DAT 375 – Module 6 assignment

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DAT 375 – Module 6 assignment Derek Thurston Southern New Hampshire University February 18th, 2024

I was provided a sample data set of 443 crimes which occurred across nineteen cities in Florida, between January 2019 and October 2019. I took a random sample of 10% of the crime occurrences and reviewed the original data and sample data set for similarities. The top three crime types in the larger data set were Burglary with 93 occurrences, Theft-All Other with 52 occurrences, and Criminal Mischief / Vandalism with 46 occurrences. The sample data set listed the top three crimes as Burglary with 10 occurrences, Theft – All Other with 7 occurrences, and Burglary – Residence with 4 occurrences. The sample data set and the larger data set were consistent with two of the crime types being captured in the top three, Burglary and Theft – All Other. The third crime type in the sample data set, Burglary – Residence was different than the third most frequent crime type in the larger sample – Criminal Mischief / Vandalism. The larger data set contained only 26 Burglary– Residence occurrences, whereas there were 46 Criminal Mischief/Vandalism occurrences. However, even though the top three were different in each data set, Burglary – Residence was still in the top 62% of most frequent crime types. Data Sampling is a statistical analysis technique that analyzes a smaller sample representative of a larger population (Yasar, 2023). There are many techniques for sampling data, however the various techniques are usually distilled into two groups – probability and non-probability sampling. Probability sampling relies on random numbers being attached to each data point in the dataset, while non-probability sampling relies on the analyst’s judgement when choosing

sample data; each of these techniques have their own use cases and are effective means of sampling data depending on the needs of the study. Using these techniques allows analysts to work with smaller, more manageable data sets to produce predictive models quicker while still being accurate. In addition to time savings, data sampling can also result in the removal of bias since a random sample is taken rather than the analyst choosing the specific samples.

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References: Yasar, K. (2023, May). What is data sampling? - Definition from WhatIs.com . SearchBusinessAnalytics. https://www.techtarget.com/searchbusinessanalytics/definition/data-sampling

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