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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

Q: Define a random experiment sample space simple event and compound event?

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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.

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

The sample size determines the accuracy of results in an experiment

a random friend put

Related questions

Sample: The answer is called Sample space.

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

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}

The answer is Random Sample

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

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.

False

You can overcome or reduce the problem of random error and systematic error while doing an experiment by increasing the sample size, which means averaging over a huge number of observations.

simple random sample is to select the sample in random method but systematic random sample is to select the sample in particular sequence (ie 1st 11th 21st 31st etc.)â€¢ Simple random sample requires that each individual is separately selected but systematic random sample does not selected separately.â€¢ In simple random sampling, for each k, each sample of size k has equal probability of being selected as a sample but it is not so in systematic random sampling.