Fundamentals of Data Analytics
Part 1: The police chief asks you to analyze the logs from emergency 911 calls in the city and then provide a summary of that data. A. Prepare a dataset from the data provided in the “Raw Data” spreadsheet, attached below. Remove any potential errors or outliers, duplicate records, or data that are not necessary. Provide a clean copy of the data in your submission. B. Explain why you removed each column and row from the “Raw Data” spreadsheet, or why you imputed data in empty fields as you prepared the data for analysis. C. Create data sheets using your cleaned dataset, provide each of the following to represent the requested aggregated data. • table: date and number of events • bar graph: date and number of events • table: number of incident occurrences by event type • bar graph: number of incident occurrences by event type • table: sectors and number of events • bar graph: sectors and number of events D. Summarize your observations from reviewing the data sheets you have created Part 2: The state governor has offered an additional funding incentive for police departments that are able to meet the standard of having a minimum of 2.5 officers onsite per incident. The police department has asked you to analyze their data to determine if the department will be eligible for additional funding, using the attached linear regression. E. Describe the fit of the linear regression line to the data, providing graphical representations or tables as evidence to support your description. F. Describe the impact of the outliers on the regression model, providing graphical representations or tables as evidence to support your description. G. Create a residual plot and explain how to improve the linear regression model based on your interpretation of the plot. H. Using the linear regression analysis, explain if the department qualifies for additional state funding, including any limitations posed by the available data to the assessment of the department’s current funding eligibility. I. Describe the precautions or behaviors that should be exercised when working with and communicating about the sensitive data in this scenario. J. Acknowledge sources, using in-text citations and references, for content that is quoted, paraphrased, or summarized. K. Demonstrate professional communication in the content and presentation of your submission.
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