tp钱包官网下载安装|liker

李克特量表_百度百科

表_百度百科 网页新闻贴吧知道网盘图片视频地图文库资讯采购百科百度首页登录注册进入词条全站搜索帮助首页秒懂百科特色百科知识专题加入百科百科团队权威合作下载百科APP个人中心李克特量表播报讨论上传视频评分加总式量表最常用的一种量表收藏查看我的收藏0有用+10本词条由“科普中国”科学百科词条编写与应用工作项目 审核 。李克特量表(Likert scale)是属评分加总式量表最常用的一种，属同一构念的这些项目是用加总方式来计分，单独或个别项目是无意义的。它是由美国社会心理学家李克特于1932年在原有的总加量表基础上改进而成的。该量表由一组陈述组成，每一陈述有非常同意、同意、不一定、不同意、非常不同意五种回答，分别记为5、4、3、2、1，每个被调查者的态度总分就是他对各道题的回答所得分数的加总，这一总分可说明他的态度强弱或他在这一量表上的不同状态。中文名李克特量表外文名Likert scale应用学科心理学应用范围实验心理学目录1简介2五点选项3基本步骤4计分分析5测量尺度6应用7优点8缺点9关键字10读音简介播报编辑李克特量表在心理学上的读法相似于 'lick-urt' 与 'lie-kurt'之间（虽然前者的读法是取自于建立此量表的人的姓氏），是一种心理反应量表，常在问卷（英语：questionnaire）中使用，而且是目前调查研究（survey research）中使用最广泛的量表。当受测者回答此类问卷的项目时，他们具体的指出自己对该项陈述的认同程度。此量表是由Rensis Likert所建立。李克特量表形式上与沙氏通量表相似，都要求受测者对一组与测量主题有关陈述语句发表自己的看法。它们的区别是，沙氏通量表只要求受测者选出他所同意的陈述语句，而李克特量表要求受测者对每一个与态度有关的陈述语句表明他同意或不同意的程度。另外，沙氏通量表中的一组有关态度的语句按有利和不利的程度都有一个确定的分值，而李克特量表仅仅需要对态度语句划分是有利还是不利。五点选项播报编辑理清李克特量表(Likert Scale)和李克特选项(Likert item)的区别是重要的。李克特量表是使用各种李克特选项的总称。因为李克特选项，常常是一个视觉化量表（例如，在一个题目上的一条水平线，让受测者以画圈或点选的方式回答），这些选项有时也称为量表。但是，这容易造成混淆，因此，比较好的做法是，李克特选项专指一个单独的选项。一个李克特选项是一个陈述。受测者被要求指出他或她们对该题目所陈述的认同程度，或任何形式的主观或客观评价。通常使用五个回应等级，但许多计量心理学者（psychometrician）主张使用7或9个等级。一项最近的实证研究指出，5等级、7等级和10等级选项的数据，在简单的资料转换后，其平均数、变异数、偏态和峰度都很相似。例如李克特的五等选项的：1.强烈反对 2.不同意 3.既不同意也不反对 4.同意 5.坚决同意 李克特量表是有两个极端的量化方法，衡量一个陈述的正面或负面回答。当中间选项“无意见”不能用时，有时会使用四等量表──一个强迫选择（英语：forced choice）的方法。李克特量表也许会受到几种因素干扰而失真。受测者也许会回避勾选极端的选项（趋中倾向的偏差）；对陈述的习惯性认同（惯性偏差）；或试着揣摩并迎合他们自己或他们的组织希望的结果（社会赞许偏差）。基本步骤播报编辑（1）收集大量（50～100）与测量的概念相关的陈述语句。（2）有研究人员根据测量的概念将每个测量的项目划分为“有利”或“不利”两类，一般测量的项目中有利的或不利的项目都应有一定的数量。（3）选择部分受测者对全部项目进行预先测试，要求受测者指出每个项目是有利的或不利的，并在下面的方向-强度描述语中进行选择，一般采用所谓“五点”量表：a．非常同意b．同意c．无所谓（不确定）d．不同意e．非常不同意（4）对每个回答给一个分数，如从非常同意到非常不同意的有利项目分别为5、4、3、2、1分，对不利项目的分数就为1、2、3、4、5。（5）根据受测者的各个项目的分数计算代数和，得到个人态度总得分，并依据总分多少将受测者划分为高分组和低分组。（6）选出若干条在高分组和低分组之间有较大区分能力的项目，构成一个李克特量表。如可以计算每个项目在高分组和低分组中的平均得分，选择那些在高分组平均得分较高并且在低分组平均得分较低的项目。计分分析播报编辑在问卷完成后，每一个选项也许会被个别的分析，或某些成组的选项被加总并建立成一个量表。因此，李克特量表常常被称为累加量表（summative scale）。至于个别的李克特选项可视为区间数据，或只应该被视为顺序数据，仍然是具争议性的议题。许多人将这样的项目视为顺序尺度的数据，因为特别是只有使用5个等级时，无法让受测者察觉到这些相邻的项目，其间隔是等距的。在另一方面，通常（正如上面的例子）其response levels的措辞清楚的暗示出中间类别的response levels的对称性；在最低限度，这样一个项目，将变成介于顺序和区间尺度之间 ；只将它视为顺序数据将遗失一些信息。此外，如果该项目附带视觉近似评价标尺（visual analog scale），其回答程度的间隔则明确表示，其作为区间数据的论点是更加坚固。当被视为顺序数据，李克特数据可以整理成长条图，以中位数或众数（但不是平均数）表现集中趋势，以四分位距表现分散程度（但不是标准差），或用非参数检验分析，如 Chi-square test,Mann-Whitney test，威尔克科逊检验（英语：Wilcoxon signed-rank test），或Kruskal-Wallis test。几个李克特题目的数据也许会被加总，若所有题目使用相同的李克特量表，则该量表可有效的接近区间尺度，此时可以将之视为区间数据测量潜在变项。如果加总结果满足这些假设，可以用参数统计（parametric statistical）如变异数分析作测试。但只有当项目在5个以上才可使用。从李克特量表获得的数据，有时会合并所有的同意和不同意的回复为"接受"和"不接受"两个类别，此时会成为名目尺度。Chi-Square，Cochran Q，或McNemar-Test都是在资料做这些转换后常用的统计方法。Consensus based assessment (CBA)可以用来为没有普遍接受的标准或客观标准的领域产生一个客观的标准。CBA可用于完善或甚至验证普遍接受的标准 [1]。测量尺度播报编辑五个答题选项类别常常被认为是区间测量变项尺度（英语：level of measurement）。但是，如果尺度各点的区间与metric sense中的实证观察结果一致时，这只能算是一种个案。事实上，也有可能出现顺序尺度的情况。例如，在一个A，B，C 集合中，可能出现李克特量表循环关系（circular relation）如 A>B，B>C和 C>A。这违反顺序尺度的递移性公理（axiom of transitivity）。应用播报编辑李克特量表的构作比较简单而且易于操作，因此在市场营销研究实务中应用非常广泛。在实地调查时，研究者通常给受测者一个“回答范围”卡，请他从中挑选一个答案。需要指出的是，目前在商业调查中很少按照上面给出的步骤来制作李克特量表，通常由客户项目经理和研究人员共同研究确定。优点播报编辑（1）容易设计；（2）使用范围比其他量表要广，可以用来测量其他一些量表所不能测量的某些多维度的复杂概念或态度。（3）通常情况下，李克特量表比同样长度的量表具有更高的信度。（4）利克特量表的五种答案形式使回答者能够很方便的标出自己的位置。缺点播报编辑相同的态度得分者具有十分不同的态度形态。因为利克特量表是一个项目总加的分代表一个人的赞成程度，它可大致上区分个体间谁的态度高，谁的低，但无法进一步描述他们的态度结构差异。关键字播报编辑华语：李克特量表,利克特量表,李克特5点量表,李克特式量表,李氏累加量表,里克特量表,李克特5级量表,赖克梯量表英语：Likert scale, Likert summated rating scale读音播报编辑建立此量表的Rensis Likert对他自己名字'lick-urt'的读法为一个短"i"的音。 已经有人主张Likert的名字"是在[该]领域中错误的读音。" 虽然许多人用长"i"音的读法（'lie-kurt'），但是那些企图保有Dr. Likert原本的读音的人是用短"i"音新手上路成长任务编辑入门编辑规则本人编辑我有疑问内容质疑在线客服官方贴吧意见反馈投诉建议举报不良信息未通过词条申诉投诉侵权信息封禁查询与解封©2024 Baidu 使用百度前必读 | 百科协议 | 隐私政策 | 百度百科合作平台 | 京ICP证030173号 京公网安备110000020000

