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When two variables are correlated can the researcher be sure that one variable causes the other?
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What third variables might there be that would cause a spurious correlation in the survey results?
The third variable could be one which is correlated to both variables. These are called confounding variable. For example, in the UK you could find a correlation between coastal air pollution and ice cream sales. This is not because eating ice cream causes air pollution nor because air pollution causes people to eat ice cream. The confounding variable is the temperature. Warm weather gets people to drive to the sea!
The causes of muticolinearity in multiple regression?
There is multicollinearity in regression when the variables are highly correlated to each other. For example, if you have seven variables and three of them have high correlation, then you can just use one them in your dependent variable rather than using all three of them at the same time. Including multicollinear variables will give you a misleading result since it will inflate your mean square error making your F-value significant, even though it may not be significant.
What are the three criteria for causality?
• Theories describe the relationships among variables (causation/"prichinnost") X causes Y Example: Education (X) causes the reduction in prejudice (Y)" • Independent variable (X) • Dependent variable (Y)
Can a chi square ever tell us whether one variable causes variations in the second variable?
Regrettably, no. The most a chi-square statistic can do is to participate in the measurement of the level of association of the variation between two variables.
If anxiety and depression are correlated what three possible directions of causality might explain this correlation?
If anxiety and depression are correlated, there are three possible directions of causality. These are anxiety causes depression, depression causes anxiety, and there is an environmental stimuli that causes both anxiety and depression.
On a graph of two variables which is the variable that causes changes in the other?
The independent variable causes changes in the dependent variable; the dependent variable is contingent on the manipulations of the independent variable.
What third variables might there be that would cause a spurious correlation in the survey results?
The third variable could be one which is correlated to both variables. These are called confounding variable. For example, in the UK you could find a correlation between coastal air pollution and ice cream sales. This is not because eating ice cream causes air pollution nor because air pollution causes people to eat ice cream. The confounding variable is the temperature. Warm weather gets people to drive to the sea!
If higher income and job satisfaction are positively correlated which one is true 1. Higher income causes job Satisfaction 2. Job satisfaction causes higher income 3. third variable causes both?
Just because something is positively correlated does not automatically make any of those answers causally relevent.
What is an dependent?
Variables used in an experiment or modelling can be divided into three types: "dependent variable", "independent variable", or other.The "dependent variable" represents the output or effect, or is tested to see if it is the effect.The "independent variables" represent the inputs or causes, or are tested to see if they are the cause. Other variables may also be observed for various reasons.
The causes of muticolinearity in multiple regression?
There is multicollinearity in regression when the variables are highly correlated to each other. For example, if you have seven variables and three of them have high correlation, then you can just use one them in your dependent variable rather than using all three of them at the same time. Including multicollinear variables will give you a misleading result since it will inflate your mean square error making your F-value significant, even though it may not be significant.
What is independent variables?
an independent variable is a variable that changes the dependent variable.___________________________________________________Independentvariableis:a factor or phenomenon thatcausesorinfluencesanotherassociatedfactor or phenomenon called adependent variable. For example,incomeis an independentvariablebecause it causes and influences another variableconsumption. In a mathematicalequationormodel, the independent variable is the variable whosevalueis given. In anexperiment, it is the controlledcondition(that is allowed tochangein asystematicmanner) whose effect on thebehaviorof a dependent variable is studied. Also calledcontrolled variable,explanatory variable, orpredictor variable.
What is an Dependent varible?
Variables used in an experiment or modelling can be divided into three types: "dependent variable", "independent variable", or other.The "dependent variable" represents the output or effect, or is tested to see if it is the effect.The "independent variables" represent the inputs or causes, or are tested to see if they are the cause. Other variables may also be observed for various reasons.
What are the three criteria for causality?
• Theories describe the relationships among variables (causation/"prichinnost") X causes Y Example: Education (X) causes the reduction in prejudice (Y)" • Independent variable (X) • Dependent variable (Y)
What is a indpendent varible?
An independent variable is exactly what it sounds like. It is a variable that stands alone and isn't changed by the other variables you are trying to measure. For example, someone's age might be an independent variable. Other factors (such as what they eat, how much they go to school, how much television they watch) aren't going to change a person's age. In fact, when you are looking for some kind of relationship between variables you are trying to see if the independent variable causes some kind of change in the other variables, or dependent variables.
What is a indpendence?
An independent variable is exactly what it sounds like. It is a variable that stands alone and isn't changed by the other variables you are trying to measure. For example, someone's age might be an independent variable. Other factors (such as what they eat, how much they go to school, how much television they watch) aren't going to change a person's age. In fact, when you are looking for some kind of relationship between variables you are trying to see if the independent variable causes some kind of change in the other variables, or dependent variables.
Third variable problem?
The third variable problem refers to the challenge of determining whether an observed relationship between two variables is direct or if it is influenced by a third variable that was not initially considered. This can lead to spurious or misleading conclusions if the third variable is not accounted for in the analysis. Control variables can help mitigate this issue by accounting for the potential influence of additional factors on the relationship between the two variables of interest.
What are the possible reasons for a correlation between two variables?
Chance association, (the relationship is due to chance) or causative association (one variable causes the other).
