Q: What Is a procedure which allows us to predict an individual's score on one variable based on knowing one or more other variables?

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Since there are two variables in this sum, without knowing what one of the variables is, it is impossible to calculate the other variable.

The degrees of freedom is a count of the number of variables which are free to vary. This number can be fewer than the number of variables because of constraints imposed by additional information. Suppose, for example, you have n variables and you also know their mean. Knowing the mean is effectively the same as knowing their sum. So (n-1) of the variables can take any value but, after that, the nth variable must be such that all n of them add to the know sum. Similarly, if you have n variables and are given k means (for k classes), then only n-k of the variables are free to take any value. There are k constraints imposed by the k means.

hi well you are very stupid for not knowing ask your dang on teacher stupid

Without an equality sign and not knowing the plus or minus values of the given terms it can't be considered to be an equation.

You have not told us what expression you wish to simplify.

Related questions

Knowing which is the variable in a laboratory when designing a procedure will help you come up with a number experiments and their possible outcomes.

Since there are two variables in this sum, without knowing what one of the variables is, it is impossible to calculate the other variable.

You can know which is the variable in a laboratory just by observation. The number of times that it has been used in the different procedures will also help you tell which is the variable.

It means there is no discernable relationship between the two variables. Knowing one variable does not give you any help in working out the other. They are independent of each other.

When a variable is declared, your computer assigns a section of memory to that variable. If the variable isn't initialized, there's no way of knowing what data is already stored in that section of memory, which can cause errors in your programs. In managed languages, such as C#, this is done automatically at declaration. Although it's still good practice to initialize variables yourself.

R2 refers to the fraction of variance. it is the square of the correlation coefficient between two dependent variables. It is a statistical term that tells us how good one variable is at predicting another. If R2 is 1.0, then given the value of one variable you can perfectly predict the value of the other variable. If R2 is 0.0, then knowing either variable does not help you predict the other variable. In turn, the higher the R2 value the more correlation there is between the two variables.

Ideally, an experiment should test only one variable (the independent variable) at a time. If you have two or more variables changing at the same time you have no way of knowing which variable is causing your results.

Doing so can enable you to pinpoint which independent variable had what effect on the dependent variable. If more that one variable is altered, there is no way of knowing which of them actually contributed to the change without doing further experimentation.

The degrees of freedom is a count of the number of variables which are free to vary. This number can be fewer than the number of variables because of constraints imposed by additional information. Suppose, for example, you have n variables and you also know their mean. Knowing the mean is effectively the same as knowing their sum. So (n-1) of the variables can take any value but, after that, the nth variable must be such that all n of them add to the know sum. Similarly, if you have n variables and are given k means (for k classes), then only n-k of the variables are free to take any value. There are k constraints imposed by the k means.

To understand this you need to remember that the independent variable is a condition that you can change, and the dependent variable is the outcome that you see. If you have two independent variables, and you change both during an experiment, how are you going to tell which one caused the change to the outcome? So, you only change one independent variable at a time.

No way of knowing, to many variables.

Array elements are all members of the same variable, indexed in a logical manner. variables are distinct objects which must be referred to distinctly. The main functional difference is that a program can iterate over an array without the programmer knowing the original size of the array or explicitly which member to access.