形成理论来解释或描述等关系,事件或行为。观察和理论给出了一个声明由一个相互关联的、逻辑的思想和模型。结构可能持有或支持理论研究中被称为“理论框架”。它解释了为什么研究存在的问题。因此,理论是一个理论框架,扮演作为起点进行研究。理论框架是非常重要的研究,因为它可以帮助研究人员清楚地表明研究中使用的变量,它可以帮助形成数据分析的一般框架。有两种类型的变量,自变量和因变量。
采样小组或人口的一个子集(塞卡让2003)。有两种类型的non-probability取样和概率抽样的抽样。概率抽样是完全基于样本的选择的机会。研究者没有控制的选择或non-selection样本。概率抽样是命名为随机抽样。相比之下,non-probability抽样样本的选择不是取决于机会。选择的样本研究。Non-probability抽样又称随机抽样。另一个术语是人口。人口是一群人,有一个或多个共同特征可以收集和分析数据。
为了执行权力分析,Gpower统计项目将用于这个研究(Erdfelder,福尔&毕希纳,1996)。这个Gpower用于获取高精度中最常见的统计检验行为研究t等野生和Chi-tests。为例子,它可以用于独立样本,相关性,多重相关和回归以及应急表。程序基本上计算功率值,样本大小和α和β的值。这个程序也可以显示任意两个相关变量之间的关系图形和计算效果的措施从基本参数定义备择假设。
澳洲心理学论文代写:解释或描述
Theories are formed to explain or describe something such as relationships, events or behavior. A theory gives a statement on observations and consists of an interrelated, logical set of ideas and models. A structure that could hold or support a theory in a study is called the theoretical framework. It explains why the problem from the study is present. Thus, the theoretical framework is a theory that plays the role as a starting point for conducting a research. Theoretical framework is very important in a research as it helps the researcher to clearly show the variables used in the study and it can help to form the general framework for data analysis. There are two types of variables which are independent variable and dependent variable.
Sampling is a subgroup or a subset of a population (Sekaran, 2003). There are two types of sampling which are non-probability sampling and probability sampling. Probability sampling is the selection of sample based entirely on chance. The researcher has no control on the selection or non-selection of the sample. Probability sampling is named as random sampling. In contrast, non-probability sampling is the selection of sample which is not depends on chance. The samples are selected by the researcher. Non-probability sampling is also known to be non-random sampling. Another term is population. Population is a group of people that have one or more common characteristics which data can be collected and analyzed.
In order to perform power analysis, Gpower statistical program will be used in this research (Erdfelder, Faul, & Buchner, 1996). This Gpower is used to obtain high-precision for the most common statistical tests in behavioural research such as t-tests, F-tests and Chi-tests. For examples, it could be used for independent samples, correlations, multiple correlation and regression and also contingency tables. The program basically computes the power values, sample sizes and alpha and beta values. This program could also show the relation between any two relevant variables graphically and calculate the effect size measures from basic parameters defining the alternative hypothesis.