liker_百度百科

r_百度百科 网页新闻贴吧知道网盘图片视频地图文库资讯采购百科百度首页登录注册进入词条全站搜索帮助首页秒懂百科特色百科知识专题加入百科百科团队权威合作下载百科APP个人中心收藏查看我的收藏0有用+10liker播报讨论上传视频英文单词liker，英文单词，常作名词，译为”喜欢的人；爱好者“。中文名爱好者外文名liker用    途名词英式读法['laɪkə(r)]美式读法['laɪkə(r)]目录1单词用法2短语搭配3双语例句单词用法播报编辑liker，常作名词，译为”喜欢的人；爱好者“。短语搭配播报编辑blind liker 盲目点赞党risk liker 风险偏好者much liker 更像The Liker 按赞君liker appendage 释义指状终末附加环Jeffrey Liker 杰弗瑞·莱克 ; 杰弗里·莱克Liker Scale 克特量表Jeg liker deg 挪威语target-liker outlier 目标信号类型干扰 [1]双语例句播报编辑Jeffrey K. Liker suggests in his new book, The Toyota Way, that this thinking is associated withtraditional process improvement, focusing on local efficiencies. Jeffrey k . Liker在他的新书The Toyota Way，中建议说这些想法与传统的过程改善相关，集中在局部的效率。Liker notes, "This is especially true because in most processes there are relatively few value-added steps, so improving those value-added steps will not amount to much." Liker解释说：“这一点特别正确，因为在多数过程中，很少有价值累加的步骤，因此改善这些步骤也不能得到更多效果。According to Jeffrey Liker, a University of Michigan professor of industrial engineering, it is the way Toyotas are engineered and manufactured that makes them successful. 密西根大学工业工程学教授Jeffrey Liker认为，丰田的成功归功于他们设计和生产的模式。 [1]新手上路成长任务编辑入门编辑规则本人编辑我有疑问内容质疑在线客服官方贴吧意见反馈投诉建议举报不良信息未通过词条申诉投诉侵权信息封禁查询与解封©2024 Baidu 使用百度前必读 | 百科协议 | 隐私政策 | 百度百科合作平台 | 京ICP证030173号 京公网安备110000020000

liker是什么意思_liker的翻译_音标_读音_用法_例句_爱词霸在线词典

r是什么意思_liker的翻译_音标_读音_用法_例句_爱词霸在线词典首页翻译背单词写作校对词霸下载用户反馈专栏平台登录liker是什么意思_liker用英语怎么说_liker的翻译_liker翻译成_liker的中文意思_liker怎么读,liker的读音,liker的用法,liker的例句翻译人工翻译试试人工翻译翻译全文liker英 ['laɪkə(r)]美 ['laɪkə(r)]释义n.喜欢的人，爱好者点击 人工翻译，了解更多 人工释义实用场景例句全部Facing the lover, the winter is the spring, for the liker, winter a beautiful spring.面对心爱的人, 冬天就像是春天, 然而面对喜欢的人, 冬天是个美丽的春天.互联网收起实用场景例句释义实用场

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What Is a Likert Scale? | Guide & Examples

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What Is a Likert Scale? | Guide & Examples

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What Is a Likert Scale? | Guide & Examples

Published on

July 3, 2020

by

Pritha Bhandari

and

Kassiani Nikolopoulou.

Revised on

June 22, 2023.

A Likert scale is a rating scale used to measure opinions, attitudes, or behaviors.

It consists of a statement or a question, followed by a series of five or seven answer statements. Respondents choose the option that best corresponds with how they feel about the statement or question.

