Examples of using Independent variable in English and their translations into Thai
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Colloquial
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Ecclesiastic
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Ecclesiastic
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Computer
Here this is the independent variable.
Our independent variable x is the actual exponent.
X3 is going to be kind of an independent variable.
My independent variable is x, I have just swapped t for x there, and I'm taking the integral from 0 to 3.
I switched the dependent and independent variables.
Independent variable frequency speed regulating feeder, feeding capacity can be adjusted steadily and continuously.
So this is the domain, the independent variable, just.
It is often required to interpolate(i.e. estimate) the value of that function for an intermediate value of the independent variable.
Just remember this is the independent variable and this is the dependent variable. .
Rise over run or change in the value of the function divided by change in the independent variable.
Here, we just used y as the independent variable, or as the input variable. .
In engineering and science, one often has a number of data points, obtained by sampling or experimentation, which represent the values of a function for a limited number of values of the independent variable.
But we want to be clear that when we express it like this, the independent variable is x and the dependent variable is y.
So if we viewed a squared as kind of the independent variable or the x term, so now this kind of has the shape of polynomials that hopefully you're used to factoring a.
Notice here, I did multiply stuff times the second derivative, but it was the independent variable x that I multiplied.
So let's put that on the vertical axis. and let's put our independent variable, the one where I just randomly picked values for it to see what y would become.
And then this definite integral function, you have to tell it which is the independent variable, or kind of, you know, what variable are we integrating across, and that's the variable x.
So another way of thinking about the slope of our regression line, it can be literally viewed as the covariance of our 2 random variables over the variance of X. You can kind of view it as the independent random variable.
They are independent random variables.