All-provider course timetable
Tuesday 21 February 2012
| 14:00 |
Module 10:Time Series Analysis
Finished
This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences. The module introduces time series techniques relevant to forecasting in social science research and computer implementation of the methods. |
|
Module introduces students to one of the most fundamental statistical techniques, namely regression analysis. Students learn about assumptions underlying regression models, how to run regression analysis using SPSS and how to access and solve possible problems with a regression model. |
|
| 16:00 |
Module introduces students to one of the most fundamental statistical techniques, namely regression analysis. Students learn about assumptions underlying regression models, how to run regression analysis using SPSS and how to access and solve possible problems with a regression model. |
|
Module introduces students to one of the most fundamental statistical techniques, namely regression analysis. Students learn about assumptions underlying regression models, how to run regression analysis using SPSS and how to access and solve possible problems with a regression model. |
Wednesday 22 February 2012
| 14:00 |
Module introduces students to one of the most fundamental statistical techniques, namely regression analysis. Students learn about assumptions underlying regression models, how to run regression analysis using SPSS and how to access and solve possible problems with a regression model. |
|
Module 11: Multilevel Modelling
Finished
This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research |
Tuesday 28 February 2012
| 14:00 |
Module 10:Time Series Analysis
Finished
This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences. The module introduces time series techniques relevant to forecasting in social science research and computer implementation of the methods. |
|
Module introduces students to one of the most fundamental statistical techniques, namely regression analysis. Students learn about assumptions underlying regression models, how to run regression analysis using SPSS and how to access and solve possible problems with a regression model. |
|
| 16:00 |
Module introduces students to one of the most fundamental statistical techniques, namely regression analysis. Students learn about assumptions underlying regression models, how to run regression analysis using SPSS and how to access and solve possible problems with a regression model. |
|
Module introduces students to one of the most fundamental statistical techniques, namely regression analysis. Students learn about assumptions underlying regression models, how to run regression analysis using SPSS and how to access and solve possible problems with a regression model. |
Wednesday 29 February 2012
| 14:00 |
Module introduces students to one of the most fundamental statistical techniques, namely regression analysis. Students learn about assumptions underlying regression models, how to run regression analysis using SPSS and how to access and solve possible problems with a regression model. |
|
Module 11: Multilevel Modelling
Finished
This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research |
Thursday 1 March 2012
| 09:15 |
Soccer Skills 1
Finished
|
Friday 2 March 2012
| 09:00 |
Soccer Skills 1
Finished
|
Tuesday 6 March 2012
| 14:00 |
Module 10:Time Series Analysis
Finished
This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences. The module introduces time series techniques relevant to forecasting in social science research and computer implementation of the methods. |
|
Module introduces students to one of the most fundamental statistical techniques, namely regression analysis. Students learn about assumptions underlying regression models, how to run regression analysis using SPSS and how to access and solve possible problems with a regression model. |
|
| 16:00 |
Module introduces students to one of the most fundamental statistical techniques, namely regression analysis. Students learn about assumptions underlying regression models, how to run regression analysis using SPSS and how to access and solve possible problems with a regression model. |
|
Module introduces students to one of the most fundamental statistical techniques, namely regression analysis. Students learn about assumptions underlying regression models, how to run regression analysis using SPSS and how to access and solve possible problems with a regression model. |
Wednesday 7 March 2012
| 14:00 |
Module introduces students to one of the most fundamental statistical techniques, namely regression analysis. Students learn about assumptions underlying regression models, how to run regression analysis using SPSS and how to access and solve possible problems with a regression model. |
|
Module 11: Multilevel Modelling
Finished
This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research |
Thursday 8 March 2012
| 12:00 |
An introduction to the wide range of resources available at the MML Library and the UL, both in print and online. |
Tuesday 13 March 2012
| 10:15 |
Guide to Department Funds
Finished
Much of the session comprises a case study based on a medium sized University department. Delegates will examine University regulations and procedures and decide the actions for various scenarios and correct anomalies for selected sources of funds. |
| 14:00 |
Module 10:Time Series Analysis
Finished
This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences. The module introduces time series techniques relevant to forecasting in social science research and computer implementation of the methods. |
|
Module introduces students to one of the most fundamental statistical techniques, namely regression analysis. Students learn about assumptions underlying regression models, how to run regression analysis using SPSS and how to access and solve possible problems with a regression model. |
|
| 16:00 |
Module introduces students to one of the most fundamental statistical techniques, namely regression analysis. Students learn about assumptions underlying regression models, how to run regression analysis using SPSS and how to access and solve possible problems with a regression model. |
|
Module introduces students to one of the most fundamental statistical techniques, namely regression analysis. Students learn about assumptions underlying regression models, how to run regression analysis using SPSS and how to access and solve possible problems with a regression model. |