Reject Value (Stats) ( )

In summary, it is important to consider the context and sample size when deciding between using a t-test or coeff of variance for rejecting a value in an experiment.
  • #1
icystrike
445
1
Reject Value (Stats) (URGENT)

Homework Statement



Hi PF!

I've gotten a few values from an experiment for (QA):

7233, 8064, 8202, 8277

The instruction manual told keep the coeff of variance within 2.00% and that force for to reject the value 7233.

But I'm wondering if i can use t test to see if i should reject the value?

By using t-test,

t-value
[tex]= \frac{7944-7233}{241.069}[/tex]
=2.94935
<3.182 (0.05 level of significance)

Therefore i can retain the value.

Precisely which is better?

Homework Equations


The Attempt at a Solution

 
Last edited:
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  • #2
It depends on the context of your experiment and what you are trying to accomplish. Generally, if you have a large sample size, then using a t-test would provide a more reliable result. However, if you only have a small sample size, then the coeff of variance may be the better option since it is more conservative and less likely to produce a false positive. In this case, since the sample size is relatively small, the coeff of variance may be the better option.
 

What is reject value in statistics?

Reject value, also known as critical value, is a specific value used to determine whether to reject or fail to reject the null hypothesis in a statistical test. It is based on the level of significance chosen for the test.

How is reject value calculated?

Reject value is calculated using a statistical table or calculator. The calculation takes into account the degrees of freedom, level of significance, and type of statistical test being performed.

Why is reject value important in statistics?

Reject value is important because it helps determine the outcome of a statistical test. If the calculated test statistic is greater than or equal to the reject value, the null hypothesis is rejected. If the test statistic is less than the reject value, the null hypothesis is not rejected.

What is the relationship between reject value and p-value?

Reject value and p-value are both used in statistical hypothesis testing. The reject value is compared to the test statistic to determine whether to reject the null hypothesis. The p-value, on the other hand, is the probability of obtaining a test statistic at least as extreme as the one observed if the null hypothesis is true. If the p-value is less than the chosen level of significance, the null hypothesis is rejected.

How does the level of significance affect the reject value?

The level of significance chosen for a statistical test directly affects the reject value. A higher level of significance will result in a lower reject value, making it easier to reject the null hypothesis. Conversely, a lower level of significance will result in a higher reject value, making it more difficult to reject the null hypothesis.

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