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ASSESSMENT TASKS

Task 1 FORMATIVE TASK Logistic Regression in Principle

FORMATIVE TASK

Instruction: Produce a briefing document for the intern in your department that explains logistic regression and its potential uses in your organisation. The report must contain the following:

• An outline of what is understood by logistic regression, and how it is different from linear
• Identify and explain the characteristics of the Logistic Function, the Odds Ratio and the Logit function
• Discuss the potential uses for logistic regression within your organisation, and a judgment as to its overall value to the organisation

Task 2 SUMMATIVE TASK Logistic Regression in your Organisation

SUMMATIVE TASK

Instruction: Carry out an evaluation of a logistic regression undertaken within your organisation. Your report must contain the following:

• An outline of how Python was used to create the logistic regression, including calculating correctly the probability values of inputs belonging to classes using the Logistic function (LO 1, 3.1)
• Identify and explain how the Odds-ratio metrics were calculated accurately (LO 2,)
• A judgment as to the conclusions that can be drawn from the data, and the accuracy of these conclusions in making future decisions (LO 3, 3.2)

Learning Outcomes: To achieve this unit, the learner must be able to:	Assessment Criteria: Assessment of these learning outcomes will require a learner to demonstrate that they can:
2. Be able to perform logistic regression calculations.	2.1            Calculate correctly the probability values of inputs belonging to classes using the Logistic function. 2.2            Calculate correctly the Odds-ratio. 2.3            Calculate correctly relevant classification evaluation metrics for logistic regression model outputs.
3.     Be able to create logistic regression models.	3.1           Use Python to build an accurate logistic regression model for datasets. 3.2           Use Python to evaluate the accuracy of the model built in 3.1. and analyse the results.