Public safety is an important issue in every society. Crime analysis can help governments or
law-enforcing agencies understand crime patterns, prevent and resolve crimes effectively,
making citizens feel safe.
You are given with a dataset “Brazilian_Crimes.csv” that contains a total of 6,672 crime
incident records occurred in Brazil. The description of the dataset is given in Table 1.
Table 1. Description of the dataset “Brazilian_Crimes.csv”
ID Unique identifier of the crime incident
Date Date of the crime incident
Time Time (hour) of the crime incident (E.g., “0” means 12am, “1” means
1am, “12” means 12pm, “13” means 1pm, “23” means 11pm)
Region The region where the crime incident occurs
Crime_Type The type of the crime incident (E.g., Robbery, Theft)
Gender Gender (Female/Male) of the victim
Holiday Whether the crime incident occurs on a holiday (“1” = Yes, “0” = No)
Weekday Weekday of the crime incident
Import the dataset to IBM SPSS Modeler and answer Question 1. Your answer to Question 1
should not exceed 1,000 words, excluding appendices.
(a) It is found that there are values under “Crime_Type” other than “ROBBERY” and
“THEFT”. Prepare the dataset by encoding those values as “OTHERS” using IBM
SPSS Modeler. Provide necessary screenshot(s) to illustrate your data preparation steps.
Apart from the data quality issue mentioned above, identify one (1) more data quality
issue from the dataset. Propose a method to solve it and give reason(s). Then, prepare
the dataset in IBM SPSS Modeler accordingly. Provide necessary screenshot(s) to
support your answers.
(b) Suggest two (2) additional fields that are important for crime analysis. Explain your
(c) It would be interesting to explore how different types of crime are related to different
periods of the day. There are four periods per day: “Dawn” (from 12am to 5am),
“Morning” (from 6am to 11am), “Afternoon” (from 12pm to 5pm) and “Night” (from
6pm to 11pm). Provide necessary screenshot(s) to illustrate how you create a new field
indicating the period of the day in IBM SPSS Modeler accordingly. Then, use data
visualisation techniques to answer the following enquiries:
• What is the type of crime that occurs the most at night?
• Is the majority of victims of theft happened at night male or female?
Provide one (1) graphic display for each enquiry to support your answers.
ANL303 Group-based Assignment
SINGAPORE UNIVERSITY OF SOCIAL SCIENCES (SUSS) Page 4 of 5
(d) Based on the dataset prepared in parts (a) and (c), identify a data mining objective that
can be achieved by association analysis. Then, indicate which fields should be used in
the association analysis to achieve the stated objective.
(e) The law-enforcing agency tried to include the flag fields “Gender” and “Holiday” in the
association analysis where only true values for flags are considered. However, it is
observed that there is a problem with the rules obtained. Identify the problem in this
Someone suggested that one of the solutions is to change the measurement types of
“Gender” and “Holiday” from “Flag” to “Nominal” in IBM SPSS Modeler. Do you
agree? Explain your answers.
(f) Using the dataset prepared in parts (a) and (c), construct an association rule mining
model using Apriori algorithm. Then, analyse the results and suggest two (2) strategies
for the law-enforcing agency to prevent crime. For each strategy, state clearly which
association rule is being referred to.
In your answer, please report the parameters used in the algorithm, and also provide a
screenshot of the association rule(s) that you used for designing the strategies.
In the clothing industry, one of the interesting applications of K-means clustering is to divide
customers into clusters based on their body measurements so as to determine the dimensions
of each size of clothing.
With reference to the six phases of the CRISP-DM framework, discuss how a clothing
manufacturer can plan a data mining project for the abovementioned application. Your
answer to Question 2 should not exceed 600 words, excluding appendices.
Another 10 marks are allocated for your writing.
(Up to 25 marks of penalties will be imposed for inappropriate or poor paraphrasing.
For serious cases, they will be investigated by the examination department. More
information on effective paraphrasing strategies can be found on
Compelling correspondence is essential to the achievement all things considered but since of the changing idea of the present working environments, successful correspondence turns out to be more troublesome, and because of the numerous impediments that will permit beneficiaries to acknowledge the plan of the sender It is restricted. Misguided judgments.In spite of the fact that correspondence inside the association is rarely completely open, numerous straightforward arrangements can be executed to advance the effect of these hindrances.
