of g

roup

ed

data

com

men

ting

on th

e va

lue

of th

e va

rianc

e an

d st

anda

rd d

evia

tion

of

grou

ped

data

solv

ing

prob

lem

s in

volv

ing

varia

nce

and

stan

dard

dev

iatio

n fo

r gr

oupe

d da

ta

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s


23

8.2.

4: S

AM

PLIN

G

38

8.2.

4: S

AMPL

ING

SU

B T

OPI

C

LEAR

NIN

G O

BJE

CTI

VES

Le

arne

rs s

houl

d be

abl

e to

: C

ON

TEN

T (A

ttitu

des,

Sk

ills

and

Kno

wle

dge)

SUG

GES

TED

NO

TES

AND

AC

TIVI

TIES

SU

GG

ESTE

D R

ESO

UR

CES

Sam

plin

g m

etho

ds

st

ate

sam

plin

g m

etho

ds

de

scrib

e ea

ch o

f the

sa

mpl

ing

met

hods

expl

ain

situ

atio

ns in

w

hich

rand

om a

nd n

on-

rand

om s

ampl

ing

met

hods

are

use

d

de

scrib

e ad

vant

ages

and

di

sadv

anta

ges

of e

ach

of

the

sam

plin

g m

etho

d

Si

mpl

e ra

ndom

sam

plin

g

Syst

emat

ic s

ampl

ing

Stra

tifie

d sa

mpl

ing

Clu

ster

sam

plin

g

Q

uota

sam

plin

g

C

onve

nien

t sam

plin

g

Ex

plai

ning

eac

h of

the

sam

plin

g m

etho

ds

id

entif

ying

situ

atio

ns in

w

hich

sam

plin

g m

etho

ds a

re u

sed

Dis

cuss

ing

the

adva

ntag

es a

nd

disa

dvan

tage

s of

eac

h of

the

sam

plin

g m

etho

d

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s

8.2.

5: P

RO

BA

BIL

ITY

39

8.2.

5: P

RO

BAB

ILIT

Y SU

B T

OPI

C

LEAR

NIN

G O

BJE

CTI

VES

Le

arne

rs s

houl

d be

abl

e to

: C

ON

TEN

T (A

ttitu

des,

Sk

ills

and

Kno

wle

dge)

SUG

GES

TED

NO

TES

AND

AC

TIVI

TIES

SU

GG

ESTE

D R

ESO

UR

CES

Com

bine

d ev

ents

defin

e w

ith e

xam

ples

co

mbi

ned

even

ts

co

nstru

ct o

utco

me

tabl

es

and

prob

abilit

y sp

ace

diag

ram

s

use

prob

abilit

y ru

les

in

the

com

puta

tion

of

prob

abilit

ies

calc

ulat

e co

nditi

onal

pr

obab

ilitie

s

solv

e pr

oble

ms

invo

lvin

g pr

obab

ility

in li

fe

situ

atio

ns

C

ombi

ned

even

ts

Pr

obab

ility

spac

e

Pr

obab

ility

rule

s

C

ondi

tiona

l pro

babi

lity

D

iscu

ssin

g co

mbi

ned

even

ts

C

iting

exa

mpl

es o

f co

mbi

ned

even

ts

C

onst

ruct

ing

outc

ome

tabl

es a

nd p

roba

bilit

y sp

ace

diag

ram

s

C

ompu

ting

prob

abilit

y us

ing

prob

abilit

y ru

les

solv

ing

prob

lem

s in

volv

ing

prob

abilit

y in

lif

e si

tuat

ions

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s

Dic

e

C

oins

Play

ing

card

s

Balls


24

8.2

6: R

AN

DO

M V

AR

IAB

LES

8.2.

7: E

RR

OR

S

40

8.2

6: R

AND

OM

VAR

IAB

LES

SU

B T

OPI

C

LEAR

NIN

G O

BJE

CTI

VES

Le

arne

rs s

houl

d be

abl

e to

: C

ON

TEN

T (A

ttitu

des,

Sk

ills

and

Kno

wle

dge)

SUG

GES

TED

NO

TES

AND

AC

TIVI

TIES

SU

GG

ESTE

D R

ESO

UR

CES

Dis

cret

e ra

ndom

var

iabl

es

C

onst

ruct

the

prob

abilit

y di

strib

utio

n ta

ble

Cal

cula

te th

e E(

X)an

d Va

r (X

)

D

iscr

ete

rand

om v

aria

bles

C

arry

ing

out

expe

rimen

ts s

uch

as

toss

ing

a co

in, t

hrow

ing

a di

e

D

raw

ing

up a

pr

obab

ility

dist

ribut

ion

tabl

e

C

ompu

ting

the

E(X)

and

Var

(X)

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s

Coi

ns

D

ice

Scal

e

R

uler

41

8.2.

