Download Chapter 13 Probability

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WORK PROGRAM  MQ 9 NSW 5.2 Pathway
Chapter 13 Probability
Strand: Number, Data
Substrands and outcomes:
Chance
NS2.5 Describes and compares chance events in social and experimental contexts
Chance
NS3.5 Orders the likelihood of simple events on a number line from zero to one
Probability
NS4.4 Solves probability problems involving simple events
Probability
NS5.1.3 Determines relative frequencies and theoretical probabilities
Data analysis and evaluation
DS4.2 Collects statistical data using either a census or a sample, and analyses data using measures of
location and range
Section
Are you ready? (page 452)
GC tips, Investigations,
History of mathematics,
Maths Quest challenge,
10 Quick Questions,
Code puzzles
SkillSHEETS,
WorkSHEETS,
Interactive games,
Test yourself, Topic tests
(CD–ROM)
SkillSHEETS (page 452)
13.1: Understanding
chance words
13.2: Probability scale
13.3: Understanding a
deck of playing cards
13.4: Listing the sample
space
13.8: Theoretical
probability
Technology applications
(CD–ROM)
Learning outcomes
NS2.5
 using the language of chance
in everyday contexts
NS3.5
 describing the likelihood of
events and ordering the
events on a number line
NS4.4
 listing all possible outcomes
of a simple event
 using the term ‘sample
space’ to denote all possible
outcomes
 assigning probabilities to
simple events by reasoning
about equally likely
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Introduction to probability
(page 453)
WE 1a-b, 2a-c, 3a-b
Ex 13A Introduction to
probability (page 455)
SkillSHEET 13.1:
Understanding chance
words (page 455)
SkillSHEET 13.2:
Probability scale
(page 456)
SkillSHEET 13.3:
Understanding a deck
of playing cards
(page 456)
Mathcad: Probability scale
(page 456)
Sample space (page 457)
WE 4a-b, 5a-b. 6a-b
Ex 13B Sample space
(page 459)
SkillSHEET 13.4: Listing
the sample space
(page 459)
Excel: Coin toss lister
(page 460)
SkillSHEET 13.5: Forming
fractions (page 464)
Excel: Simulating die roll
(page 462)
Relative frequency
(page 461)
Investigation:
Investigating relative
outcomes
 expressing the probability of
a particular outcome as a
fraction between 0 and 1
NS3.5
 describing the likelihood of
events as being more or less
than a half (50% or 0.5) and
ordering the events on a
number line
NS4.4
 expressing the probability of
a particular outcome as a
fraction between 0 and 1
 explaining the meaning of a
probability of 0, 1 and 1 in
2
a given situation
(Communicating,
Reasoning)
 using language associated
with chance events
appropriately
(Communicating)
NS4.4
 listing all possible outcomes
of a simple event
 using the term ‘sample
space’ to denote all possible
outcomes
NS5.1.3
 repeating an experiment a
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WE 7a-b, 8
frequency (page 462)
Ex 13C Relative frequency 10 Quick Questions 1
(page 463)
(page 465)
Experimental probability
(page 466)
WE 9, 10a-b
Ex 13D Experimental
probability (page 468)
Theoretical probability of
an event (page 471)
WE 11
Ex 13E Theoretical
probability of an event
(page 472)
Maths Quest challenge:
Q1-2 (page 474)
10 Quick Questions 2
(page 474)
Code puzzle (page 475)
SkillSHEET 13.6:
Calculating relative
frequency (page 465)
SkillSHEET 13.7:
Converting a fraction
into a decimal
(page 465)
WorkSHEET 13.1
(page 465)
Game time 001 (page 470)
Excel: Frequency tables
and relative frequency
(page 464)
SkillSHEET 13.8:
Theoretical probability
(page 472)
SkillSHEET 13.9:
Converting a fraction
into a percentage
(page 473)
Game time 002 (page 473)
WorkSHEET 13.2
(page 473)
Mathcad: Theoretical
probability (page 472)

Mathcad: Experimental
probability (page 468)
number of times to
determine the relative
frequency of an event
estimating the probability of
an event from experimental
data using relative
frequencies
NS5.1.3
 estimating the probability of
an event from experimental
data using relative
frequencies
 expressing the probability of
an event from experimental
data using relative
frequencies
 applying relative frequency
to predict future
experimental outcomes
(Applying strategies)
NS5.1.3
 expressing the probability of
an event A given a finite
number of equally likely
outcomes as P(A) =
number of favourable outcomes
n
where n is the total number
of outcomes in the sample
space
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
Estimating probability
(page 476)
WE 12, 13
Ex 13F Estimating
probability (page 478)
Investigation: Simulating
days of the week
(page 478)
Investigation: Who’s
watching (page 479)
WorkSHEET 13.3
(page 479)
Extension: How to
generate random
numbers (page 476)
Excel: Generating random
numbers (page 478)
Excel: Generating random
numbers (DIY)
(page 478)
GC program – Casio:
Generating random
numbers (page 378)
GC program – TI:
Generating random
numbers (page 478)
GC program – Casio:
Rolling a die (page 479)
GC program – TI: Rolling
a die (page 479)
Excel: Simulating die roll
(page 479)
using the formula to
calculate probabilities for
simple events
NS5.1.3
 repeating an experiment a
number of times to
determine the relative
frequency of an event
 estimating the probability of
an event from experimental
data using relative
frequencies
 simulating probability
experiments using random
number generators
 designing a device to
produce a specified relative
frequency e.g. a fourcoloured circular spinner
(Applying strategies)
 recognising that probability
estimates become more
stable as the number of trials
increases (Reasoning)
DS4.2
 formulating key questions to
generate data for a problem
of interest
 making predictions from a
sample that may apply to the
whole population
 consider the size of the
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
Summary (page 480)
Chapter review (page 481)
‘Test yourself’ multiple
choice questions
(page 482)
Topic tests (2)
sample when making
predictions about the
population (Applying
strategies)
drawing conclusions based
on the analysis of data
(Applying strategies,
Reasoning)