Because respondents are presented with a range of possible answers, Likert scales are great for capturing the level of agreement or their feelings regarding the topic in a more nuanced way. However, Likert scales are prone to response bias, where respondents either agree or disagree with all the statements due to fatigue or social desirability or have a tendency toward extreme responding or other demand characteristics.

Likert scales are common in survey research, as well as in fields like marketing, psychology, or other social sciences.

Download Likert scale response options

Table of contentsWhat are Likert scale questions?When to use Likert scale questionsHow to write strong Likert scale questionsHow to write Likert scale responsesHow to analyze data from a Likert scaleAdvantages and disadvantages of Likert scalesOther interesting articlesFrequently asked questions about Likert scales

What are Likert scale questions?

Likert scales commonly comprise either five or seven options. The options on each end are called response anchors. The midpoint is often a neutral item, with positive options on one side and negative options on the other. Each item is given a score from 1 to 5 or 1 to 7.

The format of a typical five-level Likert question, for example, could be:

Strongly disagree

Disagree

Neither agree nor disagree

Agree

Strongly agree

In addition to measuring the level of agreement or disagreement, Likert scales can also measure other spectrums, such as frequency, satisfaction, or importance.

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When to use Likert scale questions

Researchers use Likert scale questions when they are seeking a greater degree of nuance than possible from a simple “yes or no” question.

For example, let’s say you are conducting a survey about customer views on a pair of running shoes. You ask survey respondents “Are you satisfied with the shoes you purchased?”

Yes

No

A dichotomous question like the above gives you very limited information. There is no way you can tell how satisfied or dissatisfied customers really are. You get more specific and interesting information by asking a Likert scale question instead:

“How satisfied are you with the shoes you purchased?”

1 – Very dissatisfied

2 – Dissatisfied

3 – Unsure

4 – Satisfied

5 – Very satisfied

Likert scales are most useful when you are measuring unobservable individual characteristics, or characteristics that have no concrete, objective measurement. These can be elements like attitudes, feelings, or opinions that cause variations in behavior.

How to write strong Likert scale questions

Each Likert scale–style question should assess a single attitude or trait. In order to get accurate results, it is important to word your questions precisely. As a rule of thumb, make sure each question only measures one aspect of your topic.

For example, if you want to assess attitudes towards environmentally friendly behaviors, you can design a Likert scale with a variety of questions that measure different aspects of this topic.

Here are a few pointers:

Include both questions and statements

Use both positive and negative framing

Avoid double negatives

Ask about only one thing at a time

Be crystal clear

Include both questions and statements

A good rule of thumb is to use a mix of both to keep your participants engaged during the survey. When deciding how to phrase questions and statements, it’s important that they are easily understood and do not bias your respondents in one way or another.

Use both positive and negative framing

If all of your questions only ask about things in socially desirable ways, your participants may be biased towards agreeing with all of them to show themselves in a positive light.

Positive framing

Negative framing

Environmental damage caused by single-use water bottles is a serious problem.

Strongly disagree

Disagree

Neither agree nor disagree

Agree

Strongly agree

Banning single-use water bottles is pointless for reducing environmental damage.

Strongly disagree

Disagree

Neither agree nor disagree

Agree

Strongly agree

Respondents who agree with the first statement should also disagree with the second. By including both of these statements in a long survey, you can also check whether the participants’ responses are reliable and consistent.

Avoid double negatives

Double negatives can lead to confusion and misinterpretations, as respondents may be unsure of what they are agreeing or disagreeing with.

Bad example

Good example

I never buy non-organic products.

Strongly disagree

Disagree

Neither agree nor disagree

Agree

Strongly agree

I try to buy organic products whenever possible.

Strongly disagree

Disagree

Neither agree nor disagree

Agree

Strongly agree

Ask about only one thing at a time

Avoid double-barreled questions (asking about two different topics within the same question). When faced with such questions, your respondents may selectively answer about one topic and ignore the other. Questions like this may also confuse respondents, leading them to choose a neutral but inaccurate answer in an attempt to answer both questions simultaneously.

Bad example

Good example

How would you rate your knowledge of climate change and food systems?

Very poor

Poor

Fair

Good

Excellent

How would you rate your knowledge of climate change?

Very poor

Poor

Fair

Good

Excellent

How would you rate your knowledge of food systems?

Very poor

Poor

Fair

Good

Excellent

Be crystal clear

The accuracy of your data also relies heavily on word choice:

Pose your questions clearly, leaving no room for misunderstanding.

Make language and stylistic choices that resonate with your target demographic.

Stay away from jargon that could discourage or confuse your respondents.

How to write Likert scale responses

When using Likert scales, how you phrase your response options is just as crucial as how you phrase your questions.

Here are a few tips to keep in mind.

Decide on a number of response options

Choose the type of response option

Choose between unipolar and bipolar options

Make sure that you use mutually exclusive options

Decide on a number of response options

More options give you deeper insights but can make it harder for participants to decide on one answer. Fewer options mean you capture less detail, but the scale is more user-friendly.

Usually, researchers include five or seven response options. It’s a good idea to include an odd number so that there is a midpoint. However, if you want to force your respondents to choose, an even number of responses removes the neutral option.

5 items

7 items

How frequently do you buy biodegradable products?

Never

Occasionally

Sometimes

Often

Always

How frequently do you buy biodegradable products?

Never

Rarely

Occasionally

Sometimes

Often

Very often

Always

Choose the type of response option

You can measure a wide range of perceptions, motivations, and intentions using Likert scales. Response options should strive to cover the full range of opinions you anticipate a participant can have.

Some of the most common types of items include:

Agreement: Strongly Agree, Agree, Neither Agree nor Disagree, Disagree, Strongly Disagree

Quality: Very Poor, Poor, Fair, Good, Excellent

Likelihood: Extremely Unlikely, Somewhat Unlikely, Likely, Somewhat Likely, Extremely Likely

Experience: Very Negative, Somewhat Negative, Neutral, Somewhat Positive, Very Positive

Some researchers also include a “don’t know” option. This allows them to distinguish between respondents who do not feel sufficiently informed to give an opinion and those who are “neutral” on the topic. However, including a “don’t know” option may trigger unmotivated respondents to select that for every question.

