Reference no: EM132376594

Data Science Assignment -

Objectives - Assessment is an individual assessment. In assessment, you are assigned tasks which assess your unit knowledge gained about different facets of Data Science and its applications. You are required to write a report discussing the tasks given below. You will also be developing an analytic dashboard using R language.

The tasks - You are a new data scientist hired by an aviation industry. The industry is facing a problem of fluctuating passenger numbers in the airport. As a result, it costs the industry several thousands of dollars in order to maintain the airport services. So, the aviation industry wants to get insightful information about the variation in passenger numbers that will help the management to make necessary arrangements to handle it.

The aviation industry has a dataset (historical) collected over a time period. You can download this data You load download this data in your working directory by using the following command.

data(AirPassengers)

The main objective of the assessment task is to perform an exploratory analysis of the historical data to see the different trends of passenger numbers and predict the future trends.

As a data scientist, you have been requested to prepare a report to demonstrate the outcomes of your analysis to the executives. Your target audience, the executives of aviation industry, have extensive business experience but limited ICT knowledge. They would like to see how aviation industry may be benefitted by the new findings.

To accomplish this task, you are required to do critical thinking about the data quality and findings. You are required to think what kind of other problems can be solved with the provided dataset and what other datasets can be added. Please provide a small description on it.

The main body of the report should include the following analyses.

• Write R code to display the summary of the data. Write down a summary of your analysis with a proper screen shot.
• Write R code to plot the raw data as a graph. Write down a small summary of your analysis with a proper screen shot.
• Write R code to decompose the time series data into trend, seasonal and random components and display the result in a graph (Hint: use decompose() function).
• What kind of predictive model would be good for the given dataset? Why?
• Develop a predictive model from the given dataset (Hint: use ARIMA). You need to compare the prediction made from the predictive model with the actual data. Write down your analysis with a proper screenshot.
• Develop another predictive model using the given dataset (Hint: use linear regression). Write down your analysis with a proper screenshot.
• Make a comparison between two models based on the results. Write down your analysis with a proper screenshot. (Hint: use plot() function).

The report should be well researched and written in accordance with Harvard referencing style. The length of the assignment is 2000 words. The standard report structure, including an executive summary, must be adhered to. Also the report structure should be clear, easy to read and logical, directly addressing the questions. Suitable headers should be used throughout the report. Good use of graphics and charts should be made. Please check for spelling, punctuation or grammatical errors. If you are using any Internet Source, please reference it correctly.

The report should include the following topics.

Executive Summary: You are required to provide brief but comprehensive synopsis of your proposal, which highlights its key points.

Introduction: You are required to introduce the topic of the report in an extremely engaging manner which arouses the reader's interest. You are required to give a detailed general background that indicates the overall "plan" of the report.

Discussion of topics: You are required to discuss the following topics in depth. Your discussion should display deep analysis of issues with no irrelevant info.

Task 1. Nature of Data

• Data is already provided. You need to discuss the nature of data (i.e., formats, missing value, etc).

Task 2. Data in Action

• Discuss the results of the exploratory analyses mentioned above with proper screen shots.
• Think what other datasets can be added with the given dataset and what kind of analysis you can do by combining these datasets.

Conclusion and Recommendations: You are required to provide a well written summary of the main points an excellent final comment on the topic, and recommendations based on the information provided.

Note - Need R code + 2000 words report. Do not write report in essay form.

Attachment:- Data Science Assignment Files.rar