Impact of the outliers on the regression model

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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 Source 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

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

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.

Sample Solution

when predicting attitude stability and the corresponding behavior and judgments of those behaviors. Moreover, Gantman and Van Bavel (2014) found evidence for a moral pop-out effect, such that participants were more likely to recognize moral words over nonmoral words in a lexical decision task.

With regard to group evaluations, it has been shown that moral judgments of one’s ingroup are more important than judgments of competence or sociability (Leach, Ellemers, & Barreto, 2007). Perceiving one’s ingroup as moral has been shown to lead to more positive outcomes of a group’s self-concept, such that positive moral evaluations of one’s ingroup leads to less distancing from that group and greater group identification (Leach et al., 2007). This line of research further extends to the evaluation of outgroups, with the main finding that moral traits are weighted more heavily when members of one group form impressions about an outgroup (Brambilla et al., 2013a). A limitation of this line of research is its focus on conscious, controlled perceptions of morality. Unconscious perception enjoys an extensive influence on social behavior (e.g., Greenwald & Banaji, 1995), and as such studying morality at the unconscious level may reveal interesting differences in explicit versus implicit evaluations of outgroups.

While previous research has provided a solid foundation for understanding just how important moral judgments are to individuals, more work needs to be done to fully examine how quickly moral judgments are made. Limited work has studied the role of implicit cognition in moral judgments, though there is reason to believe that moral judgments may be susceptible to nonconscious influences (e.g., Ma, Vandekerckhove, Baetens, Van Overwalle, Seurinck, & Fias, 2012; Willis & Todorov, 2006). Given that judgments of morality are deemed to be more relevant than other traits when judging whether a target represents a threat (Brambilla et al., 2013b; Willis & Todorov, 2006), we contend that research into the implicit attribution of moral personality traits is warranted to delineate whether morality is attributed automatically or through cognitive processes. This led to our first hypothesis, which predicts that participants will be more likely to recognize moral (versus nonmoral) traits

Spontaneous Trait Inferences

A spontaneous trait inference (STI) occurs when an individual makes a nonconscious, unintentional judgment about the character of another individual (Winter & Uleman, 1984). These inferences occur

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