A t-test is a statistical hypothesis test used to determine if there is a significant difference between the means of two groups. It is commonly used when you have a small sample size and want to infer if the difference between the groups is likely due to chance.
There are two types:
- Independent Samples T-Test: Compares means of two separate groups.
- Paired Samples T-Test: Compares means of paired data.
- Null Hypothesis (): No significant difference.
- Alternative Hypothesis (): Significant difference.
The test calculates a statistic (t) based on sample means and standard deviations. If the p-value is less than a chosen significance level, we reject the null hypothesis, implying a significant difference. Check assumptions like normality and equal variances.
The Crab Molt model looks at measurements of crabs before and after molting. Our main goal was to predict the crab size before molting based on their post-molt measurements. Using a simple model, we got an impressive R-squared value of 0.98, indicating the model predicts well based on the data. And also analyzed the pre-molt and post-molt data. They were similar in distribution, with a small mean difference of about 14.7 units.