Chapter 0 General module information

Math104 Statistics February 2017 Weeks 16-20 Course lecturer: Dr. Rebecca Killick E-mail: r.killick@lancs.ac.uk Office: B32 Fylde

Timetable
Lectures
Monday 2pm George Fox LT1
Wednesday 11am George Fox LT1
Thursday 9am George Fox LT1
Friday 12noon George Fox LT1
Workshops
Workshop assignment is the same as for Math103. Weeks 16-20 are the same format as for Math103 with questions to complete during the workshop. The week 20 workshop is a presentation session, further details will be given in your first workshop and in the lectures.

Administration
Online quizzes: Deadline Wednesday at 23:59.

Written assignments: Due every Tuesday at 5pm, to your tutor’s pigeonhole. Handed back in your workshop.

Assessment: 50% examination, 25% end of module test, 20% coursework (quizzes + written assignments 10% each), 5% participation in presentation session.

Handouts: Course notes and Exercises. Solutions will be released on Moodle after the corresponding workshop.

Office Hour: Monday 3pm & Friday 11am, B32 Fylde. Other times can be made by appointment — please email!

Exam: 1 hour exam in June 2017.

Note: This course was given in previous years as Math105 and was rewritten in 2014-15, so take care when using past exam papers. Further advice will be given by the lecturer.

Data examples are used throughout the course to illustrate the techniques that the course aims to teach you. Details of the examples are not part of the syllabus. You will be assessed on your understanding of the methods and not the detail of the examples. All the data used in the course is available in the Math104 R package on moodle.

To install the Math104 R package:

1. 1.

   Download the relevant package from the moodle page, *.zip for Windows and *.tar.gz for Linux/Mac.

2. 2.

   Within R Studio select Tools, Install Packages.

3. 3.

   In the new window, under ‘‘Install From:’’ choose ‘‘Package Archive File’’.

4. 4.

   In the new window, select the Math104 package downloaded from moodle (you may have to navigate to where you saved this).

5. 5.

   Click ‘‘Install’’.

6. 6.

   In the R window you will see the appropriate command run and it should say ‘‘Done (Math104)’’ when complete.

If you have problems installing the package, please email me with full details of the error and your setup (operating system, R version etc.).

Your participation in the course, by taking part in experiments, contributing in lectures and workshops and responding to the questionnaire is much appreciated.

R Code is given for all the examples in the notes. Not much description is given in the notes, see the R code file on moodle for commented code.

Aims
To enable students to achieve a solid understanding of the broad role that statistical thinking plays in addressing scientific problems in which the recorded information is subject to systematic and random variations. Specifically, by the end of the module, students should be able to select and formulate appropriate probability models, to implement the associated statistical techniques, and to draw clear and informative statistical conclusions for a range of simple scientific problems.

Objectives

1. 1.

   To be able to summarize data using appropriate numerical and graphical tools.

2. 2.

   To understand the challenges surrounding sampling of data and to be able to critique a sampling strategy.

3. 3.

   To understand the reasons for and against carrying out a hypothesis test and be able to carry out a number of simple hypothesis tests, including testing the value of the sample mean, paired and unpaired $t$-tests. Also to understand when each of these tests is appropriate.

4. 4.

   To understand the interpretation of a confidence interval and to be able to construct these for the sample mean, and the difference between two group means (paired and unpaired). To understand how to use these confidence intervals appropriately in hypothesis testing and to know what additional information they carry.

References

Parts of these notes are taken from the OpenIntro Statistics book available at: https://www.openintro.org/stat/textbook.php. Thanks go to David Diez, Christopher Barr and Mine Çetinkaya-Rundel for providing their material under a CC BY-SA license.

Rice, John, A. (2007) Mathematical Statistics and Data Analysis, Duxbury. AYA R$>$

Diggle, Peter, J. and Chetwynd, Amanda, A. (2011) Statistics and Scientific Method: An Introduction for Students and Researchers, OUP. AYA D$>$