Choose between unipolar and bipolar options

On a unipolar scale, you measure only one attribute (e.g., satisfaction). On a bipolar scale, you can measure two attributes (e.g., satisfaction or dissatisfaction) along a continuum.

Unipolar

Bipolar

How satisfied are you with the range of organic products available?

Not at all satisfied

Somewhat satisfied

Satisfied

Very satisfied

Extremely satisfied

How satisfied are you with the range of organic products available?

Extremely dissatisfied

Dissatisfied

Neither dissatisfied nor satisfied

Satisfied

Extremely satisfied

Your choice depends on your research questions and aims. If you want finer-grained details about one attribute, select unipolar items. If you want to allow a broader range of responses, select bipolar items.

Unipolar scales are most accurate when five-point scales are used. Conversely, bipolar scales are most accurate when a seven-point scale is used (with three scale points on each side of a truly neutral midpoint.)

NoteChoosing between unipolar and bipolar questions is not the same thing as asking two things at once (double-barreled questions).

Make sure that you use mutually exclusive options

Avoid overlaps in the response items. If two items have similar meanings, it risks making your respondent’s choice random.

Bad example

Good example

Environmental damage caused by single-use water bottles is a serious problem.

Strongly agree

Agree

Neither agree nor disagree

Indifferent

Disagree

Strongly disagree

Environmental damage caused by single-use water bottles is a serious problem.

Strongly agree

Agree

Neither agree nor disagree

Disagree

Strongly disagree

Receive feedback on language, structure, and formatting

Professional editors proofread and edit your paper by focusing on:

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How to analyze data from a Likert scale

Before analyzing your data, it’s important to consider what type of data you are dealing with. Likert-derived data can be treated either as ordinal-level or interval-level data. However, most researchers treat Likert-derived data as ordinal: assuming there is not an equal distance between responses.

Furthermore, you need to decide which descriptive statistics and/or inferential statistics may be used to describe and analyze the data obtained from your Likert scale.

You can use descriptive statistics to summarize the data you collected in simple numerical or visual form.

Example: Descriptive statistics

Ordinal data: To get an overall impression of your sample, you find the mode, or most common score, for each question. You also create a bar chart for each question to visualize the frequency of each item choice.

Interval data: You add up the scores from each question to get the total score for each participant. You find the mean, or average, score and the standard deviation, or spread, of the scores for your sample.

You can use inferential statistics to test hypotheses, such as correlations between different responses or patterns in the whole dataset.

Example: Inferential statistics

Ordinal data: You hypothesize that knowledge of climate change is related to belief that environmental damage is a serious problem. You use a chi-square test of independence to see if these two attributes are correlated.

Interval data: You investigate whether age is related to attitudes towards environmentally friendly behavior. Using a Pearson correlation test, you assess whether the overall score for your Likert scale is related to age.

Lastly, be sure to clearly state in your analysis whether you treat the data at interval level or at ordinal level.

Analyzing data at the ordinal level

Researchers usually treat Likert-derived data as ordinal. Here, response categories are presented in a ranking order, but the distances between the categories cannot be presumed to be equal.

For example, consider a scale where 1 = strongly agree, 2 = agree, 3 = neutral, 4 = disagree, and 5 = strongly disagree.

In this scale, 4 is more negative than 3, 2, or 1. However, it cannot be inferred that a response of 4 is twice as negative as a response of 2.

Treating Likert-derived data as ordinal, you can use descriptive statistics to summarize the data you collected in simple numerical or visual form. The median or mode generally is used as the measure of central tendency. In addition, you can create a bar chart for each question to visualize the frequency of each item choice.

Appropriate inferential statistics for ordinal data are, for example, Spearman’s correlation or a chi-square test for independence.

Analyzing data at the interval level

However, you can also choose to treat Likert-derived data at the interval level. Here, response categories are presented in a ranking order, and the distance between categories is presumed to be equal.

Appropriate inferential statistics used here are an analysis of variance (ANOVA) or Pearson’s correlation. Such analysis is legitimate, provided that you state the assumption that the data are at interval level.

In terms of descriptive statistics, you add up the scores from each question to get the total score for each participant. You find the mean, or average, score and the standard deviation, or spread, of the scores for your sample.

Advantages and disadvantages of Likert scales

Likert scales are a practical and accessible method of collecting data.

Quantitative: Likert scales easily operationalize complex topics by breaking down abstract phenomena into recordable observations. This enables statistical testing of your hypotheses.

Fine-grained: Because Likert-type questions aren’t binary (yes/no, true/false, etc.) you can get detailed insights into perceptions, opinions, and behaviors.

User-friendly: Unlike open-ended questions, Likert scales are closed-ended and don’t ask respondents to generate ideas or justify their opinions. This makes them quick for respondents to fill out and ensures they can easily yield data from large samples.

Problems with Likert scales often come from inappropriate design choices.

Response bias: Due to social desirability bias, people often avoid selecting the extreme items or disagreeing with statements to seem more “normal” or show themselves in a favorable light.

Fatigue/inattention: In Likert scales with many questions, respondents can get bored and lose interest. They may absent-mindedly select responses regardless of their true feelings. This results in invalid responses.

Subjective interpretation: Some items can be vague and interpreted very differently by respondents. Words like “somewhat” or “fair” don’t have precise or narrow definitions.

Restricted choice: Since Likert-type questions are closed-ended, respondents sometimes have to choose the most relevant answer even if it may not accurately reflect reality.

Other interesting articles

If you want to know more about statistics, methodology, or research bias, make sure to check out some of our other articles with explanations and examples.

Statistics

Student’s t-distribution

Normal distribution

Null and Alternative Hypotheses

Chi square tests

Confidence interval

Quartiles & Quantiles

Methodology

Cluster sampling

Stratified sampling

Data cleansing

Reproducibility vs Replicability

Peer review

Prospective cohort study

Research bias

Implicit bias

Cognitive bias

Placebo effect

Hawthorne effect

Hindsight bias

Affect heuristic

Social desirability bias

Frequently asked questions about Likert scales

What is a Likert scale?

A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviors. It is made up of 4 or more questions that measure a single attitude or trait when response scores are combined.

To use a Likert scale in a survey, you present participants with Likert-type questions or statements, and a continuum of items, usually with 5 or 7 possible responses, to capture their degree of agreement.

