In this analysis, I compared the age distribution of individuals involved in police incidents across different racial categories. The main objective was to discern significant differences in the ages of individuals based on their race.

Visualization Method: Box Plot

Explanation:

• X-Axis (Race): I represented each racial category, such as ‘White’, ‘Black’, and ‘Hispanic’, on the X-axis.
• Y-Axis (Age): The age of individuals involved in police incidents was depicted on the Y-axis.
• Box Plot: Utilizing the box plot visualization, I displayed essential statistical metrics such as the minimum, first quartile (Q1), median (Q2), third quartile (Q3), and maximum of the dataset. This graphical representation offered a clear summary of the distribution of ages within each racial category, aiding in the identification of potential outliers.

Through this analysis, I aimed to gain insights into the disparities in age across various racial groups involved in police incidents, thereby contributing to a comprehensive understanding of the data.

Based on the analysis and visualizations performed on the age distribution of individuals killed by police, we can draw several inferences:

I found descriptive statistics Minimum and Maximum Age ,Mean Age, Median Age , Standard Deviation , Skewness , Kurtosis

1. Age Range and Central Tendency:

• The age range of individuals killed by police in the dataset spans from 6 to 91 years.
• The mean age, which is approximately 37.1 years, represents the average age of individuals in these incidents.

2. Distribution Shape:

• The histogram of the age distribution shows a shape that is close to normal (bell-shaped), indicating that the ages are relatively evenly distributed around the mean.
• This is further supported by the Q-Q plot, where the data points lie approximately along a straight line, suggesting that the age data follows a normal distribution.

3. Variability and Skewness:

• The standard deviation of approximately 13.0 indicates that ages vary around the mean by this amount on average.
• The skewness of around 0.73 indicates a slight positive skew, suggesting that the age distribution is slightly skewed to the right. This means there are a few incidents involving individuals older than the mean age, pulling the distribution in that direction.

4. Comparison with Normal Distribution:

• The age distribution, while slightly skewed, does not have extensive fat tails or significant peakiness around the mean (kurtosis is close to 3). This suggests that there are no extreme outliers or highly concentrated age groups.
• The analysis includes a comparison with a standard normal distribution, highlighting that the dataset’s age distribution deviates slightly from a perfect normal distribution.