Relationship Between Explicit Bias Towards Being Overweight & Heart Attack Mortality

Relationship Between Explicit Bias Towards Being Overweight & Heart Attack Mortality Order Description Please use these sources: 1.) httрs://journals.рlos.org/plosone/artіcle?іd=10.1371/journal.pone.0083543 2.) https://www.obesіty.org/obesіty/resources/facts-about-obesity/bias-stigmatization 3.)https://www.nytimes.com/2017/08/21/well/live/fat-bias-starts-early-and-takes-a-serious-toll.html Introduction (1-2 paragraphs) Describe the relevant background literature on your chosen topic: (I am interested in how attitudes towards weight correlate to heart attack. I expect counties that have more explicit negative attitudes towards being overweight, will be positively correlated to less deaths from heart attack.) - Provide rationale for why you decided to look at these variables and their potential relationship to one another. - Include at least 3 references. (please see above) Method (1-2 paragraphs) Describe how you investigated this relationship in the following sections: - Datasets & sample participants (I used open source software called Jupyter and merged overweight implicit bias data and heart attack mortality data based on county codes. - Analyses Results (1 paragraph) - Write up your results, i.e. what you found. (please see Correlation &; Regression file to analyze) - Include one correlation and one regression. Discussion (1-2 paragraphs) - Explain what you think the finding suggests or reveals. (why is this data important, how can we use this data in the real world?) - Describe limitations and potential directions for future research. HEAVY EMPHASIS ON RESULTS AND DATA MEANING. Please thoroughly analyze the relationship that was found in the data between the two variables and elaborate on why it is significant. correlation analysis: strength of relationship: 0.12684350789110843 p-value: 2.4277609366928609e-123, which is less than 0.5 therefore the relationship is significant regression analysis: both independent variables are under .05 (0.00), therefore they both uniquely contribute to the outcome variable