 Student Records
Programme & Unit Catalogues

## MA10212: Probability & statistics 1B

2015/6 Owning Department/School: Department of Mathematical Sciences
6
Certificate (FHEQ level 4)
Semester 2
CW 25%, EX 75%
• Coursework 1 (CW 6%)
• Coursework 2 (CW 6%)
• Coursework 3 (CW 6%)
• Coursework 4 (CW 7%)
• Examination (EX 75%) Supplementary Assessment: MA10212 Mandatory extra work (where allowed by programme regulations)
Before taking this module you must take MA10211 Description: Aims:
To introduce probability theory for continuous random variables. To introduce statistical modelling and parameter estimation and to discuss the role of statistical computing.

Learning Outcomes:
After taking this unit the students should be able to:
* Solve a variety of problems and compute common quantities relating to continuous random variables.
* Formulate, fit and assess some statistical models.
* Use the R statistical package for simulation and data exploration.

Skills:
Numeracy T/F A
Problem Solving T/F A
Data Analysis T/F A
Information Technology T/F A
Written and Spoken Communication F (in tutorials).

Content:
Definition of continuous random variables (RVs), cumulative distribution functions (CDFs) and probability density functions (PDFs).
Some common continuous distributions including uniform, exponential and normal.
Transformations of RVs. Discussion of the role of simulation in statistics. Use of uniform random variables to simulate (and illustrate) some common families of discrete and continuous RVs.
Results for continuous RVs analogous to the discrete RV case, including mean, variance, standard deviation, properties of expectation, joint PDFs (including dependent and independent examples), independence (including joint distribution as a product of marginals), covariance, correlation.
The distribution of a sum of continuous RVs, including normal and exponential examples. Statement of the central limit theorem (CLT).
Introduction to model fitting; exploratory data analysis (EDA) and model formulation. Parameter estimation via method of moments and (simple cases of) maximum likelihood.
Sampling distributions, particularly of sample means. Point estimates and estimators. Estimators as random variables. Bias and precision of estimators.
Graphical assessment of goodness of fit. Programme availability:

#### MA10212 is Compulsory on the following programmes:

Department of Economics
• UHES-AFB04 : BSc(Hons) Economics and Mathematics (Year 1)
• UHES-AKB04 : BSc(Hons) Economics and Mathematics with Year long work placement (Year 1)
Department of Mathematical Sciences
• USMA-AFB15 : BSc(Hons) Mathematical Sciences (Year 1)
• USMA-AAB16 : BSc(Hons) Mathematical Sciences with Study year abroad (Year 1)
• USMA-AKB16 : BSc(Hons) Mathematical Sciences with Year long work placement (Year 1)
• USMA-AFB13 : BSc(Hons) Mathematics (Year 1)
• USMA-AAB14 : BSc(Hons) Mathematics with Study year abroad (Year 1)
• USMA-AKB14 : BSc(Hons) Mathematics with Year long work placement (Year 1)
• USMA-AFM14 : MMath(Hons) Mathematics (Year 1)
• USMA-AAM15 : MMath(Hons) Mathematics with Study year abroad (Year 1)
• USMA-AKM15 : MMath(Hons) Mathematics with Year long work placement (Year 1)
• USMA-AFB01 : BSc(Hons) Mathematics and Statistics (Year 1)
• USMA-AAB02 : BSc(Hons) Mathematics and Statistics with Study year abroad (Year 1)
• USMA-AKB02 : BSc(Hons) Mathematics and Statistics with Year long work placement (Year 1)
• USMA-AFB05 : BSc(Hons) Statistics (Year 1)
• USMA-AAB06 : BSc(Hons) Statistics with Study year abroad (Year 1)
• USMA-AKB06 : BSc(Hons) Statistics with Year long work placement (Year 1)

Notes:
* This unit catalogue is applicable for the 2015/16 academic year only. Students continuing their studies into 2016/17 and beyond should not assume that this unit will be available in future years in the format displayed here for 2015/16.
* Programmes and units are subject to change at any time, in accordance with normal University procedures.
* Availability of units will be subject to constraints such as staff availability, minimum and maximum group sizes, and timetabling factors as well as a student's ability to meet any pre-requisite rules.