To sort in Excel by numerical size, you can select the column you want to sort by and then go to the "Data" tab on the ribbon. From there, click on the "Sort" button and choose "Smallest to Largest" or "Largest to Smallest" depending on how you want to sort the data. You can also use the "Sort" dialog box to customize the sorting options further, such as sorting by multiple columns or sorting by a custom list. Once you have selected your sorting options, click "OK" to apply the sorting to your data. **

To sort a numerical table in Excel, you can select the entire table or just the column you want to sort. Then, go to the "Data" tab on the Excel ribbon and click on the "Sort" button. Choose the column you want to sort by and select either ascending or descending order. Finally, click "OK" to apply the sorting to your numerical table. **

You can sort an array by numerical value in JavaScript using the `sort` method. You can use the `sort` method with a compare function to sort the array in ascending order. For example, you can use the following code to sort an array of numbers in ascending order: ```javascript let numbers = [3, 1, 5, 2, 4]; numbers.sort((a, b) => a - b); ``` This will sort the `numbers` array in ascending order. If you want to sort the array in descending order, you can use the following code: ```javascript numbers.sort((a, b) => b - a); ``` This will sort the `numbers` array in descending order. **

Among the three sorting algorithms, Insertion Sort is generally considered better in terms of performance. This is because Insertion Sort has an average time complexity of O(n^2), which is better than the average time complexity of O(n^2) for both Selection Sort and Bubble Sort. Additionally, Insertion Sort is more efficient when dealing with small datasets, as it has a relatively low overhead. Overall, Insertion Sort is often preferred over Selection Sort and Bubble Sort for its better average time complexity and efficiency with small datasets. **

Selection Sort has the advantage of being simple to implement and having a consistent time complexity of O(n^2) regardless of the input data. However, it is not efficient for large datasets due to its quadratic time complexity. On the other hand, Insertion Sort is efficient for small datasets and nearly sorted arrays, with a best-case time complexity of O(n). However, it also has a worst-case time complexity of O(n^2) and is not suitable for large datasets. **

The runtime of Insertion Sort in the worst case is O(n^2), where n is the number of elements in the array. This is because in the worst case scenario, each element needs to be compared and shifted to its correct position in the sorted array, resulting in a quadratic time complexity. Count Sort, on the other hand, has a linear runtime of O(n+k) in the worst case, where k is the range of the input values. This is because Count Sort creates a count array to store the frequency of each element, and then iterates through this count array to reconstruct the sorted array. **

Insertion sort works by iterating through the array from left to right, comparing each element to the elements on its left and inserting it into the correct position in the sorted portion of the array. It starts with the second element and compares it to the first element, then moves to the third element and compares it to the elements on its left until it finds its correct position. This process continues until all elements are in their correct positions, resulting in a sorted array. Insertion sort has a time complexity of O(n^2) in the worst-case scenario. **

Equations can be sorted by organizing them based on their variables and constants. One common method is to group equations with similar variables together. Another way is to arrange equations in a systematic order, such as alphabetically or by the power of the variables. Additionally, equations can be sorted based on their complexity or the type of mathematical operation involved, such as linear equations, quadratic equations, or exponential equations. **