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A random experiment that has exactly two (mutually exclusive) possible outcomes is known as a Bernoulli trial. [2] When an experiment is conducted, one (and only one) outcome results— although this outcome may be included in any number of events, all of which would be said to have occurred
For many experiments, there may be more than one plausible sample space available, depending on what result is of interest to the experimenter. For example, when drawing a card from a standard deck of fifty-two playing cards , one possibility for the sample space could be the various ranks (Ace through King), while another could be the suits ...
In statistical hypothesis testing, a two-sample test is a test performed on the data of two random samples, each independently obtained from a different given population. The purpose of the test is to determine whether the difference between these two populations is statistically significant .
Inherent in conducting observational research is the risk of observer bias influencing your study's results. The main observer biases to be wary of are expectancy effects. When the observer has an expectation as to what they will observe, they are more likely to report that they saw what they expected. [7]
In probability theory, an outcome is a possible result of an experiment or trial. [1] Each possible outcome of a particular experiment is unique, and different outcomes are mutually exclusive (only one outcome will occur on each trial of the experiment). All of the possible outcomes of an experiment form the elements of a sample space. [2]
Test the hypothesis' predictions by an experiment, observational study, field study, or simulation; Draw a conclusion from data gathered in the experiment, or revise the hypothesis or form a new one and repeat the process; Write a descriptive method of observation and the results or conclusions reached
An experiment must also control the possible confounding factors—any factors that would mar the accuracy or repeatability of the experiment or the ability to interpret the results. Confounding is commonly eliminated through scientific controls and/or, in randomized experiments , through random assignment .
In the statistical theory of design of experiments, randomization involves randomly allocating the experimental units across the treatment groups.For example, if an experiment compares a new drug against a standard drug, then the patients should be allocated to either the new drug or to the standard drug control using randomization.