1201C C. Maximum Median

给定一个奇数长度的整数数组,允许最多k次操作,每次选择一个元素加1,目标是使数组排序后的中位数最大化。通过先排序数组,然后从中位数开始使用二分搜索确定最大可能的增加次数,从而找到最大中位数。

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						C. Maximum Median
						time limit per test2 seconds
						memory limit per test256 megabytes
						inputstandard input
						outputstandard output

You are given an array a of n integers, where n is odd. You can make the following operation with it:

Choose one of the elements of the array (for example ai) and increase it by 1 (that is, replace it with ai+1).
You want to make the median of the array the largest possible using at most k operations.

The median of the odd-sized array is the middle element after the array is sorted in non-decreasing order. For example, the median of the array [1,5,2,3,5] is 3.

Input
The first line contains two integers n and k (1≤n≤2⋅105, n is odd, 1≤k≤109) — the number of elements in the array and the largest number of operations you can make.

The second line contains n integers a1,a2,…,an (1≤ai≤109).

Output
Print a single integer — the maximum possible median

Make sure that we grade your HW based solely on your R code script. If we don’t see the correct results when we run your code, you will get 0 point for those questions. 1. Create a R function to show the central limit theorem. This function should have the following properties: - In the argument of the function, you have an option to consider poisson, exponential, uniform, normal distributions as the population distribution. - Depending on the choice of the population distribution in part (1), the function will receive extra argument(s) for the parameters of the distribution. For example, if a normal distri- bution is chosen, the mean and SD are needed in the function argument. Note that each distribution has a different parameter setting. - If the distribution is not selected from (“Normal”, “Poisson”, “Uniform”, “Exponential”), the function needs to print the following error message: check the distributional setting: consider ("Normal", "Poisson", "Uniform", "Exponential") and stop. - The function should give the summary statistics (minimum, 1st quartile, median, mean, 3rd quartile, maximum) of 1, 000 sample mean values for given n values (n = 10, 50, 100, 500). - The result should have the following statement at the beginning, for example, if a normal distribution with mean 1 and SD 0.5 was chosen: ‘‘For the Normal distribution, the central limit theorem is tested’’ where the term “Normal” is automatically inserted in the statement based on the argument. And the output should have the following form: For the Normal distribution, the central limit theorem is tested When n=10: Min. 1st Qu. Median Mean 3rd Qu. Max. 0.5187 0.8930 1.0016 0.9993 1.1019 1.4532 When n=50: Min. 1st Qu. Median Mean 3rd Qu. Max. 0.7964 0.9508 1.0010 0.9997 1.0493 1.2309 1 When n=100: Min. 1st Qu. Median Mean 3rd Qu. Max. 0.8534 0.9679 0.9972 0.9992 1.0325 1.1711 When n=500: Min. 1st Qu. Median Mean 3rd Qu. Max. 0.9258 0.9836 1.0006 0.9997 1.0154 1.0678 I Using your own function, test the N(−1,0.52) and the Unif(−3,6) case.
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06-05
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