Is the Definition of Unpaired t-test in My Book Correct?

In summary, an unpaired t-test is used to compare data from two groups or samples that are not related or paired in any way. The definition mentioned in the book is correct and the example given by Wikipedia does not contradict it. The groups in the example may be equal in size, but they are still unpaired measurements. Additionally, the example in Wikipedia does not specify the population from which the groups are selected. The book's definition is accurate and an unpaired t-test would be used in situations where the groups are not related or paired in any way.
  • #1
Tyto alba
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I was reading a book that said:

Unpaired t-test is applied to unpaired data of independent observations made on individuals of two different groups (of a single sample) or samples drawn from two populations.

Now what wiki says is that they are not unpaired the e.g. given is one with 50 and 50 individuals. Besides they do not mention the groups coming from a single sample. (wiki)

Is the definition mentioned by my book correct?
 
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  • #2
SanjuktaGhosh said:
Now what wiki says is that they are not unpaired the e.g. given is one with 50 and 50 individuals.
The wikipedia article you linked does not say that the measurements in that example are "not unpaired". It says the measurements are unpaired.

The fact that there are two groups of 50 in the example, does not imply the measurements are paired. It is possible to have two groups of unpaired measurements that are equal in size.

Besides they do not mention the groups coming from a single sample. (wiki)
Did you mean to say "from a single population"? You are correct that example in the wikipedia does not specify the population from which the 100 students are selected.

Is the definition mentioned by my book correct?

The definition in your book defines an "unpaired t-test" and it is a correct definition. You did not quote a definition that shows how your book defines the concept of "unpaired".

Consider an example where we selecting 100 students at random from student population of , say, the students enrolled at Cal Tech. If we do a study where 50 of the students eat a normal diet and 50 eat a special diet, then to judge whether weight gain or loss after 6 months is affected by the special diet, we would use an unpaired t-test. If student Zed Smith is in the group that eats the normal diet, we have no reason to pair his results with those of any other student - unless he happened to have a twin brother!

However, suppose each of the 100 students eats a normal diet for 6 months and then eats a special diet for 6 months. Then to judge whether weight gain or loss after 6 months is affected by the special diet, we could use a paired t-test. In this situation we have data like: Zed Smith's weight after 6 months of normal diet vs Zed Smith's weight after 6 months on the special diet.
 

Related to Is the Definition of Unpaired t-test in My Book Correct?

1. What is an unpaired t-test?

An unpaired t-test is a statistical test used to determine whether there is a significant difference between the means of two independent groups. It is commonly used in scientific research to compare the effectiveness of two treatments, the performance of two groups, or the relationship between two variables.

2. How is an unpaired t-test different from a paired t-test?

An unpaired t-test compares the means of two independent groups, while a paired t-test compares the means of two related groups. In a paired t-test, the same individuals are measured twice, such as before and after a treatment, whereas in an unpaired t-test, the individuals in each group are completely different.

3. What are the assumptions of an unpaired t-test?

The assumptions of an unpaired t-test include: the data is normally distributed, the variances of the two groups are equal, and the observations within each group are independent. Violation of these assumptions can affect the accuracy of the results.

4. When should an unpaired t-test be used?

An unpaired t-test should be used when comparing the means of two independent groups and the data is normally distributed. It is often used in scientific research to determine whether a treatment or intervention has a significant effect on a particular outcome.

5. How is the significance level determined in an unpaired t-test?

The significance level, also known as alpha, is usually set at 0.05 or 0.01 in an unpaired t-test. This value represents the probability of rejecting the null hypothesis when it is actually true. It is important to select an appropriate significance level to minimize the chances of making a type I error (incorrectly rejecting the null hypothesis).

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