Video Games Sales Report

do step 6 which is the communicating results. the file is uploaded for python. if you you could just write on Microsoft word and send the document.

Problem description: • You are a Data Scientist assigned to perform a comprehensive analysis to provide insights and predictions to the stakeholders for possible future policies/decisions. • You are expected to establish a full design of the Data Analytics life cycle as follows: Page 2 of 3 Expected deliverables for the project You have to run several analyses to fulfil the phases of the data analytics life cycle. 1. Discovery: a. Select a field or topic of your interest. For example, an industrial engineering student is usually interested in supply chain applications. Further, set the objective of the analysis. b. Find a relevant dataset which supports your topic of interest, and the objectives are drawn above. For your ease few data websites are provided below: Google Dataset: https://datasetsearch.research.google.com/ Kaggle: https://www.kaggle.com/datasets Data.Gov: https://data.gov/ Datahub.io: https://datahub.io/collections UCI Machine Learning Repository: https://archive.ics.uci.edu/ml/datasets.php World Health Organization: https://apps.who.int/gho/data/node.home KSA Open Data: https://data.gov.sa/en/home 2. Data Preparation: a. Read the selected data, list the fields/variables and identify their types. b. List the inconsistencies, missing data and outliers. Fix the inconsistencies, impute the missing data and remove the outliers. c. Run the exploratory data analysis: i. Find the statistical summaries. ii. Make univariate graphs (i.e., graphs based on single variable). iii. Prepare bivariate plots (i.e., plots based on two variables). iv. Portray advance graphs (i.e., graphs based on more than two variables). v. Assess the relationship between variables. d. Summarise your findings. 3. Model Planning: In this course, we are covering three models such as regression models, classification models and clustering. Choose the appropriate modelling technique for the successful achievement of your objectives and provide the justification. 4. Model Building: a. Perform the modelling by utilizing the selective parameters obtained from crossvalidation. b. Compare different models based on the performance measures. c. Interpret the findings and provide the details of the final selected model. Page 3 of 3 5. Operationalize: a. Provide the general guidelines to adopt your methodology. b. List the problems and issues in the implementation of the selected methodology. 6. Communicate results: a. Provide the summary and conclusion of your analysis. b. Give possible future recommendations. General notes and guidelines: i. You are required to submit both a report and a PowerPoint presentation of your project. ii. The structure of the report should be outlined such that each section addresses one of the aforementioned deliverables. Your work will be assessed on both the quality of the content as well as the presentation of your material. iii. It is crucial to support your analysis and choices by researching and citing your sources. State any assumptions you make during your analysis and justify them. The credibility of your analysis hinges on how thorough your research is. Note: The plagiarism or copying of the project from any source is not allowed. If we find plagiarised and copying text, then it will be accounted as misconduct. Hence, the respective actions will be taken, and the students are solely responsible for any decision made by the authorities.