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Full List of Courses

Research Methodology and Statistical Courses offered by the SCU

To enrol for any of these courses please contact the CSTAR team on cstar@ul.ie to request a registration form. EHS's PhD's and EPS's PhD students can enrol for free. For others fees can be paid by internal transfer within UL from depts/centres etc or can be paid directly. Numbers will be limited so please contact us asap if you wish to attend. Actual venues etc will be communicated after enrolment a few days before each course to all registered attendees.


Analyses of (Categorical) Survey data
Duration: 1 day

This will provide an introduction to the basic approaches to exploratory data analysis mainly looking at categorical variables (the variables most often found in questionnaire/survey data). No prior knowledge of statistics is assumed although you will require a basic knowledge of using SPSS and/or other statistical software packages e.g. knowledge gained from the above 'Introductory SPSS' course. The course uses sample data from the sciences and social sciences fields but the application is relevant to all subject areas. It covers: ways of exploring variable distributions using tables and charts; use of cross- tabulation and the use of control variables to explore the relationship between categorical variables, chi-squared test & other tests, techniques for recoding and deriving new variables; odds ratios & relative risks, the use of weighting where appropriate. This course is taught by an experienced statistician - advice can be sought during the course for specific research/statistics queries. (It is not advised that this course should be taken together with the Basic Statistics Course as there is much overlapping material)


Exploring Relationships & Regression Analyses
Duration: 1 day

This course will build on ’Analyses of survey data’ and/or Basic Statistics for Researchers by taking a more formal look at the relationships between variables at different levels of measurement but mainly scalar/measurement/continuous variables. It will cover:

  • Exploring relationships with quantitative (scalar/continuous) data
  • Scatterplots
  • Correlation
  • Simple linear Regression
  • Multiple Linear Regression
  • Model building
  • Muliticollinearity
  • Logistic Regression & methods for checking fit & logistic regression model building

Questionnaire Design
Duration: 1
day

This introductory course covers the basic elements of research questionnaire design and question wording. Learn how to construct unbiased questions - the common mistakes and how to put them together in a survey and/or interview schedule that will be easily answered. The different requirements for postal and interview questionnaires as well as online surveys will be emphasised and practical exercises will be given in question wording. Various modes of presentation will be described. Some suggestions for ways of improving response rates will also be given. The course is taught by an experienced researcher and tips and advice will be given for specific surveys.
After the course participants will be able to send their draft questionnaires for review by SCU consultants.


Surveys and Sampling
Duration: 1
day

This course examines how sampling techniques can be applied in survey research. We begin by looking at the role of sampling in the survey process. We introduce the basic principles of sampling theory and how this relates to sampling strategies and sample design in a practical context. Practical exercises address the questions of the required sample size and precision of estimates, sampling strategies and when sample surveys are appropriate. This course, together with the 'Questionnaire Design' course above, provides important guidance for any researcher planning a survey.


Introduction to R
Duration: 1
day

R - a freely available version of the S programming language is becoming more and more popular as a statistical analysis package. R can be downloaded from the web (Download R here) and provides a wide variety of statistical and graphical techniques. R enables the user to have more control over the algorithms used to analyse data and therefore facilitates more sophisticated analyses than allowed by other packages, e.g. SPSS, Minitab, etc. There is also a wealth of support to users on the internet with freely downloadable routines that can be used for specific purposes. It is becoming very popular amongst statisticians and other researchers e.g. within the business and economics fields.

This course will serve as an introduction to the package and its uses at a very elementary level. A high level of statistical knowledge will not be assumed.


Introduction to NVIVO
Duration: 1 day

The objective of this course is to equip you with enough knowledge to enable you to begin your project using a computer-aided methodology. By the end of the course you will understand the advantages and limitations of using a computer for qualitative data analyses and will know how to set-up a database, how to import data and how to code data. You will also understand the potential of NVIVO as a tool for organising, questioning and reporting on the data so that you can truly support and defend your findings.

The depth and breadth to which these topics will be covered will depend on the general level of computer literacy of the group coupled with their experience, if any, of using databases designed for working with qualitative or unstructured data. Participants are encouraged to bring their own data if they have some. Otherwise, tutorial data will be provided on the day. Please note numbers will be limited on this course to enable all to benefit from the course.
(Full post workshop support by telephone, e-mail and on-line one-to-one direct desktop support and consultancy for the life of your current project)


Analysing Data with NVIVO
Duration: 1
day

The objective of this workshop is to conduct a piece of analysis using raw data and a research question. By the end of the session, the participants will have: 1. Set up a database with a robust architecture 2. Analysed the data using queries and manual analysis where appropriate 3. Reported on the findings Please note numbers will be limited on this course to enable all to benefit from the course.
*YOU SHOULD ONLY ENROL ON THIS ONE DAY COURSE IF YOU HAVE ALREADY COMPLETED THE INTRODUCTORY NVIVO DAY COURSE* (preferably at a previous SCU/CSTAR course session) or have used Nvivo before.
(Full post workshop support by telephone, e-mail and on-line one-to-one direct desktop support and consultancy for the life of your current project).


