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∙ 16y agoIn any experimental test there are factors that can contribute to error. For example in a biochemical test if you add the compounds with a faulty pippete then the amount of reagent per sample would vary and that would contribute to a noisy measurement. So by controlling experimental conditions as best as one is able error can be reduced. Never completely eliminated, but managed.
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∙ 16y agoThere isn't one. 7 cannot reduce and 18 can reduce, but not in a factor of 7.
Same as fractions. Check if there is a common factor, then divide both numbers by the common factor.
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No birth control in Romania.
You should reduce a fraction if the numerator and denominator have any common factor greater than one.
The significance level can be reduced.
first do you reduce the voltage level or increase the load factor
Kinetic energy is proportional to the square of the speed. If you reduce the speed by a factor of 12, the kinetic energy will reduce by a factor of 12 x 12 = 144.Kinetic energy is proportional to the square of the speed. If you reduce the speed by a factor of 12, the kinetic energy will reduce by a factor of 12 x 12 = 144.Kinetic energy is proportional to the square of the speed. If you reduce the speed by a factor of 12, the kinetic energy will reduce by a factor of 12 x 12 = 144.Kinetic energy is proportional to the square of the speed. If you reduce the speed by a factor of 12, the kinetic energy will reduce by a factor of 12 x 12 = 144.
Controls are designed to reduce or eliminate risk.
no one knows.
The voltage must reduce by the same factor - that is Ohm's law.
The greatest common factor is used to reduce fractions.
It means to divide by x. For example, if I were to reduce 4 by a factor of x, I would get 4/x.If I reduced x by a factor of x, I would get x/x, which is equal to 1.
To reduce fractions
In statistical tests there are 2 main types of Errors, Type I and Type II. Type 1 errors occur when you reject a null hypothesis that is actually true and is thus refereed to as a false positive. Type II errors are essentially the opposite, accepting a null hypothesis that is false, and is often called a false negative. You can reduce the risk of a type I error by lowering the value of P that you're significance test must return to reject the null, but doing so will increase the chance of a type II error. The only way to reduce both is to increase the entire sample size. Alternatively, in some cases, it may also be possible to lower the standard deviation of the experiment, which would also decrease the risk of type I and type II errors.
Controls are designed to reduce or eliminate risk.
There isn't one. 7 cannot reduce and 18 can reduce, but not in a factor of 7.