https://github.com/saroshfarhan/world_crime_record_data_analysis

World Crime record 2022 data analysis as part of my assignment in UCD
https://github.com/saroshfarhan/world_crime_record_data_analysis

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World Crime record 2022 data analysis as part of my assignment in UCD

• Host: GitHub
• URL: https://github.com/saroshfarhan/world_crime_record_data_analysis
• Owner: saroshfarhan
• Created: 2025-01-28T17:49:31.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-01-28T17:59:11.000Z (over 1 year ago)
• Last Synced: 2025-01-28T18:35:56.270Z (over 1 year ago)
• Size: 0 Bytes
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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# Conclusion of the analysis

With the given data and the analysis:

-   I cleaned it first by importing the data. I then changed the name of the first column to "Country" so that I can read the data and make it work.

-   I then removed the columns that were redundant.

-   I then added NA values for missing data.

-   I then removed the countries with missing data, the data was removed such that there were no missing values.

-   I then added a new column that summed up data for all columns(offences) and added it to *Total offences* column, for this I first converted all columns from *chr* to *dbl* and then summed it up using *rowSums()*

-   I then produced a table showing country names and record of participation in organized crimes. The table shows data in decreasing order with 1 decimal place.

-   I then produced the country name that has the highest participation in organized criminal group, the country was found to be *Spain*.

-   I then created a scatter plot displaying relationship between *Robbery* and *Unlawful acts involving controlled drugs or precursors* columns.

-   I found out something different from that data that *Spain* had highest number of cases in participation of organized crimes yet it had the least corruption.

-   I then plot a correlation matrix to find some other relations in the offences.

-   I found that there is a positive correlation between *Corruption* and *Attempted intentional homicide,* which makes sense as corruption in governance increases the chances of law and order going down increases which can be seen in the number of attempts in homicides.

-   To confirm my suspicion I also fit the model using *lm()* and found the Std Error to be small (*0.016*) which supported the positive co-linearity which was found in the correlation plot.