Individual Assignment 2

docx

School

University of Washington *

*We aren’t endorsed by this school

Course

MISC

Subject

Medicine

Date

Dec 6, 2023

Type

docx

Pages

Uploaded by HighnessMousePerson924

Individual Assignment 2 Q1: If BMI has an impact on the medical costs: Business Insights:  The color differentiation, specifically employing yellow and purple, serves as a visual aid to facilitate the comparative analysis of medical costs within distinct clusters of individuals categorized as smokers and non-smokers across varying Body Mass Index (BMI) levels.  Evidently, a discernible pattern emerges indicating that individuals who smoke tend to exhibit elevated medical costs when contrasted with their non-smoking counterparts.  Upon closer examination, it becomes evident that amongst smokers, a discernible trend is present wherein higher BMI values correspond to escalated medical costs. In contrast, among non-smokers, the correlation between BMI values and medical costs appears to be comparatively less pronounced.

 It is noteworthy that an observable linear relationship seems to exist between BMI and medical cost charges among smokers. This suggests that as BMI increases within the smoking cluster, a proportional increase in medical cost charges can be anticipated. This linear association signifies that the health implications and subsequent medical expenses for smokers become progressively more substantial as their BMI levels rise. Q2: Compare the distribution of the medical costs of smokers and that of non- smokers: Business Insights:  The histograms presented above can be used to discern the contrasting distribution patterns of medical cost charges between individuals identified as smokers and those categorized as non-smokers.  A salient observation arises when scrutinizing the disparities between the two histograms. The distribution of medical cost charges for smokers appears to exhibit a

noticeable rightward shift along the x-axis, indicating a propensity towards higher charges. This divergence in distribution patterns serves as an initial cue suggesting that smoking might indeed be associated with heightened medical costs.  The pronounced shift of the smokers' histogram towards higher cost ranges implies a substantial difference in the economic burden borne by individuals who smoke.  The mode, being the most frequently occurring value, is notably distinct for the two cohorts. Non-smokers exhibit a mode around 1000, indicating a concentration of charges at this relatively lower value. In stark contrast, the mode for smokers is positioned around 20000, markedly elevated in comparison. This contrast underscores a considerable discrepancy in the central tendency of medical cost charges between the two groups.  This divergence in modes becomes pivotal in understanding the disproportionate financial implications associated with smoking-related health issues. Q3: Comparing the distribution of medical costs of young people and that of elder people:

Your preview ends here

Eager to read complete document? Join bartleby learn and gain access to the full version

Access to all documents
Unlimited textbook solutions
24/7 expert homework help

Business Insights:  The histograms serves as a fundamental tool in discerning potential dissimilarities in the distribution of medical costs between two distinct patient age groups: the younger and older populations.  An immediate insight emerges upon scrutinizing the distribution disparities. The histogram pertaining to the younger patient cohort demonstrates a leftward shift along the x-axis, indicating a propensity towards lower medical costs. This initial observation provides a basis for exploring the potential correlation between patient age and corresponding medical expenditure.  The subtle variation in the distribution of younger patients' medical costs being skewed towards lower values is indicative of relatively lesser financial burden associated with medical treatments for this demographic. This trend might be attributed to factors such as generally lower incidence of chronic illnesses and lesser exposure to long-term health complications in comparison to their older counterparts.  Conversely, the histogram representing older patients exhibits a more pronounced spread towards the right side of the x-axis, which conveys a broader distribution of higher medical expenses. This pattern signifies that medical costs tend to escalate with advancing age. This observation is consistent with the well-established notion of increased healthcare utilization and medical needs among elderly individuals due to the prevalence of age-related ailments and chronic health conditions.  The mode of the charge distributions further accentuates the disparities between the two age groups. Younger patients exhibit a mode around 1000, indicating a concentration of medical costs at this lower value. In contrast, the mode for elderly patients is positioned around 10000, significantly higher than that of the younger group. This discrepancy in the central tendency of medical costs strongly indicates a substantial shift in financial implications associated with age-related health considerations. Q4: Plot 1: Medical costs across two genders:

Findings:  The distinction between medical costs for males and females does not exhibit substantial variations across different BMI categories. This observation suggests that, on a general scale, the interplay between gender and BMI does not significantly impact medical costs. This lack of discernible gender-based divergence could reflect the

convergence of other influential factors that collectively contribute to medical expenditure.  However, it's important to note that within the dataset, there exist certain outliers. These outliers manifest as instances where both males and females exhibit high BMI values. Such outliers can potentially be indicative of exceptional cases where individuals exhibit unusually high body mass indexes, which could potentially be attributed to specific medical conditions or other factors. Investigating these outliers could provide valuable insights into the connection between extreme BMI values and subsequent medical costs.  Additionally, the presence of outliers is also notable with regards to charges. In the context of medical costs, these outliers could indicate instances where individuals incurred unusually high charges for medical treatments or procedures. These outliers might warrant further scrutiny to understand the circumstances that led to such atypical medical cost profiles. Such insights could be crucial for identifying exceptional medical scenarios or uncovering potential inefficiencies within the healthcare system.  The presence of outliers in both BMI values and medical charges highlights the importance of investigating exceptional cases. Plot 2: Medical costs across different regions:

Your preview ends here

Eager to read complete document? Join bartleby learn and gain access to the full version

Access to all documents
Unlimited textbook solutions
24/7 expert homework help

Findings:  Initially, it's apparent that there is limited variance in medical cost charges based on the geographical distribution of the beneficiaries. This lack of pronounced variation suggests that the region of residence does not seem to be a dominant factor influencing the charges. This could imply that other variables, such as medical conditions, treatments, or

insurance coverage, might play a more significant role in determining the medical cost structure.  The limited correlation between the region and charges is indicative of the complex interplay of factors that contribute to healthcare expenses. While the geographical location might influence certain aspects of healthcare access and cost, its direct impact on medical charges appears to be subdued in comparison to other influential variables.  The south-eastern regions stand out due to their broader distribution of customer charges. This extended range, reaching up to approximately 20,000, suggests a potentially higher variability in medical costs within these regions. This could arise from a combination of factors, including demographic variations, healthcare infrastructure, and regional health policies.  Outliers are present across all regions in relation to charges. These outliers signify instances where the medical charges significantly deviate from the norm. Plot 3: Age distribution of dataset records Findings:  The Age of the insured approximately follows a uniform distribution with Mean of 39.2 and Median of 39, and with lowest age being 18 and highest being 64.  There are no outlier values in the Age distribution in the data.

Individual Assignment 2

Related Documents