代写Assignment 2

日期：2024-05-31 05:25

Assignment 2

2024/6/3 Word Count: 2500

This assessment relates to the following module learning outcomes:

Coursework Brief:

Assignment (individual): Part B (70%): Advanced data analysis using SAS Enterprise Miner

This is an individual part of your assignment using any the datasets provided in part A (i.e. the group assignment). This assignment requires you to analyse the data using advanced statistical techniques such as tree based algorithms (CART/ Random Forests / Gradient Boosting), regression and neural networks.

Please review relevant literature before you begin, and give some thoughts to your research questions and decide your relevant independent and dependent variables or when appropriate moderators and mediators.

Specifically, your tasks include:

1. Examine the dataset and carry out preliminary data analysis to ensure that the data fulfil statistical assumptions prior to actual data analysis.

2. Identify latent factors and assess their reliability, which would help you determine latent constructs and their relationship. This may involve the use of exploratory factor analysis and principal component analysis.

3. Develop a theoretically grounded conceptual model using your knowledge of marketing as a starting point for theoretical reasons, and provide justification for model, such as hypothesized relationships in your conceptual model.

4. Use relevant statistical techniques to check measurement model, and provide measure validation for the hypothesized constructs and overall model.

5. Compute and estimate relationships of your model(s). This includes providing full explanation of SAS outputs and carrying model evaluation when it is appropriate and be supported by theoretical reasoning (if applicable).

Please prepare a technical report (2,500 words) and SAS code scripts / Enterprise Miner diagrams (include good practice of using comment (/*Comment*/).

This report will

complement SAS input (code scripts / diagrams) and SAS output files. The SAS code scripts / diagrams will not be counted in the overall assignment wordcount. In brief, your report will include:

(a) The steps taken in the data analysis process

(b) Details of SAS procedures/nodes used

(c) Choice of analytical methods and implications

(d) Explanation for categorisation and manipulation of the data

(e) Basics of data management

(f) Theoretical and practical arguments for model specification

(g) Specification of the final model based on the data

(h) Model evaluation

(i) An appendix containing replicable SAS code and diagrams

It has to be comprehensive and thorough. Please use 12-point fonts for your report containing your SAS codes/diagrams and relevant data files.

NB: If limitations exist with your approach, that is fine, if those limitations are recognised, they are reasonable and their implications considered thoughtfully.