Statistical tests are just a way of working out the probability of obtaining the observed or even more extreme variations among samples or between expected and observed value if a specific hypothesis usually the null of no difference is true. Once the probability is known the experimenter can make a decision about the variation, using criteria that are understood and used uniformly (Klimesch, 2006, p 209; Mckillup, 2005).
Chi Square Test:
A statistical test to evaluate variations is referred to as chi square test. The chi square test measures the variations between a statistically produced expected results and an actual outcome to view if there is a statistically essential variations between them i.e. to view if the frequencies observed are essential and it is also the measure of goodness of fit between actual and an expected outcome or collection of outcomes. The expected result is based on statistical process and it denotes the statistical significance notion which is concerned on the probability notions. The formula for chi square test is:
The basic need of any chi square test is that they compare how well an observed breakdown of people over different categories fits some expected breakdown. A chi square test is described as comparing an observed frequency distribution to an expected frequency and then viewing whether that number denotes a greater mismatch that they would expect by chance (Cohen, Manion and Morrison, 2007, p 525; Aron, Aron and Coups, 2007).
统计测试只是工作的概率得到观察甚至更极端的变化之间的样品或预期值与实测值之间，如果一个特定的假设通常是无差异的零假设为真。一旦概率是已知的实验者可以决定使用的变化，是理解和使用统一的标准（klimesch，2006，P 209；mckillup，2005）。
卡方检验：
评估变化的统计测试被称为卡方检验。卡方检验措施的统计产生预期的结果和查看是否有统计学基本变量之间即认为如果观察到的频率是必要的，也是符合实际和预期的结果或成果的集合之间的善良措施的实际结果之间的差异。预期的结果是基于统计过程，它指的是统计意义上的概念，是对概率概念。卡方检验的公式：
任何卡方检验的基本需要，他们比较好的观察到的故障在不同类别的人适合一些预期故障。卡方测试的描述比较观察到的频率分布的预期频率，然后查看这个数字是否表示一个更大的不匹配，他们预期的机会（科恩，马尼恩和墨里森，2007，P 525；阿龙，阿龙和政变，2007）。
