Assignment 1: Descriptive Statistics Paper

Running Head: ASSIGNMENT 1: DESCRIPTIVE STATISTICS 1
Assignment 1: Descriptive Statistics Paper
Author’s Name
Professor’s Name
Strayer University
MAT300
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ASSIGNMENT 1: DESCRIPTIVE STATISTICS
2
Assignment 1: Descriptive Statistics
Introduction
It is normally hypothesized that there exists some correlation between seasons of the year
and fluctuations in crime statistics. Most researchers believe that there are times of the year when
crime is considerably high compared to other seasons in a year (McDowall, et.al., 2011). If this
assumption is true, then it can be easily demonstrated using descriptive statistical analysis. For
example, the frequency or count of crimes committed in one season will tend to be higher than in
another period of the year. Descriptive statistics are an easy way to evaluate for differences in
two or more datasets. A researcher can use measures of central tendency and dispersion to
clearly demonstrate whether there are contrasts when comparing two datasets. In this research
assessment we will evaluate the journal article “Crime Seasonality: Examining the Temporal
Fluctuations of Property Crime in Cities with Varying Climates” with regard to the application of
measures of dispersion i.e. maximum, minimum, and standard deviation. We will assess how
these measures are used in the formulation of a conclusion relating to the connection between
crime and variation in climate (Linning, et.al, 2016).
Summary
According to Shannon, martin, and Paul (2016), there is a connection between different
property crimes in cities and variations in climate. The article evaluates two research questions
based on data collected from two Canadian cities (Vancouver, and Ottawa). The analysis of this
two sets of data are used to draw conclusions on the state of property crimes in Canadian cities
relative to climatic conditions being experienced (Linning, et.al, 2016).
Descriptive Statistics