_____________________models are used to trace cause of occurrence of an eventa.Causal Modelsb.Surrogate modelsc.Linear Regression Models

Causal Models are used to trace the cause of occurrence of an event. These models are designed to show the cause-and-effect relationship between different variables. They are often used in fields like economics, medicine, and social sciences to understand how one factor can influence another.

Here's a step-by-step explanation:

1. Identify the event or outcome you want to analyze. This is what you're trying to explain or predict.

2. Identify the potential causes of that event. These are your independent variables.

3. Use statistical methods to analyze the relationship between your event (dependent variable) and its potential causes (independent variables). This often involves collecting data and running regression analyses.

4. Interpret your results. If your analysis shows that a particular independent variable is significantly associated with your dependent variable, this suggests that the independent variable may be a cause of the dependent variable.

5. Keep in mind that correlation does not imply causation. Just because two variables are associated does not mean that one causes the other. There may be other factors at play, or the relationship may be coincidental.

6. Finally, use your model to make predictions or to inform decisions. For example, if you find that smoking is a significant cause of lung cancer, this information could be used to inform public health policies.