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There are type 1 and type 2 errors in studies. Type 1 errors are an incorrect rejection of a certain hypothesis. An example is incorrectly diagnosing someone with an illness.

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That depnds on the study

It can have bad consequences either way, depending on the subject of the study.

depends on the consecence of make the mistake sometimes one is worse then 2 and sometimes its the other way round

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What type of things does a agronomist study?????

There are many introductions you could write about the study type method. You could say that the study type method is effective and why it is effective.

mc100202119 1) Errors of Omission 2) Errors of Commission 3) Errors of Principle 4) Errors of Commission

The data type that measures the outcome of a study is quantitative data.

Single -center study

Syntax errors; errors that violate the language rules.

False, Increase the sample size.

A Herpetology is the study of reptile and amphibians.

Punctuation

People who study tornadoes are a type of meteorologist.

Geologists study the Earths surface

A paleontologist would generally study paleontology.

Butterflies and moths are the study area of lepidopterists.

Kamala A. Sardana has written: 'A fresh look at errors in English' -- subject(s): English language, Errors of usage, Indic speakers, Study and teaching, Study and teaching (Higher)

Yes, Type 1 diabetes has been shown to delay the onset of puberty. Results of one study showed a significant delay in puberty in both males and females.

Geologists study Plate Techtonics.

Motion and speed are parts of the study of physics.

A better question is "who" needs to study grammar. If you do not know your grammar, your writing will contain grammatical errors. If your writing is important to your career, you need to study grammar.

An astronomer would study asteroids since they study the universe and planetary motion.

case study

In statistical tests there are 2 main types of Errors, Type I and Type II. Type 1 errors occur when you reject a null hypothesis that is actually true and is thus refereed to as a false positive. Type II errors are essentially the opposite, accepting a null hypothesis that is false, and is often called a false negative. You can reduce the risk of a type I error by lowering the value of P that you're significance test must return to reject the null, but doing so will increase the chance of a type II error. The only way to reduce both is to increase the entire sample size. Alternatively, in some cases, it may also be possible to lower the standard deviation of the experiment, which would also decrease the risk of type I and type II errors.