NVIVO Day 3 – Working with live data
Duration: 1 day

The objective of this workshop is to conduct a piece of analysis using raw data and a research question. By the end of the session, the participants will have:

  • Set up a database with a robust architecture.
  • Analysed the data using queries and manual analysis where appropriate.
  • Reported on the findings.

(Full post workshop support by telephone, e-mail and on-line one-to-one direct desktop support and consultancy for the life of your current project).


Introduction to SPSS (v24)
Duration: 1 day

This course provides an intensive introduction to SPSS. It assumes that participants have a basic familiarity with the Windows environment. We examine the features of SPSS for Windows, use a simple data set to cover the topics of transforming variables, selecting data for analysis, then perform basic analyses to produce frequency distributions, summary statistics and cross tabulations before examining some of the extensive graphic capabilities of SPSS. This course would provide an introduction to anyone wishing to analyse their own data using SPSS. This course is taught by an experienced statistician - advice can be sought during the day for specific SPSS problems. Those with sufficient statistical knowledge already would only need to go on this course in order to carry out any analyses. It is not recommended that SPSS and statistics be learnt at the same time.


Introduction to STATA
Duration: 1 day

This is a new course being offered by the Statistical Consulting Unit. We will familiarise ourselves with the point and click menus available in STATA. We will also use the command window to type in commands, offering users a choice in how to approach this software package. We will explore various capabilities of the software e.g. manipulating datasets, producing summary statistics, frequency tables, cross tabulations and also graphical output such as scatter plots, bar-charts, histograms etc.
STATA is compatible on most major operating systems including Windows, Mac & UNIX. It produces publication-quality graphics and is continuously updated with new features.


Exploring Relationships & Regression Analyses
Duration: 1 da
y

This course will build on ’Analyses of survey data’ and/or Basic Statistics for Researchers by taking a more formal look at the relationships between variables at different levels of measurement but mainly scalar/measurement/continuous variables. It will cover:  - exploring relationships with quantitative (scalar/continuous) data

  • Scatterplots
  • Correlation
  • Simple linear Regression
  • Multiple Linear Regression
  • Model building
  • Muliticollinearity
  • Logistic Regression & methods for checking fit & logistic regression model building
  • Also a quick look at other predictive models

Further Data Analysis
Duration: 1
day

This course will build on Exploratory Data Analysis by taking a more formal look at the relationships between variables at different levels of measurement. It will mainly concentrate on the analysis of continuous variables. Formal testing of sampling distributions, the normal distribution, and a quick review of simple parametric and non-parametric hypothesis testing will be covered. The course will also examine correlation between two variables and simple bivariate regression analysis. Again there will be a high practical component with examples based on data provided for the course. Theory will be kept to a minimum.


Basic Statistics for Researchers
Duration: 2 days

This course covers the basic methods of analysis needed for quantitative research. Most researchers would find the material covered would be sufficient to analyse any data gathered as part of their research (both categorical and continuous variables). No prior knowledge of statistics is assumed although you will require a basic knowledge of using SPSS and/or other statistical software packages e.g. knowledge gained from the above 'Introductory SPSS' course. The course uses sample data from the sciences and social sciences fields but the application is relevant to all subject areas. Topics covered include:

  • Sampling
  • Data analysis - an overview; Types of data; Scales of data measurement; Coding questionnaire data
  • Describing data using graphical and numerical methods
  • Normal Probability distributions
  • Coding questionnaire data
  • Confidence Intervals and Hypothesis Testing (Parametric and non-parametric)
  • Multivariable analysis - Qualitative (categorical) variables; Chi-squared Tests
  • Multivariable analysis - Quantitative (continuous) variables - Scatter plots, correlation and regression.

This course is taught by an experienced statistician - advice can be sought during the course for specific research/statistics queries.


Introduction to Structural Equation Modelling (Using Mplus)
Duration 2
days

This workshop is intended as an introduction to SEM based statistical methods that are becoming increasingly popular in the socio-behavioural sciences. The course will cover many of the main uses of SEM such as confirmatory factor analysis, path analysis (with and without error), and modelling the relationships between latent variables. Each day will be comprised of a taught component, a practical session, and a question and answers session. No experience of the software is required. Topics will include:

  • Recent developments in multivariate analysis.
  • The general linear model.
  • Measurement models and confirmatory factor analysis.
  • Path analysis and regression models.
  • The full structural equation model.
  • Assessment of model fit.
  • Approaches to dealing with missing data

This workshop is intended as an introduction to SEM based statistical methods that are becoming increasingly popular in the socio-behavioural sciences. The course will cover many of the main uses of SEM such as confirmatory factor analysis, path analysis (with and without error), and modelling the relationships between latent variables. Each day will be comprised of a taught component, a practical session, and a question and answers session. No experience of the software is required. AMOS (now available with SPSS v22) will also be mentioned.


Introduction to Design of Experiments
Duration: 1 day

This is a new course being offered by the Statistical Consulting Unit. It covers the principles of DOE but at an introductory level. It would be useful for anyone new to research in the sciences that needs to understand these principles before planning their research. It will cover simple DOE techniques, when they are applicable, how to design efficient experiments and an introduction to analysing the results. During the day you will also be introduced to a simple DOE package. It will not be possible in one day to look at more complicated designs but you will be introduced to enough methodology to be able to investigate these further if needed.

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