Model Development
Poojan Patel
National Louis University
Heat Map
The below heat map show the relationship between age, hypertension, heart disease as well as stroke.
C:\Users\Bontechq\Desktop\Heatmap.GIF
Multiple Regression Model
When you have more than one independent variable that you are using to predict the dependent variable. And this is a regression model, it does not necessarily determine causality, just how variables covey. The media often mistakes correlation and regression for implying causality. You need an experimental design with appropriate statistical tests to have possible evidence for causality, and further replication and confirmation of the findings.
Not any model fits all situations, each model has its advantages and disadvantages in different situations (Ivanov, 2018). The main idea is that any linear regression can only be approximations of real sets of data, real sets of data are always messier, most data sets would be better approximated by closed curves that surround the data than a single line, or opened curve of any polynomial degree.
The above multiple regression model displays the relationship between age, glucose level and BMI. Where age have a direct impact on the glucose level and BMI have a direct impact on glucose level.
Scatter Plot
Scatter plot displays different numerical values. It is a tool used to observe relationships between numeric variables. In an event you have two variables, plotting them in a scatter plot is the best way to show relationship between the values (Randall, 2019). There are various powerful libraries present in Python and R programming that can help you analyses your data in a better way
The scatterplot above displays the relationship between Glucose levels and age where the higher the age the higher the glucose levels.
Reference
Ivanov, V. (2018). Model development and optimization. Springer Science & Business Media.
Randall, D. A. (2019). General circulation model development: Past, present, and future. Elsevier.
Age Male Female Male Female Female 67.0 61.0 80.0 49.0 79.0 Avg Glucose Level Male Female Male Female Female 22869.0 20221.0 10592.0 17123.0 17412.0 BMI Male Female Male Female Female 36.6 32.5 34.4 24.0
Avg Glucose Level 67.0 61.0 80.0 49.0 79.0 22869.0 20221.0 10592.0 17123.0 17412.0