T-Statistic test on Crab Shell Data

Hello,

In today’s blog, I wanted to describe about T-Test on Crab shell example which was discussed in last week’s class.

If there is no difference between the means of pre-molt and post-molt data, then it is called the Null Hypothesis (H0). Contrary to that, if there is no difference in means for pre-molt and post-molt data, then it is called the Alternative Hypothesis (H1).

Later, we must calculate the t- t-statistic and degrees of freedom (df) using the formulas below.

  • t-statistic =Standard error of the difference(mean)/Difference in sample statistics
  • df=n1+n2−2

Where, n1 = Sample size of the first group.

n2​ = Sample size of the second group.

 

Using these two (t- statistic and degrees of freedom (df)), we must find the p-value.

 

As per last Wednesday’s class example regarding crab shells, we must analyze the data for pre-molt and post-molt crab shell sizes for differences. If we assume that there is no difference between the crab shell size pre-molt and post-molt data, which is a Null Hypothesis (H0). Contrary, if we assume that there is a difference in crab shell size for pre-molt and post-molt data, which is the Alternative Hypothesis (H1).

Here, let’s consider Alternative Hypothesis (H1) and t-test the data.

 

As mentioned above, we can get the value using the t-statistic formula, and then proceed to find the p-value. If the p-value is less, then it means that there’s a real and meaningful difference between the data.

 

Based on the calculated p-value, if the data is less than 0.05, then we can come to the conclusion that there is no enough evidence to finalize that there is a difference between the two data.

 

Thank You!

 

 

 

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