时间:2021-01-19 14:50:27 作者: papercrazy阅读数:186 次



Why analyze data in research?


Researchers rely heavily on data as they have a story to tell or problems to solve. It starts with a question, and data is nothing but an answer to that question. But, what if there is no question to ask? Well! It is possible to explore data even without a problem – we call it ‘Data Mining’ which often reveal some interesting patterns within the data that are worth exploring.


Irrelevant to the type of data, researchers explore, their mission, and audiences’ vision guide them to find the patterns to shape the story they want to tell. One of the essential things expected from researchers while analyzing data is to stay open and remain unbiased towards unexpected patterns, expressions, and results. Remember, sometimes, data analysis tells the most unforeseen yet exciting stories that were not expected at the time of initiating data analysis. Therefore, rely on the data you have at hand and enjoy the journey of exploratory research.

1.2 研究中的数据类型

Types of data in research


Every kind of data has a rare quality of describing things after assigning a specific value to it. For analysis, you need to organize these values, processed and presented in a given context, to make it useful. Data can be in different forms; here are the primary data types.

定性数据类: 当呈现的数据有文字和描述时,那么我们称之为定性数据。虽然可以观察这些数据,但是在研究中分析——特别是为了比较——这类数据时会比较主观,比较困难。例子: 品质数据(Quality data)代表所有描述味道、体验、质地或被认为是质量数据的观点的一切事物。例如,这种类型的数据通常是通过焦点小组(focus groups)、个人访谈或在调查中使用开放式问题收集的。

Qualitative data: When the data presented has words and descriptions, then we call it qualitative data. Although you can observe this data, it is subjective and harder to analyze data in research, especially for comparison. Example: Quality data represents everything describing taste, experience, texture, or an opinion that is considered quality data. This type of data is usually collected through focus groups, personal interviews, or using open-ended questions in surveys.

定量数据类: 任何以数字表示的数据都称为定量数据。这种类型的数据可以分为类别数字(categories)、分组数字(grouped)、测量数字(measured)、计算数字(calculated)或排序数字(ranked.)。例如: 年龄、等级、成本、长度、体重、分数等等一切都属于这类数据。可以用图形格式、图表或统计分析方法来显示这些定量数据。(例如,)在调查研究中,OMS(Outcomes Measurement Systems——结果测量系统)问卷是收集数字数据的一个重要来源。

Quantitative data: Any data expressed in numbers of numerical figures are called quantitative data. This type of data can be distinguished into categories, grouped, measured, calculated, or ranked. Example: questions such as age, rank, cost, length, weight, scores, etc. everything comes under this type of data. You can present such data in graphical format, charts, or apply statistical analysis methods to this data. The (Outcomes Measurement Systems) OMS questionnaires in surveys are a significant source of collecting numeric data.

        分类数据类(Categorical data): 它是以分组呈现的数据。但是,分类数据中包含的条目不能属于一个以上的组。举例来说:一个人对一项调查的回应是说出他的生活方式、婚姻状况、吸烟习惯或饮酒习惯,这属于分类数据。卡方检验是分析这些数据的标准方法。Categorical data: It is data presented in groups. However, an item included in the categorical data cannot belong to more than one group. Example: A person responding to a survey by telling his living style, marital status, smoking habit, or drinking habit comes under the categorical data. A chi-square test is a standard method used to analyze this data.


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