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University of Cambridge Training

All-provider course timetable

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Sat 12 Feb 2011 – Wed 2 Mar 2011

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Saturday 12 February 2011

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)

Monday 14 February 2011

14:00
Module 3: Bivariate Association (Series 1) (4 of 4) Finished 14:00 - 16:00 Phoenix Teaching Room

This module introduces students to four of the most commonly used statistical tests in the social scinces: Correlations, Chi-square tests, T-tests, and one-way ANOVAs.

Module 3: Bivariate Association (Series 2) (4 of 4) Finished 14:00 - 16:00 Titan Teaching Room 1, New Museums Site

This module introduces students to four of the most commonly used statistical tests in the social scinces: Correlations, Chi-square tests, T-tests, and one-way ANOVAs.

16:00
Module 3: Bivariate Association (Series 3) (4 of 4) Finished 16:00 - 18:00 Titan Teaching Room 1, New Museums Site

This module introduces students to four of the most commonly used statistical tests in the social scinces: Correlations, Chi-square tests, T-tests, and one-way ANOVAs.

Tuesday 15 February 2011

14:00
Module 3: Bivariate Association for Judge Students (4 of 4) Finished 14:00 - 16:00 Judge Business School, Computer Room

This module introduces students to four of the most commonly used statistical tests in the social scinces: Correlations, Chi-square tests, T-tests, and one-way ANOVAs.

Module 9: Meta Analysis (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 methods skills that are relevant across the social sciences.

Module 11: Multilevel Modelling (1 of 4) Finished 14:00 - 16:00 Titan Teaching Room 1, New Museums Site

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

16:00
Module 8: Factor Analysis and SEM (4 of 4) Finished 16:00 - 18:00 Titan Teaching Room 2

Introduction to statistical techniques of Exploratory and Confirmation Factor Analyss. EFA is used to uncover the latent structure of a set of variables. CFA examines whether collected date correspond to a model of what the data are meant to measure. AMOS will be introduced as a powerful tool to conduct confirmatory factor analysis.

Friday 18 February 2011

09:30
IOSH Managing Safely (1 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 21 February 2011

14:00
Module 4: Linear Regression (Series 2) (1 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 (1 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) (1 of 4) Finished 16:00 - 18:00 Titan Teaching Room 1, New Museums Site

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) (1 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 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, New Museums Site

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

09:00
Advanced Gardening Skills (1 of 3) Finished 09:00 - 12:00 Department of Chemistry, Todd Hamied


Learn how to take cuttings, planting, and use machinery

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

Wednesday 2 March 2011

09:00
Advanced Gardening Skills (2 of 3) Finished 09:00 - 12:00 Department of Chemistry, Todd Hamied


Learn how to take cuttings, planting, and use machinery

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