Are Likert scales ordinal or interval scales?

Individual Likert-type questions are generally considered ordinal data, because the items have clear rank order, but don’t have an even distribution.

Overall Likert scale scores are sometimes treated as interval data. These scores are considered to have directionality and even spacing between them.

The type of data determines what statistical tests you should use to analyze your data.

What is operationalization?

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data, it’s important to consider how you will operationalize the variables that you want to measure.

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Likert Scale: What Is It and How to Use It?

Likert Scale: What Is It and How to Use It?

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Likert Scale: What Is It and How to Use It?

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Updated on June 03, 2019

A Likert scale is a close-ended, forced-choice scale used in a questionnaire that provides a series of answers that go from one extreme to another. For example, a scale might have five choices that start at one end with "strongly agree" and end at the other with "strongly disagree," with less extreme choices in the middle three points. Likert scales are widely used in psychology and other social science research.

Key Takeaways: Likert Scales

A Likert scale enables respondents to choose from a linear set of responses that increase or decrease in intensity or strength. It is a close-ended, forced-choice scale.Widely used in psychological and other social science research today, Likert scales enable researchers to collect data that provides nuance and insight into participants’ opinions. This data is quantitative and can easily be analyzed statistically.Likert items often offer response categories on a 1-to-5 scale, but a range of options is possible, including 1-to-7 and 0-to-4 scales or even-numbered scales that typically range from 1-to-4 or 1-to-6.

Creation of the Likert Scale

The Likert Scale was developed by American psychologist Rensis Likert in 1932. Likert wanted to find a way to systematically measure individual attitudes. His solution was the scale that now bears his name.

Likert scales offer a continuum or series of typically five to seven fixed-choice options. This enables people to self-report the extent to which they agree or disagree with a given proposition. As a result, Likert scales allow for more nuance than a simple binary response, like a yes or no. This is the reason why Likert scales are often used to collect data in psychological research.

Likert Scale Format

You know you’re completing a Likert scale if you’re asked to give an opinion in response to a statement by choosing from a series of choices that enable you to rate your degree of agreement. Sometimes instead of a statement, the item will be a question. The most important thing to note, however, is that the options from which you can choose your response offer a range of opinions that don’t overlap. 

Likert scales create a linear set of responses that increase or decrease in intensity or strength. These response categories are open to respondent interpretation. So, for example, one respondent may select “agree” in response to a statement, while another feels the same way but selects “strongly agree" instead. Regardless, respondents and the researchers collecting their data understand that “strongly agree” is considered a more intensely positive option than “agree.”

While it’s most common to see Likert scales that include 5 to 7 response options, sometimes a researcher will use more. Nonetheless, it’s been observed that when people are presented with a greater number of response options they don’t tend to choose the responses at either end of the scale. Perhaps in a large scale the end-point options look too extreme.

A scale with an odd number of response categories has a midpoint that will be considered neutral. If a researcher wants to force a respondent to choose whether they lean one way or another on a question, they can eliminate the neutral option by using a scale with an even number of options.

Examples

Here are some examples of Likert items from real psychological questionnaires.

From the Big 5 Personality Trait Short Questionnaire:

I see myself as someone who is full of energy, likes to always be active.

0.    Totally disagree

1.    Disagree a little

2.    Neutral opinion

3.    Agree a little

4.    Totally Agree

From the Meaning in Life Questionnaire:

I am always looking to find my life’s purpose

1.    Absolutely untrue

2.    Mostly untrue

3.    Somewhat untrue

4.    Can’t say true or false

5.    Somewhat true

6.    Mostly true

7.    Absolutely true

From the BBC Well-Being Scale:

Do you feel you have control of your life?

1.    Not at all

2.    A little

3.    Moderately

4.    Very Much

5.    Extremely

Likert scales can be used to ask for a wide range of attitudes besides agreement. In addition to the examples above, Likert items can ask about how frequently an individual does something (endpoints for a frequency item would be “Very frequently” and “Never”), how important an individual believes something is to them (endpoints for an importance item would be “Very Important” and “Not very important”), and how much one likes something (endpoints for a liking item would be “A lot” and “Not at all”).

Advantages and Disadvantages of Likert scales

By including several categories to choose from in the response to each item, Likert scales enable a researcher to collect data that provides nuance and insight into participants’ opinions. Also, this data is quantitative so it's fairly easy to analyze statistically.

On the other hand, Likert scales may be impacted by respondents' need to appear socially desirable. Especially if a participant holds an opinion that they know would be deemed socially unacceptable, they may choose a response to an item that will make their opinion seem more appropriate to the rest of the world. For example, an individual is unlikely to agree with items that would cause them to seem prejudiced when completing a questionnaire about attitudes towards minorities, A possible remedy for this issue could be to allow respondents to fill out questionnaires anonymously.

Sources

Cherry, Kendra. “Using Likert Scales in Psychology.” Verywell Mind, 14 June 2018. https://www.verywellmind.com/what-is-a-likert-scale-2795333

Jamieson, Susan. "Likert Scale." Encyclopaedia Britannica, 16 December 2013. https://www.britannica.com/topic/Likert-Scale

Kinderman, Peter, Schwannauer, Matthias, Pontin, Eleanor, and Tai, Sara. "The Development and Validation of a General Measure of Well-Being: The BBC Well-Being Scale." Quality of Life Research, vol. 20, no. 7, 2011, pp. 1035-1042. doi: 10.1007/s11136-010-9841-z

McLeod, Saul. “Likert Scale.” Simply Psychology, 24 October 2008. https://www.simplypsychology.org/likert-scale.html

Morizot, Julien. "Construct Validity of Adolescents' Self-Reported Big Five Personality Traits: Importance of Conceptual Breadth and Initial validation of a Short Measure." Assessment, vol. 21, no. 5, 2014, pp. 580-606. doi: 10.1177/1073191114524015,

The Editors of Encyclopaedia Britannica. “Rensis Likert.” Encyclopaedia Britannica, 30 August 2018. https://www.britannica.com/biography/Rensis-Likert

