> For the complete documentation index, see [llms.txt](https://jaywin.gitbook.io/leetcode/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://jaywin.gitbook.io/leetcode/solutions/1093-statistics-from-a-large-sample.md). # 1093. Statistics from a Large Sample ## Description You are given a large sample of integers in the range `[0, 255]`. Since the sample is so large, it is represented by an array `count` where `count[k]` is the **number of times** that `k` appears in the sample. Calculate the following statistics: * `minimum`: The minimum element in the sample. * `maximum`: The maximum element in the sample. * `mean`: The average of the sample, calculated as the total sum of all elements divided by the total number of elements. * `median`: * If the sample has an odd number of elements, then the `median` is the middle element once the sample is sorted. * If the sample has an even number of elements, then the `median` is the average of the two middle elements once the sample is sorted. * `mode`: The number that appears the most in the sample. It is guaranteed to be **unique**. Return *the statistics of the sample as an array of floating-point numbers* `[minimum, maximum, mean, median, mode]`*. Answers within* `10-5` *of the actual answer will be accepted.* **Example 1:** ``` **Input:** count = [0,1,3,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] **Output:** [1.00000,3.00000,2.37500,2.50000,3.00000] **Explanation:** The sample represented by count is [1,2,2,2,3,3,3,3]. The minimum and maximum are 1 and 3 respectively. The mean is (1+2+2+2+3+3+3+3) / 8 = 19 / 8 = 2.375. Since the size of the sample is even, the median is the average of the two middle elements 2 and 3, which is 2.5. The mode is 3 as it appears the most in the sample. ``` **Example 2:** ``` **Input:** count = [0,4,3,2,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] **Output:** [1.00000,4.00000,2.18182,2.00000,1.00000] **Explanation:** The sample represented by count is [1,1,1,1,2,2,2,3,3,4,4]. The minimum and maximum are 1 and 4 respectively. The mean is (1+1+1+1+2+2+2+3+3+4+4) / 11 = 24 / 11 = 2.18181818... (for display purposes, the output shows the rounded number 2.18182). Since the size of the sample is odd, the median is the middle element 2. The mode is 1 as it appears the most in the sample. ``` **Constraints:** * `count.length == 256` * `0 <= count[i] <= 109` * `1 <= sum(count) <= 109` * The mode of the sample that `count` represents is **unique**. ## ac ```java ```