# Gwybodaeth Modiwlau

Module Identifier
EC10910
Module Title
Statistics for Economists
2016/2017
Co-ordinator
Semester
Semester 2
Other Staff

#### Course Delivery

Delivery Type Delivery length / details
Lecture 22 x 1 Hour Lectures
Practical 2 x 1 Hour Practicals
Tutorial 2 x 1 Hour Tutorials

#### Assessment

Assessment Type Assessment length / details Proportion
Semester Assessment continuous assessment  20%
Semester Exam 1.5 Hours   (written examination)  80%
Supplementary Exam 2 Hours   Written exam  100%

### Learning Outcomes

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.

### Brief description

This module introduces statistical methods and their application, basic ideas from probability, together with the use of statistical tools in Excel

### Aims

To introduce students to statistical methods and to appreciate their importance in Economics.

### Content

1. STATISTICAL DIAGRAMS: pie charts; simple multiple and stacked barcharts; histograms; cumulative polygons; stem and leaf diagrams
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. Contingency tables, scatterplots; the idea of a line of best fit; importance of the mean point; least squares regression; 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's theorem; the Central Limit Theorem; the Binomial distribution; 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. COMPUTER-AIDED STATISTICS. With the aid of Excel: produce and interpret diagrams, tables and summary measures; compute correlation and regression; motivate probability distributions and the Central Limit Theorem.

### Notes

This module is at CQFW Level 4