Steger, Michael F., Frazier, Patricia, Oishi, Shigegiro, & Kaler, Matthew. "The Meaning in Life Questionnaire: Assessing the Presence of and Search for Meaning in Life." Journal of Counseling Psychology, vol. 53, no. 1, 2006, pp. 80-93. doi: 10.1037/0022-0167.53.1.80

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以一般方法 ( Authcore ) 註冊 Liker ID - LikeCoin

以一般方法 ( Authcore ) 註冊 Liker ID - LikeCoin

LikeCoin中文WebsiteDiscord GitHubSupport UsAsk or search…⌃KLinksLikeCoin - 去中心出版LikeCoin 進度更新LikeCoin 答客問品牌素材下載 指南社群Writing NFT去中心出版水龍頭錢包交易流動性委託治理傳媒報導 去中心應用Web3PressLiker Land讚賞公民Liker ID以 Keplr 註冊 Liker ID匯出錢包助記詞以一般方法 ( Authcore ) 註冊 Liker ID保護你的 Liker ID綁定社交帳號重設密碼管理登入裝置什麼是 Authcore？修改頭像及顯示名稱Liker.Socialdepub.spaceLikeCoin button 讚賞鍵創作者工具詞彙表 開發者資源開發者簡介 驗證人成為驗證人存檔存檔Powered By GitBook以一般方法 ( Authcore ) 註冊 Liker IDLiker ID 要怎樣註冊？使用 Liker Land 手機應用程式 能以一般方法 ( Authcore ) 註冊 Liker ID。但留意此登入方式將慢慢淡出。建議用戶立即從 Authcore 匯出你的助記詞並導入 Keplr 或其他錢包，以便管理你的 LikeCoin。使用 Liker Land app 以一般方法 ( Authcore ) 註冊 Liker ID只需下載 Liker Land 手機應用程式，並執行以下程序即可：步驟一：開始註冊打開 Liker Land 手機應用程式，點「註冊」。點「註冊」步驟二：選擇註冊方式Liker Land app 提供電郵地址+密碼及社交帳號 Google 登入、Facebook 登入、Twitter 登入、Apple ID 登入及 Matters 登入等 6 種註冊方式。建議以社交帳號註冊，過程較簡單安全。點擊登入畫面上方的社交帳號圖示。選擇註冊方式步驟三：登入社交帳號及進行授權填上社交帳戶資料並登入帳戶。以 Twitter 帳號為例，請填入 Twitter 用戶名稱及登入密碼，並點「授權應用程式」。登入社交帳號及進行授權步驟四：創建 Liker ID彈出綠色的畫面如下，請輸入你喜歡的 Liker ID。系統已為你預設選了一個，若不滿意可在此步驟中修改。填上 Liker ID 後，點「確認」完成程序。輸入你喜歡的 Liker ID 並點「確認」一旦創建了 Liker ID，便不能修改字詞組合或登入方式。若不想再用某個 Liker ID，建議你把它留著不用，再創建一個新的。留意一個電郵地址只可以註冊一個 Liker ID。同一電郵地址並不能同時以 Authcore 及 Keplr 註冊 Liker ID。Liker Land 手機應用程式使用 Authcore 登入。什麼是 Authcore？請參考此條目。所有 LikeCoin 推薦獎賞及讚賞公民推廣活動經已於2021年3月8日完結。使用指南LIKE payPrevious匯出錢包助記詞Next保護你的 Liker IDLast modified 2mo agoOn this page使用 Liker Land app 以一般方法 ( Authcore ) 註冊 Liker ID步驟一：開始註冊步驟二：選擇註冊方式步驟三：登入社交帳號及進行授權步驟四：創建 Liker ID使用指南

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李克特量表：例題和使用指南 | SurveyMonkey

