2010 Module Vb Regression0

2010 Module Vb - MODULE Vb REGRESSION ANALYSIS Instructor Objective Work required In lab At home Dr Louis Lefebvre To use graphing techniques and

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MODULE Vb REGRESSION ANALYSIS Instructor Dr. Louis Lefebvre Objective To use graphing techniques and regression analysis to analyse the data gathered in Module Va Work required In lab: Discuss and begin data analysis with your TA and group At home: Create your graphs and complete your statistical analyses You are encouraged to discuss the findings and the appropriate graphing and statistical methods to be used, but the actual calculations must be your own work Refer to Module Va for details on the content, format and evaluation of your report METHOD OF EVALUATION 90% will be based on your written report including behavioural observations and regression analysis. Criteria for grading will include the presentation, analysis and interpretation of the data as well as the clarity and stylistic correctness of your write-up: 25% for the introduction, abstract and title page. 20% for the methods. 25% for the results and 20% for the discussion. 10% will be based on your TA's evaluation of your diligence, care and skill in obtaining data and leaving your work area neat and tidy. A key part of this judgement will be based on your contribution to the group discussions and data collecting .
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The purpose of this lab is to introduce you to the statistical technique known as regression analysis . By this technique we estimate the “best fitting” line through a set of data points in order to obtain a graphical depiction of the relationship between two variables of biological interest. The statistical significance of this relationship can then be tested. The following pages provide an overview of fitting and testing your linear regression model. A more detailed description of the regression theory is presented in the lecture. Your TA will help you formulate appropriate null hypotheses and show you how to put your data from Module Va into the right form for doing regression analysis. You will analyse the data gathered in Module Va and present your results in your lab report, written in the format of a scientific paper. Refer to the Report section of Module Va for details of what to include in this lab report. Remember, failure to follow the guidelines for writing a scientific paper (Appendix I in Introduction) will result in loss of marks. Use your TA's feedback on your previous lab report to improve the professionalism of your scientific writing skills. Refer back to Appendix 6 in Module III for tips on performing calculations in Excel. LINEAR REGRESSION ( Y = a + bX ): AN OVERVIEW We will restrict our coverage of regression analyses to the simplest case: a linear regression with one dependent variable Y and one independent variable X. In our example Y depends linearly on X, leading to the name “linear regression”. It is important to realize that there are several types of regressions, each depending on the nature of your predictions and your variables. One is the curvilinear regression, in which the line you are fitting is not necessarily straight; it might, for example, have a U shape of the type Y = a
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This note was uploaded on 02/21/2011 for the course BIOL 206 taught by Professor Prof during the Fall '08 term at McGill.

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2010 Module Vb - MODULE Vb REGRESSION ANALYSIS Instructor Objective Work required In lab At home Dr Louis Lefebvre To use graphing techniques and

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