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What are examples of two variables that are likely to be correlated because they are both changing over time?
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∙ 16y ago
Hight/weight of children until they stop growing
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∙ 16y ago
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What is the meaning of confounding in statistics?
In statistics. a confounding variable is one that is not under examination but which is correlated with the independent and dependent variable. Any association (correlation) between these two variables is hidden (confounded) by their correlation with the extraneous variable. A simple example: The proportion of black-and-white TV sets in the UK and the greyness of my hair are negatively correlated. But that is not because the TV sets are becoming colour sets and so my hair is loosing colour, nor the other way around. It is simply that both are correlated with the passage of time. Time is the confounding variable in this example.
Why is the Gaussian distribution referred to as normal distribution?
Because many naturally occurring variables were approximately distributed according to a Normal bell shaped curve.Because many naturally occurring variables were approximately distributed according to a Normal bell shaped curve.Because many naturally occurring variables were approximately distributed according to a Normal bell shaped curve.Because many naturally occurring variables were approximately distributed according to a Normal bell shaped curve.
Which data collection method accurately measures all variables important to OD?
None, no single method can fully measure the kinds of variables important to OD because each has certain strengths and weaknesses.
What Bar graphs are similar to line graphs because they both?
Represent two variables on two axes.
What is correlation coefficient?
'Correlation coefficient' means a statistic representing how closely two variables co-vary; it can vary from -1 (perfect negative correlation) through 0 (no correlation) to +1 (perfect positive correlation)* * * * *A key piece of information that is left out of the answer by True Knowledge (which casts very serious doubts about its name!) is that the statistic only is a measure of linearrelationship. A symmetric non-linear relationship (a parabola, for example) will show zero correlation but show anyone a graph of a parabola and then try convincing them that there is no relationship between the two variables!A correlation for two variables is a measure of the strength of a linear relationship between them. It is a measure that ranges from -1 (the variables move perfectly together but in opposite directions) to 1 (the variables move perfectly together and in the same direction). A correlation coefficient of 0 indicates no linear relationship between the variables.Two important points to note:Correlation measures linear relationship: not any other relationships. Thus a perfect relationship that is symmetric (y = x^2, for example) will have a correlation coefficient of 0.Correlation coefficient is a measure of association, not of causality. In the UK, ice cream sales and swimming accidents are correlated. This is not because eating ice cream causes swimming accidents not because people recover from swimming accidents by eating ice cream. In reality, both events are more likely on warm days - such as they are!
What are examples of two variables that are likely to be correlated because they are both changing over time -?
Velocity and distance of an accelerating object would be one example.
Does the explanatory variable cause changes in the response variable in a valid sample?
No. It may appear to cause the change because the changes are correlated. However, it is quite possible that changes in both variables are caused by some third, possibly unknown, variable.No. It may appear to cause the change because the changes are correlated. However, it is quite possible that changes in both variables are caused by some third, possibly unknown, variable.No. It may appear to cause the change because the changes are correlated. However, it is quite possible that changes in both variables are caused by some third, possibly unknown, variable.No. It may appear to cause the change because the changes are correlated. However, it is quite possible that changes in both variables are caused by some third, possibly unknown, variable.
What are the shortcomings of correlation?
One shortcoming is the danger of assuming that because 2 variables are highly correlated then one must have caused the other. Correlations alone can never support this assumption.
How are motors and generators examples of energy changing forms?
They are because they can.
What do dependent and independent variables represent in science?
In science, independent variables are variables that you control the change of, to see how somethings changes as a result of changing these variables. Dependent variables are variables that change because the independent variables are changed, but you don't change directly. A good example of this would be an experiment where you're measing how cold a glass of water gets after putting in different amounts of ice in it and wating 5 minutes. The independant variable would be the amount of ice you put into each glass, because that's what you're directly changing. The dependent variable is how cold each glass gets, because that's the result you're trying to see by changing the independent variable - it changes because something else changes. Additionally, when graphing, independent variables are put on the x-axis (horizontal line), and dependent variables are put on the y-axis (vertical line).
How are both motors and generators examples of energy changing form?
They are because they can.
What is the meaning of confounding in statistics?
In statistics. a confounding variable is one that is not under examination but which is correlated with the independent and dependent variable. Any association (correlation) between these two variables is hidden (confounded) by their correlation with the extraneous variable. A simple example: The proportion of black-and-white TV sets in the UK and the greyness of my hair are negatively correlated. But that is not because the TV sets are becoming colour sets and so my hair is loosing colour, nor the other way around. It is simply that both are correlated with the passage of time. Time is the confounding variable in this example.
What does it mean to control the variables in an experiment?
Controls are the things you leave the same when you do an experiment. Variables are the things you affect in an experiment to see if it makes a difference. It depends on the experiment how you would "control" the variable.
How are variables related?
variables are all related because they can equal to any number
How is fame and music correlated with drug abuse?
because music is insperation and the type of music can change your mood
Why do you isolate variables for math?
You isolate variables in math because the point of an equation is to solve for the variables. By isolating the variables you have learned what that variable stands for and thus solved the equation.
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!
