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University of Cambridge Training

All-provider course timetable

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Tue 22 Feb 2011 – Wed 16 Mar 2011

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Tuesday 22 February 2011

14:00
Module 4: Linear Regression for Judge students (1 of 4) Finished 14:00 - 16:00 Judge Business School, Computer Room

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 (2 of 4) Finished 14:00 - 16:00 Titan Teaching Room 2

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

Wednesday 23 February 2011

09:30
IOSH Managing Safely (2 of 3) Finished 09:30 - 16:30 Safety Office, Seminar Room 2

Managing Safely is ideally suited to managers, research supervisors, administrators with safety responsibilities and Departmental Safety Officers across all sectors of the University. It leads to a nationally recognised and accredited training certificate. Please contact the course organiser, Will Hudson (wjh29@admin.cam.ac.uk) for further details before booking on the course.

It is an interactive course that includes state-of-the-art animation in the PowerPoint presentation, work books, DVDs, board games and quizzes, assessments, and a risk assessment project.

Friday 25 February 2011

09:30
IOSH Managing Safely (3 of 3) Finished 09:30 - 16:30 Safety Office, Seminar Room 2

Managing Safely is ideally suited to managers, research supervisors, administrators with safety responsibilities and Departmental Safety Officers across all sectors of the University. It leads to a nationally recognised and accredited training certificate. Please contact the course organiser, Will Hudson (wjh29@admin.cam.ac.uk) for further details before booking on the course.

It is an interactive course that includes state-of-the-art animation in the PowerPoint presentation, work books, DVDs, board games and quizzes, assessments, and a risk assessment project.

Monday 28 February 2011

14:00
Module 4: Linear Regression (Series 2) (2 of 4) Finished 14:00 - 16:00 Titan Teaching Room 2

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 10:Time Series Analysis (2 of 4) Finished 14:00 - 16:00 Phoenix Teaching Room

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.

16:00
Module 4: Linear Regression (Series 1) (2 of 4) Finished 16:00 - 18:00 Titan Teaching Room 1

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 4: Linear Regression (Series 3) (2 of 4) Finished 16:00 - 18:00 Titan Teaching Room 2

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.

Tuesday 1 March 2011

14:00
Module 4: Linear Regression for Judge students (2 of 4) Finished 14:00 - 16:00 Judge Business School, Computer Room

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 (3 of 4) Finished 14:00 - 16:00 Titan Teaching Room 2

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

Monday 7 March 2011

14:00
Module 4: Linear Regression (Series 2) (3 of 4) Finished 14:00 - 16:00 Titan Teaching Room 2

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 10:Time Series Analysis (3 of 4) Finished 14:00 - 16:00 Phoenix Teaching Room

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.

16:00
Module 4: Linear Regression (Series 1) (3 of 4) Finished 16:00 - 18:00 Titan Teaching Room 1

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 4: Linear Regression (Series 3) (3 of 4) Finished 16:00 - 18:00 Titan Teaching Room 2

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.

Tuesday 8 March 2011

14:00
Module 4: Linear Regression for Judge students (3 of 4) Finished 14:00 - 16:00 Judge Business School, Computer Room

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 (4 of 4) Finished 14:00 - 16:00 Titan Teaching Room 2

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 10 March 2011

12:00

An introduction to the wide range of resources available at the MML Library and the UL, both in print and online.

Friday 11 March 2011

09:45

How to succeed in your PhD! A one day course which prepares final year PhD students for finishing the writing up, surviving the viva and moving on into postdoc or other employment. All research students in the Graduate School of Life Sciences are expected to attend this highly-recommended course at some point in their final year. The Michaelmas and Easter Term instances are in town and have a bias towards those studying in Biological Sciences; the Lent Term instance is on the Addenbrooke's site and has a bias towards those studying in Clinical Medicine.NB this course replaces both the 'Completing your PhD' and 'FUMO' courses.

Monday 14 March 2011

14:00
Module 4: Linear Regression (Series 2) (4 of 4) Finished 14:00 - 16:00 Titan Teaching Room 2

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 10:Time Series Analysis (4 of 4) Finished 14:00 - 16:00 Phoenix Teaching Room

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.

16:00
Module 4: Linear Regression (Series 1) (4 of 4) Finished 16:00 - 18:00 Titan Teaching Room 1

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 4: Linear Regression (Series 3) (4 of 4) Finished 16:00 - 18:00 Titan Teaching Room 2

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.

Tuesday 15 March 2011

14:00
Module 4: Linear Regression for Judge students (4 of 4) Finished 14:00 - 16:00 Judge Business School, Computer Room

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 16 March 2011

14:00
Laser Safety for Class 3B and 4 Laser Users and Research Supervisors charged (3 of 3) Finished 14:00 - 16:30 8 Mill Lane, Lecture Room 1

This course is an essential component of training for new laser users, which should be backed up by practical training in departments. It will provide you with an introduction to laser safety and the relevant regulations and standards that apply to laser use.

15:00
How to Keep a Lab Notebook (Lecture/workshop) Finished 15:00 - 17:00 Geography Dept

Your lab notebook is one of the most important and precious objects you, as a scientist, will ever have. This session explore how keeping an exemplary laboratory notebook is crucial to good scientific practice in lab research. The course will consist of a short talk, a chance to assess some examples of good and bad practice, with plenty of time for questions and discussion. You might like to bring along your own lab notebook for feedback. (Please note that issues relating to protection of Intellectual Property Rights will not be covered in this session)

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