Level 1 Probability
Achievement Objectives 
Learning Outcomes 
Unit title 
S13

 use everyday language to talk about chance
 classify events as certain, possible, or impossible

No Way Jose 
Lonely kiwi 
Level 2 Probability
Achievement Objectives 
Learning Outcomes 
Unit title 
S23

 use dice etc to assign roles and discuss the fairness of games
 play probability games and identify all possible outcomes
 compare and order the likelihood of simple events

That's not fair 
 recognise that not all things occur with the same likelihood
 observe some things are fairer than others
 explore to adjust the rules of games to make them fairer

The Cube and Coin Challenge 
Level 3 Probability
Achievement Objectives 
Learning Outcomes 
Unit title 
S33

 make predictions based on data collected
 identify all possible outcomes of an event
 assign probabilities to simple events using fractions (1/2, 1/6 etc)

What's in the Bag? 
 determine an experimental estimate of the probability of simple events using frequency tables
 determine the theoretical probability of simple events using percentages, fractions and decimals
 systematically find all possible outcomes of an event using tree diagrams and organised lists

I'm spinning 
 systematically find all possible outcomes of an event using tree diagrams and organised lists

Counting on Probability 
 take samples and use them to make predictions
 compare theoretical and experimental probabilities

Long Running

Level 4 Probability
Achievement Objectives 
Learning Outcomes 
Unit title 

 investigate probability in common situations;
 make and justify the probability of events in common situations;
 theoretically and experimentally examine the probabilities of games of chance.

Beat It 
 find a theoretical probability
 use more than one way to find a theoretical probability
 check theoretical probabilities by trials
 identify what a fair game is and how to make a unfair game fair

The Coloured Cube Question 
 use simulations to investigate probability in common situations
 predict the likelihood of outcomes on the basis of an experiment
 determine the theoretical probability of an event

Murphy's Law 
 explore the theoretical and experimental probabilities of situations involving chance
 recognise variability from theoretical expectations, especially with small numbers of trials
 estimate and find the relative frequencies of events
 distinguish between events and the outcomes that lead to those events
 distinguish between dependent and independent events

What are the chances? 
 find a theoretical probability.
 use more than one way to find a theoretical probability.
 check theoretical probabilities by trials.
 identify what a fair game is and how to make an unfair game fair.

Flip and roll 
Level 5 Probability
Achievement Objectives 
Learning Outcomes 
Unit title 

 calculate the probabilities for outcomes of a dice roll.
 draw a dot plot of results.
 interpret dot plots in terms of centre and variation.
 calculate averages and expected values.

Greedy Pig 
 explain what a probability distribution is
 explain how probabilities are distributed
 calculate what happens to the distribution when variables are summed

Probability Distributions 
 Use longrun frequencies to estimate probabilities.
 Compare the results of theoretical and experimental approaches to games of chance.

Fair Games 
Level 6 Probability
Achievement Objectives 
Learning Outcomes 
Unit title 
S63

 conduct straightforward experiments with coins, dice, spinners, and other random event generators
 produce and understand the concept of a random walk
 develop,understand and be able to use Pascal’s Triangle
 determine probabilities of a class that is just a little too complicated for probability trees.

Investigating Random Processes 
Probability is the study of random events.
A 'random event' in probability is a collection of particular outcomes from a probability activity, for example, rolling a sum of 12 with two dice. These events are important both inside mathematics and outside it. The obvious examples to explore in a classroom setting involve games of chance, anything from a game of Ludo to a game of Roulette. On the other hand, businesses such as insurance companies need to know about events concerned with car accidents, death, and footballers having accidents. To decide whether it is worth taking some action, and what action to take, we rely on a measure of the likelihood of an event that we call probability. For practical reasons the size of the probability of an event is expressed as a number between zero and one or a percentage between zero and 100.
Probabilities can be determined in two ways: theoretically or experimentally. Many simple events can be found theoretically. For example, the probability of getting a 4, say, on the roll of a dice can be found theoretically. First you have to know the event space, the set of all possible outcomes. In the case of a dice this is {1, 2, 3, 4, 5, 6}. So there are six events in the event space. There is only one event in this event space that produces a 4. Hence the probability of getting a 4 when you roll a dice is 1/6, the 1 is for the number of times a four can occur among all possible events and the 6 is for the number of all possible events (the size of the event space). In general, when calculating probabilities theoretically, the probability is given by the equation
As another example consider what happens when you roll two dice. What are the chances of getting a sum of 4 then? Well here the event space is of size 36 {(1, 1), (1, 2), (1, 3), ... (6, 4), (6, 5), (6, 6)} and the times that 4 is possible are given by {(1, 3), (2, 2), (3, 1)}. Hence the probability of getting a 4 is 3/36 = 1/12.
But not all events can have their probabilities calculated theoretically. Think of the probability of there being three major earthquakes in a year or the chances that it will rain tomorrow. We can't produce an event space to measure these probabilities by. So we have to take measurements over a long period. In that time we can compare the number of rainy days over the number of days altogether  the number of favourable outcomes (yes, a rainy day is favourable in this context) over the number of possible outcomes. So in a case like this, where we have to calculate probability experimentally, the probability is given by