Best Answer

There are circumstances when it is important and others when it is not.

If, for example, you wanted a sample of all schools in the country, it would make more sense to go for cluster sampling.

A lot of market research work will require quota sampling.

So the supremacy of a random sample is a myth.

Q: Why the random sample is important in design of experiment?

Write your answer...

Submit

Still have questions?

Continue Learning about Math & Arithmetic

It is important to make sure your random sample is random in order to make sure the results are accurate, and to prevent experimenter bias.

Experiment cannot be predicted in advance is RANDOM EXPERIMENT...... set of all possible outcomes. outcome that can be predicted with certainity. when an experiment performed repeatedly- called trial. Ex. If a coin is tossed,we can't say,whetefr head or tail will appear .so it is a Random Experiment. Sample Space:-- Possible outcomes of a random experiment.. set of all posssible outcomes.. denoted by--- "S". and no. of elements is denoted by n(s). ex. In throwing a dice ,the number that appears at top is any one of 1,2,3,4,5,6 ,So here: S= 1,2,3,4,5,6 n(s) --- 6

It helps you nawser

A random distribution is a random sample set displayed in the form of a bell curve. See random sample set.

to select a random sample you pick them at random

Related questions

Sample: The answer is called Sample space.

It is important to make sure your random sample is random in order to make sure the results are accurate, and to prevent experimenter bias.

bias

A random variable is a function that assigns unique numerical values to all possible outcomes of a random experiment. A real valued function defined on a sample space of an experiment is also called random variable.

controlled experiment

A random sample is a selection from the population of interest where each item (persons, households, widgets, etc.) has an equal chance of being selected. The idea being that measuring a random sample of sufficient size will accurately (within a margin of error) reflect the "true" value that exists in the population - while at the same time reducing your study to a manageable size. A random sample is integral in good survey design to reduce bias in your experiment.

Random sampling is the sample group of subjects that are selected by chance, without bias. Random assignment is when each subject of the sample has an equal chance of being in either the experimental or control group of an experiment.

The set of all possible outcomes of a random experiment is nothing but sample space usually denoted by S. we can also call it as event. For example our experiment is rolling a dice, then our sample space is S= {1,2,3,4,5,6}

Experiment cannot be predicted in advance is RANDOM EXPERIMENT...... set of all possible outcomes. outcome that can be predicted with certainity. when an experiment performed repeatedly- called trial. Ex. If a coin is tossed,we can't say,whetefr head or tail will appear .so it is a Random Experiment. Sample Space:-- Possible outcomes of a random experiment.. set of all posssible outcomes.. denoted by--- "S". and no. of elements is denoted by n(s). ex. In throwing a dice ,the number that appears at top is any one of 1,2,3,4,5,6 ,So here: S= 1,2,3,4,5,6 n(s) --- 6

There is no "most" important. Different solutions are required for different circumstances.

The answer is Random Sample

random sample is a big sample and convenience sample is small sample