假设是什么?假设(复数假设)是对观察的一种建议解释。定义取决于主题。例如,在科学中,假设是科学方法的一部分。这是一个由实验来检验的预测或解释。观察和实验可能推翻科学假设,但永远无法完全证明一个假设。但是,在逻辑学的研究中,假设是一个if-then命题,通常写成“if X,then Y”。在通常用法中,假设只是一个提议的解释或预测,它可以被测试,也可以不被测试。大多数科学假设都是以if-then格式提出的,因为很容易设计一个实验来检验自变量与因变量之间是否存在因果关系。这个假设被写为对实验结果的预测。零假设与替代. 从统计上来说,显示两个变量之间没有关系比支持它们的连接更容易。因此,科学家经常提出零假设。零假设假设假设改变自变量对因变量没有影响。相比之下,备选假设表明改变自变量会对因变量产生影响。设计一个实验来检验这个假设可能比较棘手,因为有很多方法可以陈述一个可选的假设。例如,考虑一下睡个好觉和取得好成绩之间的可能关系。零假设可以这样说:“睡眠时间与学生成绩无关”或者“睡眠时间与学生成绩无关”。检验这一假设的一个实验可能涉及收集数据,记录每个学生的平均睡眠时间以及gr阿德斯如果8小时睡眠的学生通常比4小时睡眠或10小时睡眠的学生表现更好,这个假设可能会被拒绝。但是另一种假设更难提出和检验。最普遍的说法是:“学生睡眠的量会影响他们的成绩。”这个假设也可以被描述为“如果你多睡,你的成绩就会提高”或者“睡眠9小时的学生比睡眠多或少的学生成绩更好。”您可以收集相同的数据,但是统计分析不太可能给出高置信限。通常,科学家从零假设开始。由此,有可能提出并检验替代假设,以缩小变量之间的关系。

澳大利亚RMIT统计学Essay代写: 统计假设

What is the hypothesis? Hypothesis (plural hypothesis) is a suggested explanation of observation. Definition depends on the subject. For example, in science, hypothesis is part of the scientific method. This is a prediction or explanation tested by experiments. Observations and experiments may overturn scientific assumptions, but they can never fully prove a hypothesis. However, in the study of logic, the hypothesis is an if-then proposition, usually written as “if X, then Y”. In common usage, the assumption is only a proposed explanation or prediction, which can be tested or not. Most scientific hypotheses are presented in if-then format, because it is easy to design an experiment to test whether there is a causal relationship between independent variables and dependent variables. This hypothesis is written as a prediction of experimental results. Zero Hypothesis and Substitution. Statistically, it is easier to show that there is no relationship between two variables than to support their connection. Therefore, scientists often put forward zero hypothesis. The null hypothesis assumes that the change of independent variables has no effect on dependent variables. In contrast, alternative assumptions indicate that changing an independent variable has an impact on a dependent variable. Designing an experiment to test this hypothesis can be tricky because there are many ways to state an optional hypothesis. Consider, for example, the possible relationship between a good night’s sleep and good grades. Zero hypothesis can be used to say, “Sleep time has nothing to do with student performance” or “Sleep time has nothing to do with student performance”. An experiment to test this hypothesis may involve collecting data, recording the average sleep time of each student, and Gr Adams’hypothesis that students who sleep eight hours usually perform better than those who sleep four hours or ten hours may be rejected. But another hypothesis is more difficult to put forward and test. The most common saying is, “The amount of sleep students get affects their grades.” This hypothesis can also be described as “If you sleep more, your grades will improve” or “Students who sleep nine hours do better than those who sleep more or less.” You can collect the same data, but statistical analysis is unlikely to give a high confidence limit. Usually, scientists start with zero hypothesis. Therefore, it is possible to propose and test alternative hypotheses in order to narrow the relationship between variables.

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