Concerning specific contextual analysis, two significant correspondence standards, correspondence channel determination and commotion are self-evident. This course presents the standards of correspondence, the act of general correspondence, and different speculations to all the more likely comprehend the correspondence exchanges experienced in regular daily existence. The standards and practices that you learn in this course give the premise to additionally learning and correspondence.
This course starts with an outline of the correspondence cycle, the method of reasoning and hypothesis. In resulting modules of the course, we will look at explicit use of relational connections in close to home and expert life. These incorporate relational correspondence, bunch correspondence and dynamic, authoritative correspondence in the work environment or relational correspondence. Rule of Business Communication In request to make correspondence viable, it is important to follow a few rules and standards. Seven of them are fundamental and applicable, and these are clear, finished, brief, obliging, right, thought to be, concrete. These standards are frequently called 7C for business correspondence. The subtleties of these correspondence standards are examined underneath: Politeness Principle: When conveying, we should build up a cordial relationship with every individual who sends data to us.
To be inviting and polite is indistinguishable, and politeness requires an insightful and amicable activity against others. Axioms are notable that gracious “pay of graciousness is the main thing to win everything”. Correspondence staff ought to consistently remember this. The accompanying standards may assist with improving courtesy:Preliminary considering correspondence with family All glad families have the mystery of progress. This achievement originates from a strong establishment of closeness and closeness. Indeed, through private correspondence these cozy family connections become all the more intently. Correspondence is the foundation of different affiliations, building solid partners of obedient devotion, improving family way of life, and assisting with accomplishing satisfaction (Gosche, p. 1). In any case, so as to keep up an amicable relationship, a few families experienced tumultuous encounters. Correspondence in the family is an intricate and alluring marvel. Correspondence between families isn’t restricted to single messages between families or verbal correspondence.
It is a unique cycle that oversees force, closeness and limits, cohesiveness and flexibility of route frameworks, and makes pictures, topics, stories, ceremonies, rules, jobs, making implications, making a feeling of family life An intelligent cycle that makes a model. This model has passed ages. Notwithstanding the view as a family and family automatic framework, one of the greatest exploration establishments in between family correspondence centers around a family correspondence model. Family correspondence model (FCP) hypothesis clarifies why families impart in their own specific manner dependent on one another ‘s psychological direction. Early FCP research established in media research is keen on how families handle broad communications data. Family correspondence was perceived as an exceptional scholastic exploration field by the National Communications Association in 1989. Family correspondence researchers were at first impacted by family research, social brain science, and relational hypothesis, before long built up the hypothesis and began research in a family framework zeroed in on a significant job. Until 2001, the primary issue of the Family Communication Research Journal, Family Communication Magazine, was given. Family correspondence is more than the field of correspondence analysts in the family. Examination on family correspondence is normally done by individuals in brain science, humanism, and family research, to give some examples models. However, as the popular family correspondence researcher Leslie Baxter stated, it is the focal point of this intelligent semantic creation measure making the grant of family correspondence special. In the field of in-home correspondence, correspondence is normally not founded on autonomous messages from one sender to one beneficiary, yet dependent on the dynamic interdependency of data shared among families It is conceptualized. The focal point of this methodology is on the shared trait of semantic development inside family frameworks. As such, producing doesn’t happen in vacuum, however it happens in a wide scope of ages and social exchange.
Standards are rules end up being followed when performing work to agree to a given objective. Hierarchical achievement relies significantly upon compelling correspondence. So as to successfully impart, it is important to follow a few standards and rules. Coming up next are rules to guarantee powerful correspondence: clearness: lucidity of data is a significant guideline of correspondence. For beneficiaries to know the message plainly, the messages ought to be sorted out in a basic language. To guarantee that beneficiaries can without much of a stretch comprehend the importance of the message, the sender needs to impart unmistakably and unhesitatingly so the beneficiary can plainly and unquestionably comprehend the data.>