Compute the equation of the regression line

Reference no: EM132519778

MITS6002 Business Analytics - Victorian Institute of Technology

Question 1. Carefully Read the "CommBank Retail Business Insights Report FY18" provided with this as an attachment and answer the below questions.

i. Comment on the insights report based on the overall features; including the quality of visualisations, presentability, and the information provided.

ii. List the key information you derive from this insights report and explain how they will be useful in decision making.

iii. Write an abstract (one paragraph) summarising the insights report.

iv. Suggest improvements to this insights report.

Question 2. Regression analysis is a commonly used technique to find relationships among variables. Answer the below questions based on regression analysis.

i. Provide an example where regression analysis can be effectively used.

ii. Collect height and weight data from 10 friends/relatives of yours and complete the below table. Every student in class should have a unique set of values.

iii. Draw a scatterplot based on above data. Based on your plot comment on the relationship between height and weight.

iv. Compute the equation of the regression line.

v. Calculate the R² value and comment on the goodness of the fit.

vi. Use an analytics tool of your choice to calculate the values for iv, and v. Compare them with your answer.

Question 3. Classification and regression are commonly used processes in business analytics.

i. Briefly explain the difference between classification and prediction.

ii. Give examples for classification methods you know.

iii. The following diagram shows a neural network with one hidden layer.

483_Business Analytics Assignment.png

Write down the algebraic equation for y₁ in terms of input values i₁, i₂ and weights w.

Briefly explain how neural networks are used for classification.

iv. Give at least three examples how clustering can be used in business analytics. In your answer explain how each business case could be addressed using clustering.

Attachment:- Business Analytics.rar

Reference no: EM132519778

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