ECON10800 Stats Methods for Economists

Academic Year 2023/2024

The purpose of this course is to introduce you to statistical thinking. Statistics is about using numerical methods to give sensible answers to questions that interest us. For example, how effecive is a new drug for curing a disease, how much does education affect earnings, how fast will prices rise next year? As well as coming up with our best estimate of the answer, statistics is concerned with expressing our uncertainty about that estimate.

Statistics falls into two parts, descriptive statistics and statistical inference. Most studies generate large amounts of numbers and we need to transform these numbers into easily understandable forms: either summary statistics such as means, standard deviations, and correlation coefficients; or graphs.

Statistical inference is concerned with how we can generalize results from samples to entire populations. For example, if we find that a treatment helps a large number of people in a sample to give up smoking, how sure can we be that the treatment worked, rather than that the sample contained an unusual number of people who would have stopped smoking anyway?

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Curricular information is subject to change

Learning Outcomes:

The goal of the course is to teach you to apply numerical techniques to data in a sensible way, and how to present what you find. So, by the end you should have a knowledge of how (and how not) to present data graphically, and an understanding of statistical techniques, regression especially.

Indicative Module Content:

The main topics are

1. Descriptive statistics and graphics.
2. Regression and correlation.
3. Probability.
4. Statistical inference.

Student Effort Hours: 
Student Effort Type Hours
Lectures

24
Autonomous Student Learning

76
Total

100
Approaches to Teaching and Learning:
The approach is the traditional one of lectures and problem sets. 
Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Multiple Choice Questionnaire: There will be three multiple choice exams during the term. Your grade will depend on the best two. Varies over the Trimester n/a Alternative linear conversion grade scale 40% No

100

Carry forward of passed components
No
 
Resit In Terminal Exam
Autumn No
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
 
Spring
      
Lecture Offering 1 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Thurs 12:00 - 12:50
Lecture Offering 1 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Tues 13:00 - 13:50
Spring