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NZAMT NZQA NZ Grapher NZ Maths Census at School Study It

AS 2.12 Probability Revision

2.12 Probability HOME | Objectives | Probability Review | Probability tables | Two Way Tables | Risk & Relative Risk | Tree Diagrams | Conditional Prob | Distributions | Actual vs Normal | Normal Distribution | Inverse Normal | Revision

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Revision for AS 2.12 Probability

Revise, Revise, Revise

Probability Quiz (link to teacherlink.org)

NZQA exam paper 2012 and exemplar answers Excellence, Merit, Achieve, Answer Schedule (link to NZQA pdf's)

91267 Sample Exam Paper | Assessment Schedule | Excellence | Merit | Achievement | Not Achieved

 

 

NZQA Markers report Summary for 2012

ACHIEVE

candidates could:
- calculated probabilities or percentages using either Normal Distribution Tables or a Graphics calculator
- calculated probabilities using Probability Tree Diagrams
- calculated probabilities or proportions from the information presented in contingency tables.

NOT-ACHIEVED

Candidates commonly:
- did not have any calculator (often stated by candidates) or a graphics calculator to enable them to solve Normal Distribution problems
- were unable to solve Normal Distribution problems using the Standard Normal Distribution table provided
- wrote probabilities to only 1 significant figure without supporting evidence (i.e. no working)
- could not correctly add missing probabilities to a probability tree diagram
- gave their answer as a probability when a percentage was specifically asked for
- did not realise that proportions are probabilities
- could not complete a contingency table with the information provided
- did not identify the group of interest when calculating a probability from a contingency table
- gave insufficient evidence to support their ‘relational thinking’ or ‘extended abstract thinking’
- continued to reiterate the same point when making a comparison.

MERIT

In addition to Achievement, Merit candidates commonly:
- used their graphics calculator to solve more complex Normal Distribution problems (eg inverse normal distribution problems)
- applied calculated probabilities or proportions to determine the expected value for a situation and gave the answer as a whole number for a discrete situation
- compared features of a sample distribution with a Normal Distribution by partially describing similarities and differences using correct statistical terms
- calculated probabilities for multiple events using Probability Tree Diagrams
- could set up and solve a linear probability equation.


EXCELLENCE

In addition to Merit, Excellence candidates commonly:
- applied their understanding of inverse Normal Probability situations to find an unknown parameter (e.g. could find a new mean or standard deviation)
- could compare in depth the features of a sample distribution with a Normal Distribution by fully describing similarities/differences using correct statistical terms
- found a conditional probability for an event using either an extended probability tree diagram or conditional probability rule
- determined relative risks and drew a conclusion relating to a claim about the events occurring.

 
 

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