Discipline-specific knowledge and capabilities appropriate to the level of study related to a discipline or profession.
Digital Literacy Using technologies to find, use and disseminate information
Problem Solving creating solutions to authentic (real-world and ill-defined) problems.
To accomplish allocated tasks, you need to examine and analyse the dataset thoroughly. Below are some guidelines to follow:
The purpose of this task is to analyse and explore key features of these two variables individually. At very least, you should thoroughly investigate relevant summary measures of for these two variables. Proper visualisations should be used to illustrate key features of these two variables. Your technical report should describe ALL key aspects of each variable.
Identifying relevant factors for predicting customer satisfaction Analyse the relevant dependent variable against other variables included in the dataset. Your job is to decide which variables to include here. Use an appropriate technique to identify important relationships.
The outcome of this task is a list of variables that should be included in the subsequent analysis. Your technical report should describe why some variables were selected while others were dropped from subsequent analyses.
You should start building the predictive model by including ONLY the variables listed in the ‘minutes of the meeting You are required to demonstrate all iterations of your predictive model. Note that your final model should only include those variables that have predictive value.
Visualising and Interpreting Predicted Probabilities
“How change product quality and price flexibility may affect the predicted probability of building strategic alliance with AusPaper for customers who have neutral feeling towards personnel image and product line?”
In your technical report, you must explain the reason for selecting the forecasting method to predict future turnover. The report also must include a detailed interpretation of the final model.
ALL aspects of your analysis and final outputs must be described/interpreted in detail. Remember, your audience is an expert in Analytics and he expects nothing but perfection from your report. Perfection means quality content demonstrated attention to details as well as an aesthetically appealing report.