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# FASS509 Quantitative Research Methods 1 (online distance learning)

## Module description

• Uncertainty and probability.
• Random sampling and random variables. Different approaches to sampling. What is a "random" sample and why is it important for statistical inference?
• Variable types - discrete vs. continuous.
• Distributions - what they are and why they are important.
• Basic descriptive statistics - mean, median, mode, standard deviation, interquartile range.
• Credible intervals. The difference between probability and effect size. Credible intervals as limits of (un)certainty. Factors affecting the width of credible intervals.
• Simple hypothesis testing using credible intervals - the single mean, single proportion, difference between two means, and difference between two proportions.

## Aims and objectives

To provide students with:

• a fundamental understanding of probability
• a basic understanding of random sampling and why it is important.
• an introduction to basic descriptive statistics
• a simple introduction to inferential statistics for one- and two-sample problems, based around the notion of credible intervals.

To teach students how to perform the relevant calculations using a spreadsheet (Microsoft Excel or Open Office Calc).

On successful completion of this module students will be able to:

• Understand what probability is.
• Distinguish between probability and effect size.
• Understand how and why researchers take random samples from larger populations.
• Have a general idea of what a distribution is.
• Understand what basic descriptive measures (means, medians, modes, standard deviations, and interquartile ranges) can tell us.
• Understand what a credible interval is and what it can tell us.
• Know how to use a credible interval to test simple one- and two-sample hypotheses.
• Carry out the above calculations using a spreadsheet (Microsoft Excel or Open Office Calc).

Everitt, B. (2008), Chance Rules: An Informal Guide to Probability, Risk and Statistics, 2nd Ed. New York, Springer.

Franklin, J. (2009), What Science Knows and How It Knows It, New York, Encounter Books.

Gigerenzer, G. (2002), Reckoning with Risk: Learning to Live with Uncertainty, London, Penguin.

Hubbard, D.W. (2010), How to Measure Anything: Finding the Value of Intangibles in Business, 2nd Ed. Hoboken, NJ, John Wiley.

Paulos, J.A. (1995), A Mathematician Reads the Newspaper: Making Sense of The Numbers in the Headlines, London, Penguin.

Savage, S.L. (2009), The Flaw of Averages: Why We Underestimate Risk in the Face of Uncertainty, Hoboken, NJ, John Wiley.

NB these are not required texts - this is a background reading list.

## Timing and Location

 Term: Michaelmas Date(s): 14/10/13 - 22/11/13 Number of sessions: 6 x 1 hour sessions Runs weekly, starting in week 2 Timing and Location: online distance learning

Minimum quota: 6

Maximum quota: 30

Charge to non-FASS departments: £130

Apart from delivery mode, the syllabuses for FASS508: Quantitative Research Methods Introduction (face-to-face) and FASS509: Quantitative Research Methods 1 (online distance learning) are basically identical, so you should only need to take one of these. Either will provide the background necessary to prepare you for FASS512: Quantitative Research Methods 2.

## Careers workshops for PhD students 2013-14

Booking for careers workshops for PhD students will open at the start of Michaelmas Term. More>>

## Teaching development opportunities for postgraduates

Information about the teaching development opportunities for postgraduates, researchers and others involved in teaching in 2013-14. More>>

## RTP 2013-14

Registration for the 2013-14 RTP will open in October 2013.