论文标题
Covid19（2018-2021）之前和之后的洛杉矶县的犯罪模式
Crime Patterns in Los Angeles County Before and After Covid19 (2018-2021)
论文作者
论文摘要
我们研究的目的是介绍199年后洛杉矶的犯罪率变化。使用Geo-Traping，Bubbles，Marimekko和时间序列图表的数据分析，我们可以说明哪些领域的犯罪率最高，以及它的变化方式。通过回归建模，我们可以解释哪些位置也可能与犯罪，种族，犯罪类型和性别有关联。这个故事将有助于揭示与犯罪相关的领域是否是由于人口统计学或收入差异引起的。在展示洛杉矶犯罪的细节以及发挥作用的因素时，我们希望看到犯罪率与从2020年到现在的最新事件之间存在着令人信服的关系，以及在这些时期犯罪类型趋势的变化。我们使用Excel清理SAP SAC的数据以有效建模，以及其他研究的资源。
The objective of our research is to present the change in crime rates in Los Angeles post-Covid19. Using data analysis with Geo-Mapping, bubbles, Marimekko, and a time series charts, we can illustrate which areas have the largest crime rate, and how it has changed. Through regression modeling, we can interpret which locations may also have a correlation to crime versus income, race, type of crime, and gender. The story will help to uncover whether the areas associated with crime are due to demographic or income variance. In showing the details of crimes in Los Angeles along with the factors at play we hope to see a compelling relationship between crime rates and recent events from 2020 to the present, along with changes in crime type trends during these periods. We use Excel to clean the data for SAP SAC to model effectively, as well as resources from other studies a comparison.
