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How can there be a correlation between two things even though one does not cause the other?
Let's say we look at the consumption of junk food and heart attacks. What we would see is a correlation. The more junk food you eat the less risk of a heart attack. There is a correlation but is there a cause and effect relationship?
Probably not. Young people eat a lot more junk food than older people. And older people are much more likely to suffer from a heart attack.
Mathematically this is due to correlation between your x variables. In statistical analysis you usually assume independent variables. In reality thins are much more complicated. If you want to establish true relationships you need to use design of experiments (DoE).
What else can I help you with?
What is the relationship between correlation and causation?
correlation implies the cause and effect relationship,, but casuality doesn't imply correlation.
When two variables are correlated there are four possible explanations of the correlation What are they?
a. The correlation between X and Y is spurious b. X is the cause of Y c. Y is the cause of X d. A third variable is the cause of the correlation between X and Y
Strengths and weaknesses of correlation?
A good starting point to research and very good at showing relationship between variables but doesn't demonstrate cause and effect
When interpreting a correlation coefficient it is important to look at?
When interpreting a correlation coefficient, it is important to consider both the strength and direction of the relationship between the two variables, as indicated by the value of the coefficient (ranging from -1 to +1). Additionally, one should examine the context of the data, including sample size and potential confounding variables, which can influence the correlation. Finally, correlation does not imply causation, so it's crucial to avoid jumping to conclusions about cause-and-effect relationships based solely on the correlation coefficient.
Does correlation prove causality?
No. If Factor X is correlated to Factor Y then you can use one as a predictor of the other, but you should never assume that one causes the other (it may, but correlation alone doesn't prove it).Consider the correlation between proximity to a swampland and chances of contracting malaria. Do swamplands cause malaria? No. Malaria is propagated via mosquitoes which of course love to live in swamplands. So your proximity to a swampland is a useful predictor of your chances of contracting malaria, but doesn't cause it.
What is the relationship between correlation and causation?
correlation implies the cause and effect relationship,, but casuality doesn't imply correlation.
When two variables are correlated there are four possible explanations of the correlation What are they?
a. The correlation between X and Y is spurious b. X is the cause of Y c. Y is the cause of X d. A third variable is the cause of the correlation between X and Y
What is the difference between correlation and cause and effect?
Correlation is a relationship between two variables where they change together, but it does not imply causation. Cause and effect, on the other hand, indicates that one variable directly influences the other.
Is there a correlation between snowfall and phases of the moon in Maine?
There may be a weak correlation, but there is no known mechanism to cause this and it is unlikely one will be found.
What is the difference between cause and correlation?
Cause refers to a direct relationship where one event leads to another, while correlation is a statistical relationship where two events occur together but may not have a direct cause-and-effect connection.
which scenario best illustrates the concept of illusory correlation?
A person believes cell phones cause cancer despite scientific studies finding no correlation between them.
What is the difference between cause and effect vs correlation in research studies?
Cause and effect in research studies refer to a direct relationship where one variable causes a change in another variable. Correlation, on the other hand, indicates a relationship between two variables but does not imply causation. In simpler terms, cause and effect shows a clear cause-and-effect relationship, while correlation shows a connection between variables without proving one causes the other.
What is the difference between cause and correlation?
A cause implies a direct relationship between two factors where one factor results in the other. Correlation, on the other hand, refers to a relationship where two factors are observed to change together but may not have a direct cause-and-effect link. Correlation does not imply causation.
What are the strengths and weaknesses of correlation analysis?
Strengths:WeaknessesCalculating the strength of a relationship between variables.Cannot assume cause and effect, strong correlation between variables may be misleading.Useful as a pointer for further, more detailedresearch.Lack of correlation may not mean there is no relationship, it could be non-linear.
Indicate whether these passages contain a faulty move from correlation to cause. If so state your criticism There is a significant correlation between going to the hospital and dying so hospital are?
Indicate whether these passages contain a faulty move from correlation to cause. If so state your criticism? 1.There is a significant correlation between going to the hospital and dying ,so hospital are important causal factors in the occurrence of deaths.
What is the difference between cause and correlation in research studies?
Cause refers to a direct relationship where one factor directly influences another, leading to a specific outcome. Correlation, on the other hand, indicates a relationship between two factors, but does not imply causation. In research studies, establishing cause requires rigorous testing and evidence, while correlation suggests a potential connection that may or may not be causal.
What is the difference between correlation and causality?
Correlation refers to a relationship between two variables where they change together, while causality indicates that one variable directly causes a change in another. In simpler terms, correlation shows a connection, while causality shows a cause-and-effect relationship.