7: E

RR

OR

S SU

B T

OPI

C

LEAR

NIN

G O

BJE

CTI

VES

Le

arne

rs s

houl

d be

abl

e to

: C

ON

TEN

T (A

ttitu

des,

Sk

ills

and

Kno

wle

dge)

SUG

GES

TED

NO

TES

AND

AC

TIVI

TIES

SU

GG

ESTE

D R

ESO

UR

CES

Com

puta

tion

of e

rror

s

C

alcu

late

erro

rs:

- ab

solu

te e

rror

- re

lativ

e er

ror

Er

rors

: -

abso

lute

-

rela

tive

C

ompu

ting

abso

lute

and

re

lativ

e er

rors

Dis

cuss

ing

how

kn

owle

dge

of e

rrors

can

be

app

lied

in e

very

day

life

Expl

aini

ng th

e da

nger

s re

late

d to

erro

rs

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s


25

8.2

8: IN

DEX

NU

MB

ERS

42

8.2

8: IN

DEX

NU

MB

ERS

SUB

TO

PIC

LE

ARN

ING

OB

JEC

TIVE

S

Lear

ners

sho

uld

be a

ble

to:

CO

NTE

NT

(Atti

tude

s,

Skill

s an

d K

now

ledg

e)

SUG

GES

TED

NO

TES

AND

AC

TIVI

TIES

SU

GG

ESTE

D R

ESO

UR

CES

Pric

e in

dex

and

ex

pend

iture

inde

x

de

fine:

-

aver

age

perc

enta

ge

- ex

pend

iture

inde

x

di

stin

guis

h be

twee

n pr

ice

rela

tive

and

expe

nditu

re

inde

x

ca

lcul

ate

expe

nditu

re in

dex

of h

ouse

hold

s

st

ate

the

impo

rtanc

e of

ex

pend

iture

inde

x

us

e ex

pend

iture

inde

x in

ev

eryd

ay li

fe

Pr

ice

rela

tive

inde

x

Expe

nditu

re in

dex

Av

erag

e pe

rcen

tage

Wei

ghte

d an

d un

-wei

ghte

d av

erag

es

D

escr

ibin

g:

- pric

e re

lativ

e in

dex

-exp

endi

ture

inde

x

Com

putin

g ex

pend

iture

in

dex

of h

ouse

hold

s

Ex

plai

ning

the

impo

rtanc

e of

ex

pend

iture

inde

x

D

iscu

ssin

g th

e us

e of

ex

pend

iture

inde

x in

ev

eryd

ay li

fe

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s

Dem

ogra

phic

rate

s

de

fine

dem

ogra

phic

rate

s

ca

lcul

ate

dem

ogra

phic

ra

tes

D

emog

raph

ic ra

tes

-

Cru

de d

eath

rate

-

Cru

de b

irth

rate

-

Gro

wth

rate

-

Stan

dard

ized

rate

s

D

escr

ibin

g th

e de

mog

raph

ic ra

tes

Com

putin

g th

e de

mog

raph

ic ra

tes

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s


26

8.2

9: T

IME

SER

IES

43

8.2

9: T

IME

SER

IES

SUB

TO

PIC

LE

ARN

ING

OB

JEC

TIVE

S

Lear

ners

sho

uld

be a

ble

to:

CO

NTE

NT

(Atti

tude

s,

Skill

s an

d K

now

ledg

e)

SUG

GES

TED

NO

TES

AND

AC

TIVI

TIES

SU

GG

ESTE

D

RES

OU

RC

ES

Tim

e se

ries

grap

hs

an

alys

e tim

e se

ries

grap

hs

id

entif

y co

mpo

nent

s fro

m a

tim

e se

ries

grap

h

Ti

me

serie

s gr

aphs

Dis

cuss

ing

time

serie

s gr

aphs

iden

tifyi

ng c

ompo

nent

s fro

m a

tim

e se

ries

grap

h

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s

Smoo

then

ing

ex

plai

n th

e pu

rpos

e of

sm

ooth

enin

g

ca

lcul

ate

mov

ing

aver

ages

draw

tren

d lin

es

pl

ot m

ovin

g av

erag

es

so

lve

prob

lem

s in

volv

ing

time

serie

s in

life

M

ovin

g av

erag

es

Tr

end

lines

D

iscu

ssin

g th

e pu

rpos

e of

sm

ooth

enin

g

C

ompu

ting

mov

ing

aver

ages

Con

stru

ctin

g tre

nd li

nes

Inte

rpre

ting

the

trend

lin

es

Pl

ottin

g m

ovin

g av

erag

es

S

olvi

ng p

robl

ems

invo

lvin

g tim

e se

ries

in

life

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s


27

8.2.

10

LIN

EAR

REG

RES

SIO

N

44

8.2.

10:

LIN

EAR

REG

RES

SIO

N

SUB

TO

PIC

LE

ARN

ING

OB

JEC

TIVE

S

Lear

ners

sho

uld

be a

ble

to:

CO

NTE

NT

(Atti

tude

s,

Skill

s an

d K

now

ledg

e)

SUG

GES

TED

NO

TES

AND

AC

TIVI

TIES

SU

GG

ESTE

D

RES

OU

RC

ES

Line

of b

est f

it

pl

ot th

e sc

atte

r dia

gram

draw

the

line

of b

est f

it by

ey

e

dete

rmin

e th

e eq

uatio

n of

lin

e of

bes

t fit

in th

e fo

rm

use

the

equa

tion

of th

e lin

e of

bes

t fit

to e

stim

ate

valu

e of

gi

ven

sol

ve p

robl

ems

invo

lvin

g lin

ear r

egre

ssio

n

Sc

atte

rgra

m

Li

ne o

f bes

t fit

Equa

tion

of a

stra

ight

line

D

raw

ing

a sc

atte

r di

agra

m

D

raw

ing

the

line

of b

est

fit

Fi

ndin

g th

e eq

uatio

n of

th

e lin

e of

bes

t fit

Estim

atin

g th

e va

lue

of

for a

giv

en v

alue

of

sol

ving

pro

blem

s in

volv

ing

linea

r re

gres

sion

IC

T to

ols

R

elev

ant t

exts

Brai

lle m

ater

ial a

nd

equi

pmen

t

Talk

ing

book

s


28

9.0 ASSESSMENT

9.1 ASSESSMENT OBJECTIVES

Learners will be assessed on their ability to:

• Recall, recognize and use statistical terms and definitions• carry out calculations accurately showing all the necessary steps • explain statistical terms, processes and procedures• estimate and approximate quantities to a suitable degree of accuracy • measure variables to a suitable degree of accuracy • draw tables, graphs, charts and diagrams • read and interpret tables, graphs, charts and diagrams accurately • use appropriate statistical methods to collect data • analyse and interpret data accurately • make statistical inferences • use research skills to investigate, analyse and solve personal and community problems

9.2 SCHEME OF ASSESSMENT

The Forms 3 - 4 assessment in Statistics will be based on 30% continuous assessment and 70% summative assessment.

Arrangements, accommodation and modifications must be visible in both continuous and summative assessment to enable learners with special needs to access assessment and receive accurate performance measurement of their abilities. Access arrangements must neither give these candidates an undue advantage over others nor compromise the standards being assessed.Candidates who are unable to access the assessments of any component or part of component due to disability (transitory or permanent) may be eligible to receive an award based on the assessment they would have taken. a)Continuous AssessmentContinuous assessment will consists of topic tasks, written tests and end of term examinations:i) Topic Tasks These are activities that teachers use in their day to day teaching. These may include assignments and team work activities.

ii) Written TestsThese are tests set by the teacher to assess the concepts covered during a given period of up to a month. The tests should consist of short structured questions as well as long structured questions.

iii) End of term examinationsThese are comprehensive tests of the whole term’s or year’s work. These can be set at school, cluster, district or provincial level.

iv) ProjectThis should be done from term two to term five.

Summary of Continuous Assessment TasksFrom term one to five, candidates are expected to have done at least the following recorded tasks per term:

• 1 Topic task• 2 Written tests


29

44

iv) Project This should be done from term two to term five.

Summary of Continuous Assessment Tasks From term one to five, candidates are expected to have done at least the following recorded tasks per term: 1 Topic task 2 Written tests 1 End of term test 1 Project

Detailed Continuous Assessment Tasks Table Term Number of Topic

Tasks Number of Written Tests

Number of End of Term Tests

Project Total

1 1 2 1

2 1 2 1 Starts

3 1 2 1 In progress

4 1 2 1 In progress

5 1 2 1 Finalization

Weighting 15% 15% 30% 40% 100%

Actual weight 4.5% 4.5% 9% 12% 30%

Comment: Term 6 is for the National Examination

Comment: Term 6 is for the National Examination

45

Specification grid for continuous assessment

Component Skills Topic Tasks Written Tests End of Term Project Skill 1 Knowledge Comprehension

30% 30% 30% 30%

Skill 2 Application Analysis

50% 50% 50% 50%

Skill 3 Synthesis Evaluation

20% 20% 20% 20%

Total

100%

100%

100% 100%

Actual weighting 4.5% 4.5% 9% 12% b)Summative Assessment Description of papers The examination will consist of 2 papers: paper 1 and paper 2, each to be written in 2½ hours Statistics Paper 1 Duration: Two hours, 30 minutes The paper consists of about 25 structured questions marked out of 100. The paper is compulsory and will be set on all syllabus topics. Statistics Paper 2 Duration: Two hours, thirty minutes The paper consists of two sections, Section A and Section B. Section A: Approximately eight (8) compulsory questions, marked out of 64 Section B: Candidate choose three (3) out of five (5) long questions, marked out of 36 Each question carries twelve (12) marks


30

9.3 ASSESSMENT MODEL

Learners will be assessed using both continuous and summative assessments

Assessment of learner performance in Mechanical Mathematics

Continuous assessment 30% Summative assessment 70%

ProfilingTopic

Tasks4.5% Written Tests 4.5%

End of term

Tests 9%

Project12%

Paper 1 35% Paper 2 35%

Examination mark 70%

Profile

Exit Profile

Final Mark 100%

Continuous assessment mark 30%

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