Statistics Project. Analyzing the Impact of Smoking on Life Expectancy

Statistics project. Analyzing the Impact of Smoking on Life Expectancy Objective Investigate how smoking affects life expectancy within a given population, using public health data to understand the correlation between smoking habits and longevity, while controlling for other lifestyle factors. Data Sources Access to datasets from the National Health and Nutrition Examination Survey (NHANES), which include variables like age, smoking status, life expectancy, diet, physical activity, and alcohol consumption. Steps to Address the Task 1. Project Planning ● Research question: How does smoking affect life expectancy? ● Data requirement: A dataset with variables on smoking status, life expectancy, and potential confounders. 2. Data Collection ● Hypothetically use the NHANES dataset, ensuring it includes the necessary variables. 3. Data Cleaning and Preparation ● Remove missing data for crucial variables. ● Ensure correct data formats, categorizing smoking status into current smoker, former smoker, and never smoked. 4. Descriptive Statistical Analysis ● Calculate mean, median, and standard deviation of life expectancy for each smoking status group. ● Visualize the data distribution and preliminary relationships using histograms and scatter plots. 5. Inferential Statistical Analysis ● Perform correlation analysis to examine relationships between variables. ● Use multiple regression analysis with life expectancy as the dependent variable and smoking status, along with other lifestyle factors, as independent variables. 6. Interpretation of Results ● Interpret the regression coefficients, focusing on the impact of smoking on life expectancy. A negative coefficient for smoking status that is statistically significant would indicate a detrimental effect of smoking on life expectancy. 7. Reporting ● Write a comprehensive report detailing the methodology, analysis, results, and discussions. Highlight the statistical significance and practical implications of the findings, suggesting public health interventions to reduce smoking rates. 8. Presentation ● Prepare a presentation summarizing the project's objective, methodology, key findings, and implications. Use visual aids to illustrate the negative impact of smoking on life expectancy and advocate for targeted public health policies. Notes ● Validate sources and ensure ethical use of data. ● Remain objective and aware of potential biases in analysis and interpretation. ● Collaboration and consultation can enhance the project's depth and breadth. - Dataset I have a dataset with 1000 individuals, with the following columns: ● ID: Unique identifier for each individual. ● Age: Age of the individual. ● Smoking_Status: Categorized as 0 (never smoked), 1 (former smoker), or 2 (current smoker). ● Life_Expectancy: Estimated life expectancy in years. I will generate this data, perform statistical analysis, and interpret the results. Step 1: Generate Data First,I'll create a dataset with the described structure. Let's assume the following for simplicity: ● Never smokers have a life expectancy of around 82 years. ● Former smokers have a life expectancy of around 78 years. ● Current smokers have a life expectancy of around 75 years. Step 2: Descriptive Analysis (Expected Outcomes) From the descriptive statistics, I'd expect to see: ● Never Smokers (0): A higher mean life expectancy, possibly around the 82 years we set, with a standard deviation reflecting the variance introduced. ● Former Smokers (1): A lower mean life expectancy than never smokers, aimed at 78 years in our dataset generation logic. ● Current Smokers (2): The lowest mean life expectancy, targeting around 75 years due to the additional negative adjustments. Step 3: Inferential Analysis ● One-way ANOVA: This test would likely indicate a statistically significant difference in life expectancy among the three groups, given the way I constructed the differences in life expectancy based on smoking status. ● Tukey's HSD Post-hoc Test: This test would help us identify specifically between which groups the differences are significant. I'd expect to find that: ● Current smokers have a significantly lower life expectancy than never smokers. ● Former smokers also have a lower life expectancy than never smokers, but possibly to a lesser extent than current smokers. ● There might also be a significant difference between former smokers and current smokers, reflecting the impact of quitting smoking. Step 4: Interpretation Based on these hypothetical results, I could conclude that smoking has a detrimental effect on life expectancy, with current smokers being the most adversely affected. Furthermore, the results suggest that quitting smoking can partially mitigate this negative impact, as evidenced by the difference between former and current smokers. This analysis would support public health initiatives aimed at preventing smoking initiation and encouraging smoking cessation. Moreover, it highlights the importance of considering lifestyle factors in public health research and policymaking.