李克特量表：例題和使用指南 | SurveyMonkey

產品產品概覽SurveyMonkey 能滿足各種使用案例和需求。歡迎探索我們的產品，瞭解 SurveyMonkey 能為您提供什麼協助。SurveyMonkey從全球首屈一指的線上調查問卷中，獲取以資料為導向的深入分析。整合可與超過 100 款應用程式和外掛程式整合，讓您事半功倍。SurveyMonkey 表單建立並自訂線上表單，以收集資訊和付款方式。SurveyMonkey 計分高手利用內建的 AI 打造更優質的調查問卷並快速獲得獨到見解。市場研究解決方案依實際需求量身打造解決方案，滿足您所有的市場研究需求。產業醫療保健教育科技政府金融服務查看更多產業角色行銷客戶體驗產品人力資源研究查看更多角色使用案例線上民意調查登記表單員工意見活動意見客戶滿意度查看更多使用案例聯絡銷售人員範本淨推薦分數測量客戶對貴公司的滿意度和忠誠度。客戶滿意度瞭解如何讓客戶滿意，使他們成為您忠實的擁護者。網站意見取得可化為實際行動的深入解析，以改善使用者的體驗。聯絡資訊向潛在客戶、受邀人等對象收集聯絡資訊。活動報名輕鬆收集並追蹤活動邀請回函。活動意見瞭解參加者的需要，使下一場活動更成功。員工參與度發掘能提升員工參與度並改善績效的深入解析。會議意見回饋瞭解與會者的想法和意見，把下一場會議辦得更好。360 度員工評估運用同儕意見回饋來協助員工改善績效。課程評估打造更好的課程並改善教學方法。大學教師評鑑瞭解學生對課程資料和教學狀況的評價。產品測試瞭解客戶對您的新產品構想有何看法。查看所有範本聯絡銷售人員定價Enterprise相關資源資源中心使用調查問卷和調查資料的最佳實務Curiosity at Work 部落格有關問卷調查、給企業的訣竅及其他主題的內容，都在我們的部落格。客戶支援中心SurveyMonkey 的使用教學與指南。客戶頂尖品牌如何透過 SurveyMonkey 推動成長。聯絡銷售人員聯絡銷售人員登入免費註冊免費註冊產品產品概覽SurveyMonkey 能滿足各種使用案例和需求。歡迎探索我們的產品，瞭解 SurveyMonkey 能為您提供什麼協助。SurveyMonkey從全球首屈一指的線上調查問卷中，獲取以資料為導向的深入分析。整合可與超過 100 款應用程式和外掛程式整合，讓您事半功倍。SurveyMonkey 表單建立並自訂線上表單，以收集資訊和付款方式。SurveyMonkey 計分高手利用內建的 AI 打造更優質的調查問卷並快速獲得獨到見解。市場研究解決方案依實際需求量身打造解決方案，滿足您所有的市場研究需求。產業醫療保健教育科技政府金融服務查看更多產業角色行銷客戶體驗產品人力資源研究查看更多角色使用案例線上民意調查登記表單員工意見活動意見客戶滿意度查看更多使用案例範本淨推薦分數測量客戶對貴公司的滿意度和忠誠度。客戶滿意度瞭解如何讓客戶滿意，使他們成為您忠實的擁護者。網站意見取得可化為實際行動的深入解析，以改善使用者的體驗。聯絡資訊向潛在客戶、受邀人等對象收集聯絡資訊。活動報名輕鬆收集並追蹤活動邀請回函。活動意見瞭解參加者的需要，使下一場活動更成功。員工參與度發掘能提升員工參與度並改善績效的深入解析。會議意見回饋瞭解與會者的想法和意見，把下一場會議辦得更好。360 度員工評估運用同儕意見回饋來協助員工改善績效。課程評估打造更好的課程並改善教學方法。大學教師評鑑瞭解學生對課程資料和教學狀況的評價。產品測試瞭解客戶對您的新產品構想有何看法。查看所有範本定價Enterprise相關資源資源中心使用調查問卷和調查資料的最佳實務Curiosity at Work 部落格有關問卷調查、給企業的訣竅及其他主題的內容，都在我們的部落格。客戶支援中心SurveyMonkey 的使用教學與指南。客戶頂尖品牌如何透過 SurveyMonkey 推動成長。聯絡銷售人員登入免費註冊什麼是李克特量表？認識用來衡量意見、觀感和行為最可靠的題型之一，並了解如何在下一份調查問卷中使用它。註冊後即可在下一份調查問卷中使用李克特量表瞭解李克特量表調查問卷問題的使用時機與使用方式您是否回答過「您對某件事情的同意程度」這類問題？這種類型的問題就稱為李克特量表。李克特量表常用於衡量態度和意見，而且能比單純的「是/否」題型辨別出更細微的差異。讓我們來探討一下李克特量表型的問題、找出一些範例，瞭解何時應使用此工具以及如何在調查問卷中使用它。什麼是李克特量表？在瞭解李克特評分表之前，您必須先知道什麼是調查問卷量表。 調查問卷量表指的是一組答案選項 (可能是數字或字句)，其中涵蓋了關於某個主題的一系列意見。形式上，它屬於封閉式問題，因此受訪者只能從預先設定的答案選項中做選擇。那麼，李克特量表題型是什麼呢？它把評分表分為 5 或 7 個等級 (有時又稱作滿意度等級)，兩端分別為兩種極端的態度，讓受訪者在這個範圍之間做選擇。李克特量表題型當中一定會包含一個中等或中立的選項。李克特量表 (以其創造者美國社會學家倫西斯·李克特 (Rensis Likert) 命名) 非常廣為使用，因為它們是衡量意見、觀感和行為最可靠的方式之一。與只提供兩個選項的二分法問題相比，李克特題型可讓您得知更細微的意見，比如說您的產品是「尚可」還是「超棒」，而非「好」或「不好」而已。李克特題型還能用來瞭解員工對最近一次的公司旅遊是「非常滿意」、「有些不滿意」還是「沒意見」。這種方式將可讓您得知意見程度上的不同，對於瞭解您所獲得的意見反應有很大的幫助。它也可以指出您的哪些服務或產品的哪些方面有待改進。透過我們的線上調查問卷受訪群，取得市場意見和情報立即試用李克特量表的優點李克特量表提供的答案選項是可量化的，因此收集到的資料也較容易分析。它也提供涵蓋一整個範圍的多重選項，使受訪者能選出更貼近自身感受的答案。李克特量表問題既能滿足受訪者，又能提升資料品質李克特量表很棒的一點是，它可以協助您避開調查問卷設計的一些常見陷阱，例如提出過於廣泛的問題，使受訪者難以思考。這可能會使他們感到沮喪，並加快回答速度，從而影響資料品質。調查問卷的設計人員在倉促下有時會使用範圍較廣泛的問題類型 (例如「是/否」、「全選」、開放式排名或矩陣式問題) 作為調查捷徑。但是，根據經驗法則，在大多數情況下，他們應該信任自己慣用的老夥伴李克特量表，因為這種問題類型使受訪者能專注回答問題，並對其簡單、直接的語言感到自在。當問題集中在某個主題上時，李克特量表能發揮較好效果務必使調查問卷中的每一系列問題都集中在同一主題上。這樣才能獲得更準確的結果。為什麼？因為當您報告資料時，必須分析代表一些問題歸納結果的分數。例如，一開始您可以問這個問題：您對本店今晚供應的晚餐滿意度如何？