When we are faced with a group of numbers and need to arrange them in order from small to large, we can use a simple comparative logic to achieve this goal. This logic is based on the principle of size comparison in mathematics, that is, if the first number is less than the second number, then the first number should be before the second number; Conversely, if the first number is greater than the second number, the first number should be after the second number.

Suppose we have the following numbers: 5, 3, 9, 1, 7. In order to sort these numbers, we can choose two numbers to compare, such as 5 and 3. Since 5 is greater than 3, we should put 3 before 5.

Next, we can compare 3 and 9. Obviously, 3 is less than 9, so we should put 3 before 9. Continuing this comparison process, we can compare 3 with 1 and get that 3 is greater than 1, so we put 1 before 3. Finally, we compare 3 with 7 and get that 3 is less than 7, so we put 7 after 3.

By comparing and exchanging the positions of numbers step by step in this way, we can finally get the order of numbers from small to large: 1, 3, 5, 7, 9. This sorting method is simple but effective. It can help us quickly arrange a group of numbers in the order from small to large, thus facilitating us to carry out various mathematical or statistical analysis.

Sorting method:

1, bubble sorting: bubble sorting is a simple sorting algorithm, which repeatedly traverses the sequence to be sorted, compares two elements at a time, and exchanges them if their order is wrong. This process continues until there are no more elements to exchange, which means that the sequence has been sorted. The time complexity of bubble sorting is O (n 2), so the sorting of large-scale data will be slow.

2. Insertion sorting: Insertion sorting is a simple and intuitive sorting algorithm. Its working principle is to scan the unordered data from back to front in the sorted sequence, find the corresponding position and insert it. Insertion sorting usually adopts in-place sorting in implementation, that is, only O( 1) extra space is needed. The time complexity of insert sorting is O (n 2), but for partially ordered data, the efficiency of insert sorting can be higher.

3. Quick sorting: Quick sorting is an efficient sorting algorithm, which uses the idea of divide-and-conquer method to divide an array into two subarrays and sort the two parts respectively. The time complexity of quick sorting is O(nlogn), and the performance is very good on average, but for some special cases, such as ordered data, the efficiency of quick sorting will be reduced to O (N 2).