Question

1. Describe and example in which two variables are strongly correlated, but changes in one does...

1. Describe and example in which two variables are strongly correlated, but changes in one does not cause changes in the other. Does correlation imply causation?

2.

A) Give an example of two events that are mutually exclusive (disjoint).

B) Given an example of two events that are not mutually exclusive (not disjoint).

Math   Statistics-And-Probability   
0 0
Add a commentTranscribed image text
Next >

Homework Answers

Answer #1

0 0
Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Log In

Sign Up

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
Describe an example in which two variables are strongly correlated, but changes in one does not...
Describe an example in which two variables are strongly correlated, but changes in one does not cause changes in the other. Does correlation imply causation?
Correlation =/= Causation A lot of data is correlated. In some cases, this is because one...
Correlation =/= Causation A lot of data is correlated. In some cases, this is because one variable causes another. In other cases, things are correlated and neither thing cause the other. I would like for you to think of one such example. 2 variables must be (believably) correlated, but one clearly doesn't cause the other. Thus, your response should have 4 parts to it... ~Thing 1 ~Thing 2 ~Ridiculous claim- thing 1 causes thing 2 or thing 2 causes thing...
What is meant by two mutually exclusive events? Give one example of two mutually exclusive events...
What is meant by two mutually exclusive events? Give one example of two mutually exclusive events and another example of two mutually nonexclusive events.
One of the major misconceptions about correlation is that a relationship between two variables means causation;...
One of the major misconceptions about correlation is that a relationship between two variables means causation; that is, one variable causes changes in the other variable. There is a particular tendency to make this causal error, when the two variables seem to be related to each other. What is one instance where you have seen correlation misinterpreted as causation? Please describe. an orginal post please
One of the major misconceptions about correlation is that a relationship between two variables means causation;...
One of the major misconceptions about correlation is that a relationship between two variables means causation; that is, one variable causes changes in the other variable. There is a particular tendency to make this causal error, when the two variables seem to be related to each other. What is one instance where you have seen correlation misinterpreted as causation? Please describe Can you help me understand how to answer this question
1. a) Give an example of two events that are independent. Prove that your example is...
1. a) Give an example of two events that are independent. Prove that your example is correct computationally. b). Explain why being a dog and being a cat are mutually exclusive. c) Give an example of two characteristics that are not mutually exclusive and explain why they are not.
If two variables are/ have a strong linear correlation, does this mean that one is the...
If two variables are/ have a strong linear correlation, does this mean that one is the cause of the other? Give your opinion and support it with examples
1) In your own words, explain the differences parametric and nonparametric tests. Also noted which kind...
1) In your own words, explain the differences parametric and nonparametric tests. Also noted which kind is preferred to be used. 2) Pictured below is an obvious example of correlation vs. causation. The sun causes ice cream to melt. The sun also causes people to get sunburns. However, melting ice cream does not cause sunburns and vice versa; instead, those variables are correlated with one another. Provide another obvious example of correlation vs. causation. You may not use an example...
Regarding: smoking tobacco cigarettes and lung cancer These two events--"smoking" and "lung cancer"--are strongly correlated, and...
Regarding: smoking tobacco cigarettes and lung cancer These two events--"smoking" and "lung cancer"--are strongly correlated, and clinical trials have been conducted to show that smoking is a contributing factor to the development of lung cancer. Which statement best reflects the relationship between smoking tobacco cigarettes and lung cancer? The relationship is correlated but not causal because lung cancer doesn't cause smoking--the causality only goes one way. The relationship is correlated and causal: smoking causes lung cancer. The relationship is correlated...
correlation measures the degree to which two variables are related to one another. Here are the...
correlation measures the degree to which two variables are related to one another. Here are the definitions of the three possibilities: Positive correlations: In this type of correlation, both variables increase or decrease at the same time. A correlation coefficient close to +1.00 indicates a strong positive correlation. Negative correlations: This type of correlation indicates that as the amount of one variable increases, the other decreases (and vice versa). A correlation coefficient close to -1.00 indicates a strong negative correlation....
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT