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How do you compare scores on different scales?
You calculate a z-score by subtracting the mean of the population from the score in question, and then dividing the difference by the standard deviation of the population. This means that each variable will have a mean of 0 and a standard deviation of 1, so you can compare your different variables meaningfully.
How do you scale one variable to another?
Mathematically, scaled variable would be calculated by subtracting mean of the original variable from raw vale and then divide it by standard deviation of the original variable. In scale() function, center= TRUE implies subtracting the mean from its original variable.
How do you rescale values?
To rescale this data, we first subtract 160 from each student’s weight and divide the result by 40 (the difference between the maximum and minimum weights). are the min-max values.
Can you compare two graphs that use different scales explain your answer?
YES, you can take different scales on the x and y axis of a graph. For example, you can take scale values on x axis in he form of multiples of 2 i.e., 2. and the same you can do for y axis taking the scale values in the form of multiples of 20 i.e., 20, 40, 60, 80, … etc.
How to tell the difference between two z scores?
Comparing z-scores of two points from two different variables can tell you only that one of them is more standard deviations away from mean of its sample comparing to the other.
How many variables are on the same scale?
Low Score High Score Variable Name Trust in Government 1 10 (high trust) TRUST Political Efficacy 0 4 (high efficacy) POLEF Feeling towards President 0 100 (positive energy) LEAD Alienation from politics 8 24 (not alienated) ALIEN
Is it possible to compare two different data sets?
Is it possible to use z-score as a number to compare two different data sets (none of them with normal distribution) and identify which one has an average z-score higher than another? Thanks!
Is the 0-1 scale better than the z-score?
However, scaling in this manner can sometimes lose data points at the extreme ends, depending on the method used. This is an unnecessary loss of data, so unless there is a strong reason for preferring the 0-1 scale, a z-score is generally sufficient for most purposes.