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Bill_Wang_01的博客

The Well-Built City 优快云认证博客专家优快云认证企业博客

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Central Limit Theorem Overview
Lansonli: 学习了，博主原创不容易啊，过来支持一下~
(Reading) Sources of Power
盼盼编程: 干货满满，很详细，评论占个坑
What Will Happen When Adding a New Variable to a Multiple Linear Regression Model
不吃西红柿丶: 大佬的文章让我受益匪浅，如痴如醉，以后的日子还希望能够得到大佬的谆谆指指点点!
Types of Research & Two Sample t, Randomization, and Bootstrapping Tests
The Well-Built City: Here is the original question that triggered my freind's thought on the logic of the bootstrap test: "It is said that in the bootstrap test, the null hypothesis states that the means of education achievement level are equal for both groups. If we assume variances are equal, then the null hypothesis effectively says that values for both groups come from the same population So does this mean every time we do a bootstrap test, we should also assume variances are equal since this is what is needed to say values are from the same population? Because one of the statements of the null hypothesis in the lecture of the library bootstrap is that 'For a bootstrap test, the null hypothesis is that the values come from the same population'".
Types of Research & Two Sample t, Randomization, and Bootstrapping Tests
The Well-Built City: Just a side note on the bootstrap tests: a friend reminded me that to characterize a population, you have to make sure you get both the mean and the standard deviation (or variance). Thus, in bootstrap tests, you are always holding the mean and the variance constant because the process of generating a bootstrap distribution is the process of simulating the sampling distribution under the null hypothesis, in which your two groups of data come from exactly the same population. When it comes to whether to reject your null hypothesis, when you reject, it's typically because you see inconsistency on ONE OF the mean of variance from that of the bootstrap distribution; when you fail to reject, you fail to gain enough evidence about the inconsistency on BOTH the mean and the variance from those of the boostrap distribution.

Computer Programming Misc

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Bill_Wang_01的博客

Computer Programming Misc

作者: The Well-Built City

(Counting & Probability) Fisher-Yates Shuffling & Implementation in Java

(JAVA) Miscellaneous Topics