# data[].attributes.body
http://www.mathsisfun.com/numbers/e-eulers-number.html

# data[].attributes.body
http://onlinestatbook.com/2/normal_distribution/normal_approxM.html

# data[].attributes.body
https://padlet.com/mmuvictor/DPS5018_main

# data[].attributes.headline
Example Application of Binomial Distribution: Majority Decision Making for a Jury

# data[].attributes.subject
Example Application of Binomial Distribution: Majority Decision Making for a Jury

# data[].attributes.body
https://en.wikipedia.org/wiki/Condorcet%27s_jury_theorem

http://www.statisticalconsultants.co.nz/blog/condorcets-jury-theorem.html

# data[].attributes.headline
Example Application of Binomial and Poisson distribution: Military Reliability Modeling

# data[].attributes.subject
Example Application of Binomial and Poisson distribution: Military Reliability Modeling

# data[].attributes.body
http://www.usma.edu/math/military%20math%20modeling/ps1.pdf

# data[].attributes.headline
Example Application of Poisson distribution: Reliability Engineering

# data[].attributes.subject
Example Application of Poisson distribution: Reliability Engineering

# data[].attributes.body
https://src.alionscience.com/pdf/POIS_APP.pdf

# data[].attributes.headline
Example Application of Poisson distribution: Computer Network

# data[].attributes.subject
Example Application of Poisson distribution: Computer Network

# data[].attributes.body
http://www.cs.tufts.edu/comp/250P/classpages/Poisson.html

# data[].attributes.body
Binomial Calculator

http://stattrek.com/online-calculator/binomial.aspx

http://onlinestatbook.com/2/calculators/binomial_dist.html

Poisson Calculator

http://stattrek.com/online-calculator/poisson.aspx

http://keisan.casio.com/exec/system/1180573179

# data[].attributes.headline
How to decide whether the Poisson or the Binomial distribution should be used to answer an exam question?

# data[].attributes.subject
How to decide whether the Poisson or the Binomial distribution should be used to answer an exam question?

# data[].attributes.body
http://personal.maths.surrey.ac.uk/st/J.Deane/Teach/se202/poiss_bin.html

# data[].attributes.body
https://en.wikipedia.org/wiki/Poisson_limit_theorem

http://www.math.wm.edu/~leemis/chart/UDR/PDFs/BinomialPoisson.pdf

http://www.oxfordmathcenter.com/drupal7/node/297

# data[].attributes.headline
Proof of Mean and Variance of Binomial and Poisson Distributions

# data[].attributes.subject
Proof of Mean and Variance of Binomial and Poisson Distributions

# data[].attributes.body
Binomial & Poisson

http://filestore.aqa.org.uk/subjects/AQA-MS03-W-2-SM.PDF

Binomial

https://proofwiki.org/wiki/Expectation_of_Binomial_Distribution

https://proofwiki.org/wiki/Variance_of_Binomial_Distribution

Poisson

https://proofwiki.org/wiki/Expectation_of_Poisson_Distribution

https://proofwiki.org/wiki/Variance_of_Poisson_Distribution

# data[].attributes.body
Trim 3, 2015/2016

Q4a, Q4b, Q4c

Trim 2, 2015/2016

Section A:

Q15

Section B:

Q3a, Q3b, Q3c, Q3d

Trim 2, 2014/2015

Section C:

Q2a, Q2c, Q2d

# data[].attributes.headline
Summarized and Detailed Notes for Week 7 Lecture

# data[].attributes.subject
Summarized and Detailed Notes for Week 7 Lecture

# data[].attributes.body
The following topics are covered in this notes:
4.1) Probability Basics
4.2) Sample Space, Events, and Sets
4.3) Properties of Probability
4.4) Tree Diagram
5.1) Discrete Random Variable
5.2) The Mean of a Discrete Random Variable

# data[].attributes.headline
Summarized and Detailed Notes for Week 7 Tutorial

# data[].attributes.subject
Summarized and Detailed Notes for Week 7 Tutorial

# data[].attributes.body
The following topics are covered in this notes:
4.1) Probability Basics
4.2) Sample Space, Events, and Sets
4.3) Properties of Probability
4.4) Tree Diagram
5.1) Discrete Random Variable
5.2) The Mean of a Discrete Random Variable

# data[].attributes.headline
Proof of Shortcut Formulae for Variance 

# data[].attributes.subject
Proof of Shortcut Formulae for Variance 

# data[].attributes.body
https://proofwiki.org/wiki/Variance_as_Expectation_of_Square_minus_Square_of_Expectation

# data[].attributes.body
All Topic 5 concepts can be found in Chapter 11 to Chapter 13 of:

http://www.intmath.com/counting-probability/counting-probability-intro.php

The advantage of this website is that it contains many examples and solutions related to Topic 5; in case you want more practice problems while preparing for your MMU exams

# data[].attributes.headline
How to calculate the Mean and Variance of a Random Variable

# data[].attributes.subject
How to calculate the Mean and Variance of a Random Variable

# data[].attributes.body
The following topics are covered in this notes:
5.2) The Mean and Standard Deviation of a Discrete Random Variable

# data[].attributes.body
5.1a) Random variables

https://www.youtube.com/watch?v=3v9w79NhsfI

5.1b) Discrete and continuous random variables

https://www.youtube.com/watch?v=dOr0NKyD31Q

5.1c) Constructing a probability distribution for random variable

https://www.youtube.com/watch?v=cqK3uRoPtk0

5.2a) Probability Density Functions

https://www.youtube.com/watch?v=Fvi9A_tEmXQ

5.2b) Mean and Variance of Discrete Random Variables

https://www.youtube.com/watch?v=OvTEhNL96v0

5.1d to 5.2c) Example of how to use random variables to model a checkout line

https://www.youtube.com/watch?v=BIpsQIJUCC8

5.3) Binomial Distribution

http://onlinestatbook.com/2/probability/binomialM.html

5.4) Poisson Distribution

http://onlinestatbook.com/2/probability/poissonM.html

# data[].attributes.body
final 1415.pdf

Section A:

Q7, Q9

Section C:

Q2c, Q2d

final 1516.pdf

Section A:

Q12, Q13, Q14

Section B:

Q3a, Q3b

# data[].attributes.headline
Summarized and Detailed Notes for Week 4 Lecture

# data[].attributes.subject
Summarized and Detailed Notes for Week 4 Lecture

# data[].attributes.body
The following topics are covered in this notes:
1.2) Population vs. Sample
1.2) Symbols used to denote various statistics and parameter
1.4) Simple Random Sampling via Dice Rolling
2.3) Graphs and Charts: Histogram
3.1) Measures of Central Tendency: Mean
3.2) Measures of Variation: Standard Deviation
5.2) The Mean and Standard Deviation of a Discrete Random Variable
6) The Normal Distribution
8) Hypothesis Tests about a Population Mean

# data[].attributes.body
Post good learning materials over here to get your Bonus Marks :)

# data[].attributes.body
These are what you need to know about Topic 5

Random Variables

5.1) Discrete Random Variable

5.2) The Mean and Standard Deviation of a Discrete Random Variable

5.3) Binomial Distribution

5.4) Poisson Distribution