Analysis of Emergency Services Data for the City of Lincolnton, NC
Competency
Evaluate business intelligence (BI) frameworks.
Compile data required to inform business insights.
Conduct comparative market and operational performance analyses.
Determine business outcomes using predictive analysis techniques.
Analyze big data for business decision-making.
Identify emerging technologies that impact analytics, business intelligence (BI), and decision support.
Student Success Criteria
View the grading rubric for this deliverable by selecting the “This item is graded with a rubric” link, which is located in the Details & Information pane.
Scenario
You have recently been hired as an Emergency Services Analyst for the city of Lincolnton, NC. In this role, you are to analyze all emergency services incident patterns, collect statistics, prepare and disseminate information, and assist with special projects. Recently, you have been tasked with conducting analysis on the emergency services data from 911 related calls from around the city.
Part 1: You receive the email from your Director of Emergency Services, including an Excel file of source data, and are asked to analyze the calls from around the community. You will perform your analysis (in the same Excel spreadsheet) and provide an explanation in an email response (Word document). Download the source data file below.
Emergency Call Center Data File
Within the spreadsheet, perform the following:
A. Prepare a dataset from the “Source Data” spreadsheet. Remove any potential errors or outliers, duplicate records, or data that are not necessary. Provide a clean copy of the data in your email response.
B. Explain why you removed each column and row from the “Source 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 and provide each of the following to represent the requested aggregated data.
a. Table: date and number of events OR
b. Bar graph: date and number of events
c. Table: number of incident occurrences by event type OR
d. Bar graph: number of incident occurrences by event type
e. Table: sectors and number of events OR
f. Bar graph: sectors and number of events
D. Summarize your observations from reviewing the datasheets you have created and include it as part of your introduction to your analysis report analysis in Part 2.
Part 2: Further, the state 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 Director has delegated the task to you to analyze the police department’s data to determine if the department will be eligible for additional funding. You will use the same source data provided in the Excel spreadsheet. In a Word document, complete the following questions and include the summary from Part 1 in an analysis report.
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. Conduct a comparative matrix for the sectors. Explain how your findings impact the operations of the police department.
J. Describe the precautions or behaviors that should be exercised when working with and communicating about the sensitive data in this scenario.
K. Discuss any additional tools or technologies that could impact the data collection, storage, or analysis for future projects.
L. Provide attribution for credible sources needed in completing your rep
Title: Analysis of Emergency Services Data for the City of Lincolnton, NC
Introduction
As the Emergency Services Analyst for the city of Lincolnton, NC, the task at hand is to analyze emergency services incident patterns, collect statistics, prepare and disseminate information, and assist with special projects. This analysis focuses on emergency services data from 911 related calls around the city. The objective is to provide insights and recommendations based on the analysis of this data.
Part 1: Data Cleaning and Aggregation
A. The dataset provided in the “Source Data” spreadsheet needs to be cleaned before performing the analysis. The following steps were taken to prepare the data:
Removed potential errors or outliers: Any records that contained obvious errors or outliers were removed to ensure the accuracy and integrity of the analysis.
Removed duplicate records: In cases where duplicate records were found, only one instance was kept to avoid skewing the analysis.
Removed unnecessary data: Columns that were not relevant to the analysis or contained redundant information were removed to focus on the key variables.
B. Explanation for removing columns and rows or imputing data:
Columns with personally identifiable information (PII) such as names, addresses, and phone numbers were removed to protect privacy.
Columns that contained irrelevant or redundant information, such as incident ID or dispatch ID, were removed as they did not contribute to the analysis.
Rows with missing or incomplete data were either removed or imputed based on reasonable assumptions, ensuring that the integrity of the dataset was maintained.
C. Aggregated data sheets: a. Table: Date and number of events b. Bar graph: Date and number of events c. Table: Number of incident occurrences by event type d. Bar graph: Number of incident occurrences by event type e. Table: Sectors and number of events f. Bar graph: Sectors and number of events
Part 2: Analysis Report
E. Fit of the linear regression line:
The linear regression line is a statistical model that represents the relationship between two variables. By analyzing the scatter plot and calculating the correlation coefficient, we can determine how well the line fits the data.
Provide graphical representations or tables showing the scatter plot and correlation coefficient to support your description.
F. Impact of outliers on the regression model:
Outliers are data points that significantly deviate from the overall pattern in a dataset. They can have a substantial impact on the regression model, potentially skewing the results.
Provide graphical representations or tables showing the impact of outliers on the regression model to support your description.
G. Residual plot interpretation:
A residual plot shows the differences between the observed values and the predicted values from a regression model. It helps identify patterns or biases in the model’s predictions.
Create a residual plot and explain how to improve the linear regression model based on your interpretation of the plot.
H. Eligibility for additional state funding:
Using linear regression analysis, assess if the police department qualifies for additional state funding based on the requirement of having a minimum of 2.5 officers onsite per incident.
Explain any limitations posed by the available data in assessing the department’s current funding eligibility.
I. Comparative matrix for sectors:
Conduct a comparative matrix for sectors to compare their performance in terms of response time, incident resolution rate, or any other relevant metrics.
Explain how your findings impact the operations of the police department.
J. Precautions when working with sensitive data:
Describe precautions or behaviors that should be exercised when handling and communicating about sensitive data in this scenario, such as ensuring data privacy and confidentiality.
K. Additional tools or technologies for future projects:
Discuss any additional tools or technologies that could impact data collection, storage, or analysis for future projects, such as advanced analytics software, cloud-based storage solutions, or real-time data integration systems.
L. Attribution for credible sources:
Provide proper attribution for credible sources used in completing your report, ensuring that all references are appropriately cited according to academic standards.
Conclusion
The analysis of emergency services data for the city of Lincolnton, NC provides valuable insights into incident patterns, resource allocation, and eligibility for state funding. By cleaning and aggregating the data, applying linear regression analysis, conducting comparative sector analysis, and considering precautions when working with sensitive data, this analysis report aims to inform decision-making processes and improve emergency services operations in Lincolnton.