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Why is the random assignment of individuals to experimental and control groups important for an experiment?
Wiki User
∙ 9y ago
Without random assignment there is a danger of systematic error - or bias - entering into the results. Statistical theory depends on the errors being random and independent error and that is no longer the case without random assignment.
In fact, statistical experiments are often "double-blind": even the observer does not know which individual is in which group. This is to prevent unconscious or subconscious messages to affect the outcome (placebo effects).
Wiki User
∙ 9y ago
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What is the importance of Central Tendency?
Central tendency is important in statistics. It allows individuals to find a representative value, to condense data, and to make comparisons.
Why is it important to do more than one trial in an experiment?
A finding that can't be replicated voids the discovery, diminishes the reputation of those who announce the discovery and can alter or suspend the other research in that area.
Which of the following is an important advantage of experiments over observational studies?
The main possible advantage is that in an experiment, it is possible to control some of the variables so that it is easier to measure the effect of key variables. In observational studies, no such control is possible.
Why is the standard normal distribution important in statistical analysis?
Why is normal distribution important in statistical analysis? Why is normal distribution important in statistical analysis? An important statistical effect was named for this manufacturing plant. What is it? In a famous research study conducted in the years 1927-1932 at an electrical equipment manufacturing plant, experimenters measured the influence of a number of variables (brightness of lights, temperature, group pressure, working hours, and managerial leadership) on the productivity of the employees. The major finding of the study was that no matter what experimental treatment was employed, the production of the workers seemed to improve. It seemed as though just knowing that they were being studied had a strong positive influence on the workers. .The Hawthorne effect
What is statistical treatment in a thesis?
Statistics are simply a tool to help the experimentalist interpret data in an unbiased manner. When properly employed, statistics will not only tell the scientist how "good" his or her numbers are, but can also lead to improvements in experimental design. However, the most important function of a statistical description of data is to remind the experimentalist not to assume any more about his or her results than the data warrant.
Why is it important to control an experiment?
The control experiment allows a standard of comparison for the experimental group
Why is it important to control your experiment?
It's important to control your experiment so that you can be sure the results are due to the experimental variable (independent variable) and not something else.
Why is a control group important to have in a experiment?
A control group is the standard of comparison between what happens with the experimental variable and without the experimental variable.
What can happen once experimental data is analyzed?
Experimental data is an important component of any scientific paper.After looking at the data, we can compare that to our hypothesis and see if it matches to our tentative idea.Analysis of experimental data also helps us to draw a conclusion of an experiment.
Why is it important to identify as much variables as possible in an experiment?
Accounting for errors in an experiment will determine the validity and reliability to the experiment. This, in turn, will either support the experimental results by accepting the null hypothesis or to discard the experimental results by rejecting the null hypothesis
Why do scientists try to test individuals?
In an experiment that involves many people or animals, it is important to test many individuals to avoid experimental error. If only one individual were to be tested in the experiment, it would be difficult to say whether the results were a product of the test, or if it was just a result that the particular individual produced. By testing many, scientists can say definitively that their hypothesis was correct or incorrect because a wide variety of test subjects responded in the same way.
Why do scientists try test many individuals?
In an experiment that involves many people or animals, it is important to test many individuals to avoid experimental error. If only one individual were to be tested in the experiment, it would be difficult to say whether the results were a product of the test, or if it was just a result that the particular individual produced. By testing many, scientists can say definitively that their hypothesis was correct or incorrect because a wide variety of test subjects responded in the same way.
Why is experimental work important to science?
Science is based around experimentation and then creating a theory to support the evidence found through your experiment. Therefore with out experiments you have no science.
When doing experimental research it is important to limit?
When doing experimental research, it is important to limit
Why is it important to identify errors in an experiment?
why is it important to identify errors in an experiment
Why do scientist try to test many individuals?
In an experiment that involves many people or animals, it is important to test many individuals to avoid experimental error. If only one individual were to be tested in the experiment, it would be difficult to say whether the results were a product of the test, or if it was just a result that the particular individual produced. By testing many, scientists can say definitively that their hypothesis was correct or incorrect because a wide variety of test subjects responded in the same way.
Why is it important to wait for an investigation to be repeated many times?
so that you can figure out if it is not basis. To account for any experimental error that may crept in during that investigation. Basically, unknown experimental error, including biases, are best "controlled for" by having a different group repeat the experiment under "similar" conditions.
