In today’s class , I have acquired knowledge about the linear regression model that fit to data in which both variables are not normally distributed, have high skewness, high variance, and high kurtosis. But this can be a challenging scenario for linear regression, because it assumes certain characteristics of the data that may not hold true in this case. When we are working with such data, it’s important to consider alternative modeling approaches that can handle non-normality, skewness, and high kurtosis, such as robust regression methods or non-linear models. The best way to explain this model is using CRAB Method.

For eg. Pre-molt describes the shell’s size prior to molting, while Post-molt refers to the dimensions of a crab’s shell after molting.

Today’s data model was proposed to create a linear model to predict the size of a crab’s shell before molting based on the size of the shell after molting and we tried to understand if the difference between both the states means statistical significance or not and came to the conclusion that by standard statistical inference across a lot of cases, the p value in this case was less than 0.05 with makes us reject the null hypothesis that there is no real difference.

We also got to know about the t-test analysis, which is a a statistical hypothesis test used to determine if there is a significant difference between the means of two groups or populations. For eg. Imagine you have two groups, like group A and group B. Group A, who were taught using Method 1, and Group B, who were taught using Method 2. You want to determine if there is a significant difference in the average test scores between the two groups. The t-test wishes it knew the  scores of a special secret ingredient (lets call it “scaling term”) in the math, but it doesn’t. So, it has to guess it from the numbers. If it guesses right (under some specific conditions), it can use its rulebook to say if the groups are different or not.

In summary, a linear model using CRAB Molt in statistical analysis is a tool used to study and quantify the molting behavior of crabs, with the goal of understanding the factors that influence this behavior. These models can help researchers and practitioners make informed decisions related to crab populations and management.