然後再接著問：您對本店今晚供應的開胃菜滿意度如何？您對本店今晚供應的主餐滿意度如何？您對本店今晚供應的甜點滿意度如何？但有個問題應該放在調查問卷的另一個部分：您對今晚的衣帽間服務滿意度如何？將與某個主題有關的問題歸類為一組，然後把回覆分數加總以獲得一個總分 (以上述的例子來說，就是「食物品質」的總分)。這麼做能更準確地衡量受訪者對特定產品、服務或事件的態度。李克特量表使用案例和舉例李克特量表問題被廣泛運用於許多類型的調查，無論您是想瞭解員工對工作有何感受，還是客戶對於您的新產品有何想法，都能使用這種題型來詢問。客戶滿意度典型的客戶滿意度調查問卷會用順序量尺 (ordinal scale) 來讓使用者評量自己的意見等級。舉例來說，您可以使用五分制的李克特量表來詢問客戶對某個陳述的同意程度，從最高同意度到最低同意度，中間搭配一個中性的答案選項。李克特量表提供的回覆選項對客服而言非常有彈性，而且可以測量多種情緒和感受，像是同意度、滿意度，甚至是頻率和嚮往度等等。舉例來說，您可能想知道客戶多常使用您的線上支援入口網站，這時就很適合列出不同程度的使用頻率 (如：從不、很少、有時候、時常、很頻繁)。以下為客戶服務運用李克特量表測量「滿意度」的例子：整體而言，您對我們公司滿意還是不滿意？非常滿意還算滿意沒意見有點不滿意非常不滿意查看範例員工參與度李克特量表也是與員工保持溝通的好工具。公司可以用五分制的李克特量表瞭解員工議題，以持續觀察員工的參與度和情緒。舉例來說，公司可用這個方法瞭解員工對公司提供的資源有多熟悉、對資訊科技相關政策有多瞭解，或他們有多常使用新工具。李克特量表也能幫助公司瞭解員工的平均趨勢，或評量整體員工對特定議題的平均滿意度。來看看下面這個例子：公司對教育訓練的投入讓我感到滿意：非常同意同意沒有同意，也沒有不同意不同意非常不同意查看範例專業活動意見反應行銷人員或活動專家可利用五分制的李克特量表來瞭解活動是否成功。活動後調查問卷可以運用各式各樣的李克特量表問題，來評估整體活動體驗、詢問參與者對活動的其他感受 (例如再次參加的可能性)，或瞭解活動地點的重要性。舉例來說，下面這道問題就是用李克特量表來評估活動內容的價值：專業活動中提到的內容實用度為何？極有幫助很有幫助還算有幫助沒什麼幫助完全沒幫助查看範例或查看其他範本何時該使用李克特量表調查問卷調查問卷問題的題型那麼多，我要怎麼知道何時該使用李克特題型呢？李克特量表適合用來詳細瞭解人們對某個特定主題的看法。因此，當您需要探討下面這些議題時，可以考慮使用李克特題型：人們對您的新產品有什麼反應您的團隊對辦公室最近的發展有什麼想法您的客戶對貴公司的客戶服務有什麼感想對參加者來說，您舉辦的公開活動有多成功…或需要衡量對特定事物觀感，並且您希望回覆內容能提供更深層細節的任何其他問題。如果您希望對此有所瞭解，則更深入的細節是指調查專家所說的差異性。您擁有的差異性越多，就越能瞭解某人想法的細微差別。設計李克特量表問題完全不費力SurveyMonkey 計分高手可幫助您快速又胸有成竹地建立問卷調查。您只要選擇一種答案類型，計分高手就會自動為您奉上一組預先編寫好的答案選項。瞭解更多如何撰寫李克特量表調查問卷問題表達精準要提升李克特題型的效果，您必須用正確的方式表達，避免混淆受訪者。當您詢問客人對餐廳服務的滿意度時，您指的是泊車人員、服務生還是接待員提供的服務呢？還是以上皆是？您要問的是他們對服務速度、禮儀，還是餐飲品質的滿意度呢？總之，在使用李克特題型的時候，您越能詳細而具體地闡述問題，所獲得的答案就會越有參考價值。謹慎使用形容詞當您要用文字詢問某種概念時，必須確保人們能確實理解您的意思。您的回覆選項應該包含一系列易於理解的描述性字詞，而且各個選項之間的等級高低應該要很清楚，不需多加解釋。舉個例子：「相當多」和「還算多」到底哪個比較多呢？我們建議您先把極端值定下來 (「極」、「毫不」)，然後再定出表示中等程度 (「普通」) 或中立性 (「既不同意也不反對」) 的中間點，最後再用「很」、「有點」之類程度非常明確的字詞來建構其他選項。單極或雙極？ 您是希望瞭解受訪者在兩個極端 (「喜愛」與「厭惡」) 之間的分布，還是從「無」到「最大」之間的分布？在多數情況下，使用單極量表比較好。也就是說，使用從「極為勇敢」到「一點也不勇敢」的量表，比使用從「極為勇敢」到「極為退縮」的量表還好。單極量表不但比較容易回答，而且您可以確定左右兩極確實完全相反，因此從研究方法角度來看是比較可靠的做法。盡量使用問句 陳述語句有個隱形的風險：大多數人會傾向選擇同意，避免選擇不同意，這是因為大多數的人會盡量保持友善並尊重他人。(這種現象亦稱為默認回覆偏差。)因此，直接說出問題會比作出陳述更有效。關於如何使用李克特量表的另外 5 個要訣加上說明。 數字量表上如果只有數字，沒有任何文字說明，受訪者可能不一定知道量表上的哪一端代表正面，哪一端代表負面。使用奇數個選項。 有奇數個選項的量表一定會有個中間點。那麼，應該提供受訪者幾個選項呢？一般來說，當選項超過七個，受訪者會很難斷定自己的觀點。如果您提供超過七個回覆選項，受訪者較有可能隨機做選擇，使您的資料失去意義。我們的方法學家建議，使用單向量表時，設定五個選項，而使用雙向量表時，設定七個選項。保持連續性。 量表上的回覆選項在意義上應該要彼此等距。這對文字選項 (相對於數字量表) 來說比較有挑戰性，您一定要非常清楚您每個選項所代表的意義。範圍要夠廣。 量表應該涵蓋所有可能的回覆。假設您詢問顧客：「服務生的動作有多迅速？」但答案範圍只從「極為迅速」到「普通迅速」，那麼覺得服務生動作很慢的受訪者就不知道要怎麼選了。運用邏輯。 您可利用跳過邏輯替受訪者節省一些時間！例如，假述您想詢問顧客有多喜愛您的餐廳，但只想針對不甚滿意的客戶收集更多資訊以瞭解詳情，您可以新增問題邏輯，只讓不滿意的顧客跳往詢問改善建議的問題頁面。即使您不知道李克特量表這個名稱，您可能也接觸這種類型的問題很長時間了。現在，您還瞭解如何設計有效的李克特量表型問題，這些問題可以更細微地區分調查問卷中重要問題的回覆。設計李克特量表調查問卷下一份調查問卷就使用自訂的李克特量表，以獲得最好的深入解析。SurveyMonkey 提供豐富的彈性，您可依預算訂閱最理想的方案。歡迎立即註冊。探索更多資源工具組目錄探索我們專為特定角色或產業設計的眾多工具組，幫助您善加利用意見回饋。瞭解更多探索 SurveyMonkey Enterprise 功能利用 SurveyMonkey 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