7. No Multicollinearity
- We observe Multicollinearity when two or more Independent Variables in a model are “Highly Correlated”.
- Correlation could be Positive (or) Negative.
- This will lead result in less reliable predictions.
- Multicollinearity can be noticed easily by finding the correlation between each two pairs of Independent Variables.
2
19 reads
CURATED FROM
IDEAS CURATED BY
These are some of the Assumptions to be pondered while Applying Ordinary Least Square Method and Performing Regression Analysis.
“
Similar ideas to 7. No Multicollinearity
Correlation is not causation
- Correlation: Scientists may find that two variables are correlated. They may be related, but it doesn't mean that one is causing the other. It could be a coincidence, or perhaps a third variable is causing both of the other two.
- Causation: Lots of ...
How to turn one tiny thought into a blog post worth reading (contd.)
3. Expand with ideas
Let's say you're working with something concrete—an interesting finding from your experience, data from an experiment you tried, or a trend in customer feedback or behaviour. You can add your own thoughts and ideas to the concrete tidbit you've got to c...
Positive And Negative Effect
- The Law of Effect has two parts, and records contrasting behaviours. If the effect is positive and leads to satisfaction, it forms a connection in the mind and will be repeated.
- The actions that lead to negative effects or consequences, or which lead to discomfort for the doer, are...
Read & Learn
20x Faster
without
deepstash
with
deepstash
with
deepstash
Personalized microlearning
—
100+ Learning Journeys
—
Access to 200,000+ ideas
—
Access to the mobile app
—
Unlimited idea saving
—
—
Unlimited history
—
—
Unlimited listening to ideas
—
—
Downloading & offline access
—
—
Supercharge your mind with one idea per day
Enter your email and spend 1 minute every day to learn something new.
I agree to receive email updates