The Central Limit Theorem (CLT) posits that the distribution of the sample mean for a substantial quantity of independent, identically distributed variables converges to a normal distribution, irrespective of the initial distribution's form. The applicability of the CLT significantly aids statistical analysis by enabling inferences about population parameters. A common guideline for the CLT's validity is a sample size of 30 or more, typically denoted as \(n \geq 30\), which facilitates the approximation of the sample mean distribution to normality.
Therefore, based on the given choices, the appropriate response is: greater than or equal to 30
| \(\text{Length (in mm)}\) | 70-80 | 80-90 | 90-100 | 100-110 | 110-120 | 120-130 | 130-140 |
|---|---|---|---|---|---|---|---|
| \(\text{Number of leaves}\) | 3 | 5 | 9 | 12 | 5 | 4 | 2 |