Limit theorems in mathematics and statistics are fundamental results that describe the behavior of certain statistics or functions as the sample size approaches infinity. These theorems provide insights into the properties of random variables and their distributions, helping researchers make predictions and draw conclusions about a population based on a sample. Common limit theorems include the Central Limit Theorem, which states that the sum or average of a large number of independent and identically distributed random variables will have an approximately normal distribution, regardless of the original distribution of the variables. Another important limit theorem is the Law of Large Numbers, which describes how the sample mean converges to the population mean as the sample size increases. Overall, limit theorems play a crucial role in statistical inference, hypothesis testing, and decision-making in a wide range of fields, including economics, biology, and engineering. They provide a solid theoretical foundation for statistical analysis and help ensure the validity and reliability of research findings.