Probability of an outcome given multiple attributes

In summary, the conversation discusses the attributes of body fat percentage and body mass index, and their correlation with the outcome of obesity. The speaker is seeking information on how to calculate joint probability and how to combine the correlation between the attributes. Suggestions are given to look into regression analysis and discrete choice modeling.
  • #1
redeemer90
4
0
Hi,

Lets say I have the following attributes...
Body fat percentage, Body mass index
Outcome = obese (yes / no)
I have data for all attributes and outcomes. What I'd like to do is a joint probability. For example I'd like to know what the probability is of someone being obese given their BMI and body fat percentage.

I can calculate the correlation between the attributes and the outcomes. My intuition tells me that I need to combine the correlation in some way, but can't seem to find any information on this.

Can someone point me in the right direction?

- Sid
 
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  • #5
Thanks for all the help. Will look into all the links now and see which one suits my needs.

- Sid
 

1. What is the definition of probability?

Probability is the measure of how likely an event is to occur. It is expressed as a number between 0 and 1, with 0 representing impossibility and 1 representing certainty.

2. How is probability calculated?

The probability of an event can be calculated by dividing the number of favorable outcomes by the total number of possible outcomes. This is known as the classical probability approach.

3. What is the difference between independent and dependent events?

Independent events are events that do not affect each other, meaning the outcome of one event does not impact the outcome of the other. Dependent events, on the other hand, are events where the outcome of one event does affect the outcome of the other.

4. How does the number of attributes affect the probability of an outcome?

The more attributes that are involved in an event, the lower the probability of a specific outcome. This is because the number of possible outcomes increases with each additional attribute, making it less likely for a specific outcome to occur.

5. What are some real-life examples of probability with multiple attributes?

Some examples include predicting the likelihood of a person having a certain medical condition based on their age, gender, and family history, or predicting the chances of a stock market investment being profitable based on market trends, company performance, and economic conditions.

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