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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.
Are correlation and causation the same thing?
No, correlation and causation are not the same thing. Correlation means that two variables are related in some way, while causation means that one variable directly causes a change in another variable. Just because two variables are correlated does not mean that one causes the other.
What's the difference between correlation and causation?
Correlation is a relationship between two variables where they change together, while causation is when one variable directly causes a change in another variable. Just because two things are correlated does not mean that one causes the other.
In what ways does correlation differ from causation?
Correlation is a statistical relationship between two variables, while causation implies that one variable directly influences the other. Just because two variables are correlated does not mean that one causes the other.
What is a variable called that causes a change in another variable?
A variable that causes a change in another variable is called an independent variable. This variable is manipulated or controlled by the researcher to observe its effect on the dependent variable.
What are the differences between independent and dependent variables?
Independent variables are controlled or manipulated by the researcher to determine their effect on the dependent variable. Dependent variables, on the other hand, are the outcome or response that is measured in an experiment. The independent variable causes a change in the dependent variable.
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 variable causes an effect?
The independent variable is the variable that is changed or manipulated by the researcher and is hypothesized to cause an effect on the dependent variable. The dependent variable is the variable that is measured in response to the changes in 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!
What is the difference between the independent and dependant variable s in an experiment?
The independent variable is the variable that is purposely changed or manipulated by the researcher. The dependent variable is the variable that is measured or observed as a result of changes in the independent variable. In other words, the independent variable causes a change in the dependent variable.
What would be the independent variable in the experiment eating chocolate causes zits?
The independent variable in this experiment would be the consumption of chocolate. It is the variable that is deliberately manipulated by the researcher to observe its effects on the dependent variable, which in this case is the occurrence of zits.
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 the difference between indepedent and dependent variables?
In a science experiment, the independent variable is the one you change. For example: if you are doing an experiment on the impact of different types of soil on plant growth, the different types of soil would be your independent variable. The dependent variable is the outcome, or whatever the independent variable directly impacts. In this case, the dependent variable is the height of each plant.
