Hypothesis Test Essay

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Hypothesis test

How to find the sample size for analytical studies and experiments?
State the null and alternative hypothesis.
Choose the statistical test based on the type of predictor and outcome variables.
Choose an appropriate effect size.
Set type 1 (alpha) and type 2 (beta) error.
Use the appropriate table to to look for the corresponding sample size.

Basic Concepts
Hypotheses: Null and Alternative hypotheses
People often look into statistical relationship through the test of significance. It is a procedure by which clinicians collect information and see if it agrees with their initial hypothesis. Hypothesis tests are often used for comparison of two samples from the same pool. While the null hypothesis (H0) agrees both could have
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dealing with a one-sided H1 like (2) and (3) If we are using a significance level of 0.05, we are keeping out alpha in one side only. Say if our test statistics fall into that 5% tail, we are rejecting H0 and accepting H1, which suggests that the sample is either larger or smaller. Otherwise, we are accepting H0, which suggests the two samples are the same.
One tailed tests can have a stronger indication effect, since it would specify if it is stronger or weaker, larger or smaller. However, neglecting the opposite side may lead to some serious misunderstanding.
So, when can we use a one-sided alternative hypothesis?
If you do not care about the other side, e.g. you are only interested to show that the vaccination is not less effective than the vitamin
If you have already known the other side is wrong, e.g. you already know there is no way that the vaccination is less effective than than the vitamin, so you just want to check if it is more effective.

A brief discussion: What is a good hypothesis?
According Hulley et al., a good hypothesis must be based on a good research question and that it should be characterised as simple, specific and stated in
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Effect Size
The magnitude of effect in the target population determines the likelihood of a study being able to show the association between prediction and outcome. The larger the change is, the easier it is to show the relationship in between. However, people often don’t know what is actually happening in the society. Therefore, researchers aim to produce an accurate estimation of the effect magnitude.
Effect size refers to the size of association that wants to be shown. It can be difficult to choose an appropriate one based on the little information in hand. To deal with this, laboratorians may choose the smallest effect size that means something in the medical field or carry out a small pilot study to estimate the standard deviation. Nevertheless, they often need to amend the effect size when the sample is too little that or make use of the standard deviation of the change in variable when the outcome variable changes

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