What does statistically significant difference mean




















Related Learning Resources What is a meta-analysis? How to use a systematic review Blackboard Professor Double blind studies. GET-IT Jargon Buster Select a term treatment or recommendation is accepted by the people who are affected by it, or who are implementing it, in a study or in practice.

The likelihood that the actual effect will be substantially different from this is low. If your null hypothesis occurred by chance, then we do not reject retain the null hypothesis and conclude there is no difference. Because the result occurred by chance,it is not likely to happen in the real world.

However, if your null hypothesis did not occur by chance, then we reject the null hypothesis and conclude there is a difference. Because it did not occur by chance,it is likely to occur in the real world. This will in turn will affect the conclusions that you can draw from your research. A Type I error occurs when the null hypothesis is rejected when it should have been retained i. This means that the results are identified as significant when they actually occurred by chance.

Because they occurred by chance, it is unlikely to happen in the real world and so should have been identified as non-significant. A Type II error occurs when the null hypothesis is retained when it should have been rejected i. This means that the results are identified as non-significant when they actually did not occur by chance. Not occurring by chance suggests that it is likely to happen in the real world, and so should have been identified as significant.

Prior to any statistical analyses, it is important to determine what you will consider the definition of statistically significant to be. This is referred to as the alpha value, and represents the probability you are going to make a Type I error i. Alpha values are typically set at.

However, more conservative tests will use smaller alpha values such as. This means we can determine if something is actually working better than leaving things alone. Nutritionists do this all the time when testing new rations; pharmaceutical companies do this when testing new drugs or vaccines.

Veterinarians, and more likely research scientists, may use this to determine if a new type of surgery or expensive treatment is worthwhile.

While knowing how to perform these tests is important for researchers, from a practical standpoint remember two important factors: sampling error andprobability.

This is sampling error. Probability is just that, the likelihood of something actually happening. The higher the probability of a specific event or outcome, the more likely it is to happen.



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