MMD010-Data Analysis: Finding Patterns With Regressions

Module Provider: International Business and Strategy
Number of credits: 0 [0 ECTS credits]
Level:NA
Terms in which taught: Autumn / Spring term module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Module version for: 2017/8

Module Convenor: Prof Davide Castellani

Email: davide.castellani@henley.ac.uk

Summary module description:

Aims:

The module aims to broaden students’ understanding of data analysis by providing an overview of key methods and particularly focusing on regression analysis. 


Assessable learning outcomes:

By the end of the module students will be able to demonstrate:-



• An understanding of what OLS does and why we use regression analysis. 



• An understanding Stata OLS output



• Have the ability to interpret cross section OLS estimates. 



• Have some understanding of concepts of correlation, causality, selection, confounders.


Additional outcomes:

Outline content:

• Use of Stata software to gain familiarity with basic statistics principles



• Introduction to Regression Analysis. Understanding the structure of data, frequency and cross-tabulation. From scatterplot to OLS. Interpretation of coefficients. 



• Running regressions, measurement issues. Taking logs – percentage changes. Issues with working with real life data; “outliers”-influential observations. Generalizing from Regression Estimates: Confidence Interval, SE. External validity. 



• Introduction to Causal Analysis (the counterfactual principle; reverse causality, confounders and selection in regressions). 



• Introduction to Multiple Linear Regression Analysis. Comparing apples to apples.



• Interpretation of coefficients, including binary variables and interactions. 



• Introduction to modelling probability: linear probability and logit models. Discussion: Observational data and causality.


Brief description of teaching and learning methods:

The module will be taught through a series of PC lab based tutorials, lectures and self directed study.


Contact hours:
  Autumn Spring Summer
Lectures 10
Tutorials 9
Guided independent study 81
       
Total hours by term 100.00
       
Total hours for module 100.00

Summative Assessment Methods:
Method Percentage
Written assignment including essay 100

Other information on summative assessment:

Formative assessment methods:

Penalties for late submission:

Penalties for late submission on this module are in accordance with the University policy. Please refer to page 5 of the Postgraduate Guide to Assessment for further information: http://www.reading.ac.uk/internal/exams/student/exa-guidePG.aspx 



 



The Module Convenor will apply the following penalties for work submitted late, in accordance with the University policy.
  • where the piece of work is submitted up to one calendar week after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for the piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of five working days;
  • where the piece of work is submitted more than five working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

  • The University policy statement on penalties for late submission can be found at: http://www.reading.ac.uk/web/FILES/qualitysupport/penaltiesforlatesubmission.pdf
    You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

    Length of examination:

    Requirements for a pass:

    A minimum mark of 50%


    Reassessment arrangements:

    By assessment only in August/September.


    Last updated: 21 September 2017

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