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What is the difference between a bias and a random error?
Bias is systematic error. Random error is not.
How do you overcome or reduce the problem of random error and systematic error while doing an experiment?
how to reduce the problem of random error and systematic error while doing an experiment
What is random error?
Random error is the name given to unforeseen mistakes that occur under secure conditions for various scientific and non-scientific procedures. For instance a mechanical instrument used weighing objects that was affected by unforeseen conditions, such as weather, and even though all necessary pre-cautions were taken, the machine may have given the observer an off the mark weight. Perhaps the observers interpretation of the scale was improper, thus resulting in small degrees of error between that of the actual weight and that of which is observed. This is why scientist conduct their experiments dozens upon hundreds of times, taking multiple measurements and averaging them, to try to minimize random error. Random error is the opposite of Systemic error. The most important thing to remember to understanding what random error is, is that as the name implies it's unpredictable (random).
Can increasing sample size reduce random error?
Random error and sample size have an inverse relationship...As sample size INCREASES random error DECREASES. There's a good explanation at the related link.
Is the random error in a regression equation the predicted error?
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What is a stochastic error term?
A stochastic error indicates an error that is random between measurements. Stochastics typically occur through the sum of many random errors.
What is the difference between a bias and a random error?
Bias is systematic error. Random error is not.
What is random error?
Random error is the name given to unforeseen mistakes that occur under secure conditions for various scientific and non-scientific procedures. For instance a mechanical instrument used weighing objects that was affected by unforeseen conditions, such as weather, and even though all necessary pre-cautions were taken, the machine may have given the observer an off the mark weight. Perhaps the observers interpretation of the scale was improper, thus resulting in small degrees of error between that of the actual weight and that of which is observed. This is why scientist conduct their experiments dozens upon hundreds of times, taking multiple measurements and averaging them, to try to minimize random error. Random error is the opposite of Systemic error. The most important thing to remember to understanding what random error is, is that as the name implies it's unpredictable (random).
How do you overcome or reduce the problem of random error and systematic error while doing an experiment?
how to reduce the problem of random error and systematic error while doing an experiment
Mutations that occur at random are called?
Mutations that occur at random are called spontaneous mutations.
Would you say How this error occurred or how did this error occur?
The question would be the latter "How did this error occur?" The former is the objective form, e.g. "I am trying to discover how this error occurred."
Can increasing sample size reduce random error?
Random error and sample size have an inverse relationship...As sample size INCREASES random error DECREASES. There's a good explanation at the related link.
What are the types of random error?
Random errors can be parallax and from changes in the environment.
Is random error a form of bias?
No, its not.
Is the random error in a regression equation the predicted error?
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What is the difference between random and systemic error?
Systemic or precisely Systematic Error in a reading taken by an instrument occurs due to the parts installed in it. Random error occurs when we get a number of repetitive readings during the same experiment because of human error. Perfect example for random is "Parallax Method".
Can random error be minimized?
The only way to minimize random error is to repeat the experiment more times to get a better average. This means your result is accurate but not percise
