|Delivery Type||Delivery length / details|
|Lecture||18 Hours. (18 x 1 hour lectures)|
|Seminars / Tutorials||2 Hours. (2 x 1 hour tutorials)|
|Practical||3 Hours. (3 x 1 hour computer practicals)|
|Assessment Type||Assessment length / details||Proportion|
|Semester Assessment||continuous assessment||20%|
|Semester Exam||1.5 Hours (written examination)||80%|
|Supplementary Exam||2 Hours Repeat Failed Elements or equivalent Written exam||100%|
On completion of the module, a student should be able to:
* Summarise and present a data set;
* Calculate various summary measures for grouped and ungrouped data;
* Construct and interpret statistical diagrams;
* Fit a straight line to suitable data;
* Calculate and interpret correlations;
* Describe and illustrate basic probability concepts;
* Use statistical tables;
* Carry out and interpret the results of basic statistical tests;
* Use and interpret the output from statistical software.
This module introduces statistical methods and their application in Economics, together with the use of statistical computer software. The software package MINITAB is used in practical classes.
To introduce students to statistical methods and to appreciate their importance in Economics.
2. SUMMARY MEASURES: minimum, maximum, median, quartiles, percentiles; five number summaries and box-and-whisker plots; mean and mode; variance and standard deviation; calculations from grouped data.
3. SCATTERPLOTS, REGRESSION AND CORRELATION : scatterplots; the idea of a line of best fit; importance of the mean point; least squares regression; the existence of two regression lines for bivariate data; correlation and its measurement; the (product moment) correlation coefficient; Spearman'r rank correlation.
4. PROBABILITY: definition and properties; unions and intersections; mutually exclusive events; the addition law; independent events; the multiplication law; equally likely outcomes; conditional probability; Bayes? theorem; the Central Limit Theorem; the Normal distribution.
5. STATISTICAL INFERENCE: basic ideas; informal inference based on 'rwo standard deviations?; formal p-values; goodness of fit; the idea of a confidence interval.
6. TIME SERIES DATA: plotting time series; the idea of a moving average; smoothing.
The computer package MINITAB: introduction, producing and interpreting diagrams and tables, producing and interpreting summary measures; regression and correlation; output from formal procedures such as z-, t- chi-squared- and F-tests.
Reading ListSupplementary Text
Keller, Gerald and Warrack, Brian (c2000.) Statistics for management and economics. Duxbury Primo search McClave, Benson and Sincich (1998) Statistics for Business and Economics 8/e Pearson Primo search Swift, Louise. (2001.) Quantitative methods for business, management and finance /Louise Swift. Palgrave Primo search Consult For Futher Information
Curwin, Jon (2000.) Improve your maths :a refresher course /Jon Curwin and Roger Slater. Business Press Primo search Curwin, Jon. (1996.) Quantitative methods for business decisions /Jon Curwin and Roger Slater. International Thomson Business Press Primo search
This module is at CQFW Level 4