Medical Analysis Case Study | Using Excel [db7be9]
Post Time: 2025-07-29
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This case study focuses on analyzing a medical dataset using Excel to uncover how health-related factors influence medical charges. The dataset contains 1,339 records and 7 columns representing key attributes. In this analysis, we explore the relationships between variables such as age, BMI, smoking habits, and medical costs, leveraging Excel tools and functions for detailed insights. Dataset Description: The dataset includes the following columns: Age: Age of the primary beneficiary. Sex: Gender of the insurance policyholder Female or Male. BMI: Body Mass Index, which is an objective measure of body weight relative to height . Ideal BMI values range from 18.5 to 24.9. Children: Number of dependents covered under the health insurance plan. Smoker: Indicates whether the beneficiary smokes Yes or No. Region: The residential area of the beneficiary in the US Northeast, Southeast, Southwest, or Northwest. Charges: Individual medical costs billed by health insurance. In this video, we analyzing the following questions : 1. Basic Statistics and Data Understanding - Question: Calculate the average, median, and standard deviation of medical charges, BMI, and age across the entire dataset. - Relevant Excel Functions: AVERAGE, MEDIAN, STDEV 2. Gender Analysis - Question: Compare the average medical charges and BMI between male and female beneficiaries. Which gender has higher average costs and BMI? - Relevant Excel Functions: AVERAGEIF, PIVOT TABLE 3. Impact of Smoking on Costs - Question: Analyze how smoking status influences medical costs. Calculate the average cost for smokers versus non-smokers. - Relevant Excel Functions: AVERAGEIFS, PIVOT TABLE, CHARTS 4. Dependents Analysis - Question: Evaluate the relationship between the number of children/dependents and medical charges. Do beneficiaries with more dependents incur higher medical costs? - Relevant Excel Functions: CORREL, does the keto gummy really work LINE CHART, SCATTER PLOT 5. Geographical Insights - Question: Determine which US region has the highest average medical costs and BMI. Create a pivot table and chart that summarize this data by region. true ketosis keto gummies - Relevant Excel Functions: PIVOT TABLE, AVERAGEIFS, BAR CHART 6.Cost Distribution Analysis - Question: Create a histogram to visualize the distribution of medical charges. Identify the most common cost bracket. - Relevant Excel Functions: HISTOGRAM, FREQUENCY, DATA ANALYSIS TOOLPAK 7. BMI Classification - Question: Classify beneficiaries into BMI categories as pure fuel keto gummies Underweight , Normal , Overweight , and Obese. Count how many beneficiaries fall into each category. - Relevant Excel Functions: COUNTIFS, VLOOKUP with range lookup 8. Advanced Correlation Analysis - Question: Use a scatter plot to analyze the correlation between BMI and medical charges. Add a trendline to the scatter plot to assess the relationship. - Relevant Excel Functions: SCATTER PLOT, TRENDLINE, CORREL 9. Smoking and Region Interaction - Question: Investigate the interaction effect between smoking and region on medical charges. Which region has the highest cost for smokers? - Relevant Excel Functions: PIVOT TABLE, SLICERS, AVERAGEIFS 10. Dashboard Creation for Stakeholders - Question: Develop a comprehensive dashboard that provides stakeholders with insights into medical costs, including filters for gender, smoking status, region, and BMI categories. - Relevant Excel Functions: DASHBOARD DESIGN, PIVOT CHARTS, SLICERS, INTERACTIVE ELEMENTS