Workshops

This five-week workshop is for students who wish to improve their academic writing skills in English. To be allowed to attend the workshop, students must agree to do a writing project connected to the research that they are currently conducting in their field of study.

This project, which they will complete over the course of the five week term, will consist in writing a section of text that they can incorporate either into their thesis or into an acamedic article intended for publication.

Each week, the participants will submit between two and three pages of this section of text, which the instructor will revise by providing detailed corrections and commentary, not only to indicate the errors in grammar and syntax, but also to specify the best way to avoid these errors and improve the overall quality of the writing. The weekly workshop sessions will be two hours long, and they will have two main parts:

• A preliminary theoretical presentation during which the instructor will explain fundamental concepts in grammar and syntax related to academic writing in English;
• A text revision practicum during which, under the supervision of the instructor, the participants will do academic writing exercises bases on the texts that they have submitted for their writing projects.

The workshop begins by explaining the role of data preparation in the analysis process and presents the LACED's infrastructure for computing, preparing and analyzing data.

A description of the different financial databases available to the students, researchers and professors via the LACED and the HEC Montréal Library follows. This section is completed by a presentation of the services available to the library's different user categories for the data preparation and analysis, notably workshops and individual support.

There is also a demo on account creation and data extraction on the WRDS platform. Finally, there is a discussion on how to comply to the terms of use of the different licenses for educational and research purposes, from data extraction to the publication of results.

This workshop presents high-quality survey and administrative micro-data, available from Statistics Canada and l'Institut de la statistique du Québec through the Centre interuniversitaire de la statistique sociale du Québec (CIQSS).

These two types of data are accessible through a secure research data centre (RDC) from the Université de Montréal and include confidential and detailed micro-data from over 80 surveys on households and demography, from census master files, commercial data and an increasing quantity of administrative data.

In order to help you choose relevant data for your research, public-use data from Statistics Canada and secured data from the RDC will be examined.

The workshop will look at problems concerning research and data access requests as well as available support to help you analyze your data.

Although data cleaning and preparation is best accomplished via code (with statistical analysis softwares like SAS, R and Python), spreadsheets are overwhelmingly used for data analysis in universities and in the industry. In recent years, the Power Pivot and Power Query add-ins to MS Office Excel allow to handle millions of rows and better track the reshaping of the data, thus overcoming the drawbacks of the spreadsheet. These add-ins are now available to HEC Montreal students.

This workshop assumes a working knowledge of MS Office Excel. Participants are walked through the cleaning of raw firm-level dataset of more than 60,000 lines extracted from Datastream via Thomson Reuters Eikon. After the correction of errors and extraction bugs, the dataset will be prepared for applications like data mining or panel data econometrics.

Detailed explanations will cover MS Excel text functions (TRIM, MID, FIND, LENGTH, CONCATENATE, SUBSTITUTE) and the functionalities of PowerPivot and Power Query for reshaping data. They will also feature Wickam’s principles to design tidy tools for data analysis, which have been largely adopted by the data science community.

Reference:

Wickham, Hadley. "Tidy Data." Journal of Statistical Software 59.1 (2014): 1-23.

Participants will need to use their Gmail account to access the Google Colab platform to run the code.  They will be able to perform their own cleanup of a corporate dataset of over 68,000 lines extracted from Datastream via Thomson Reuters Eikon. 

After errors and extraction bugs have been fixed, issues related to missing data and duplicate observations will be addressed. Then the dataset will be transformed and reshaped for machine learning or panel data econometrics applications. 

Topic highlights

• String manipulation methods (split, strip, join, find, index, replace);
• Regular expressions and Pandas methods for strings (cat, contains, count, extract, findall);
• Pandas methods for reshaping arrays. 

Prerequisites

• Mastering the basics of Python programming, including the Pandas library.
• Having an active Gmail account 

The workshop will first walk the participant through the cleaning of raw bank data from the Orbis Bank Focus database. A worked example with SAS code and macros is provided and the syntax explained. Participants will have the opportunity to run the proposed code chunks in the Lab.

The second part of the workshop will be devoted to how to process untidy data according to the tidy data principle of Wickam, which is becoming more and more popular in data science.

The session will also feature how one can in some cases avoid challenging coding in a SAS if the assignment at hand is related to exploratory or early stages of a research project, so that a quick solution with Excel is more suitable. Participants are expected to have basic skills in SAS programming.

This hands-on workshop is for students who wish to improve their documentary research skills.

Participants will work on a topic of their choice by preparing a concept plan and applying search techniques in a few databases such as Web of Science, ABI Inform Complete and Google Scholar. Some library services will also be presented.

Use all the available resources to find information, for your research project, your dissertation or your thesis.

• Research stategies
• Using specialized databases
• Evaluation criteria
• Bibliometrics

Addresses the ethical use of information.

Explains the different aspects of using information in the students' work in order to prevent plagiarism.

Contents:

1. The ggplot2 library
   1. Overview of library options
   2. Graphics syntax
   3. Data layout
2. Creating reports and presentations
   1. Rmarkdown language
   2. Creating slides with Beamer and knitR
   3. R source code integration in LaTeX documents

  Prerequisites

Participants must have a basic knowledge of R.

Contents:

1. Functions
   1. Function properties: lexical scoping and embedded environments principles
   2. Creating your own functions
   3. Functions calling functions and functions as function arguments
2. Loops
   1. Control structures: for, while, repeat
   2. Vectorized loops: *apply functions
3. Debugging

Although data wrangling (tidying and transforming) is best accomplished via code (with statistical analysis software like SAS, R and Python), spreadsheets are overwhelmingly used for academic teaching and prominent academic works and data management.

This workshop assumes a working knowledge of MS Office Excel. Initial topics include a quick review of intermediate level features and tools of Excel for data wrangling:  properties of List range and Tables, sorting and filtering, Pivot Tables and popular functions like VLOOKUP, RANK, and MATCH. The review will also cover the use of common text functions (CONCATENATE, UPPER, LOWER, PROPER, TRIM) to clean data, as well as date formats.

Issues related to data organization in spreadsheets are then presented. We’ll show how these MS Excel tools can be applied to untidy data according to the tidy data principle of Wickam, which is becoming more and more popular in data science. Time will also be devoted to data organization steps to take in order to protect the integrity of the data, ease analyses and avoid mistakes.

Create a database of your bibliographic references by using the EndNote bibliography management software.

This workshop will help you to:

• organize your references;
• build bibliographies;
• attach PDF files to your databases;
• insert citations in your Word documents using the numerous bibliography styles, and much more.

Learn everything you need to be proficient with the LaTeX document preparation system. Discover the dissertations and theses templates built specifically for HEC Montréal!

Three workshops are offered :

• The basics
• Advanced notions
• hecthese document class

Come meet the library staff to learn more about our services and informational resources!

• Website overview
• Where to find the databases for your research
• HECo, to find books and journal articles
• How to: manage your user profile, book a study room, print your documents, etc.

Become more efficient in your research and make the most out of the library's resources to find reliable information for your work.

• Boolean operators
• Databases
• Research tips
• Beyond Google...

To efficiently search for local and international newspaper articles, come discover Eureka and Factiva.

  Instructor

Caroline Archambault, librarian

  Duration

45 minutes

 Audience

Everyone

 Required material

Laptop

 Schedule and registration

No workshops planned soon

You are looking for data and financial information and you don't know where to start? In this workshop, we will do a hands-on exploration of the NetAdvantage (Standard & Poors) database.

By the end of the workshop, you will be able to:

- efficiently find financial information on companies and industries;

- compare financial results from different companies;

- create and manipulate graphics using the gathered data.

 Workshop slides