{"id":59144,"date":"2018-07-05T23:26:46","date_gmt":"2018-07-06T06:26:46","guid":{"rendered":"https:\/\/www.questionpro.com\/blog\/?p=59144"},"modified":"2023-08-18T06:46:34","modified_gmt":"2023-08-18T06:46:34","slug":"interval-data","status":"publish","type":"post","link":"https:\/\/www.questionpro.com\/blog\/interval-data\/","title":{"rendered":"Interval Data: Definition, Characteristics and Examples"},"content":{"rendered":"

Interval Data: Definition?<\/b><\/h2>\n

Interval data, also called an integer, is defined as a data type which is measured along a scale, in which each point is placed at equal distance from one another. Interval data always appears in the form of numbers or numerical values where the distance between the two points is standardized and equal. <\/span><\/p>\n

Interval data cannot be multiplied or divided, however, it can be added or subtracted. Interval data is measured on an <\/span>interval scale<\/span><\/a>. A simple example of interval data: The difference between 100 degrees Fahrenheit and 90 degrees Fahrenheit is the same as 60 degrees Fahrenheit and 70 degrees Fahrenheit. <\/span><\/p>\n

In <\/span>market research<\/span><\/a> or in any other forms of social, economic or business research interval data plays a pivotal role. What makes interval data so popular and in-demand is because interval data supports almost all statistical test and transformations in obtaining <\/span>quantitative data<\/span><\/a>.<\/span><\/p>\n

LEARN ABOUT:\u00a0<\/strong>Test Market Demand<\/a><\/p>\n

Interval data has very distinctive attributes that make it distinct in comparison to nominal data<\/a>, ordinal data or even ratio data. Interval data doesn\u2019t have a defined absolute zero point which is present in ratio data. The lack of absolute point zero makes comparisons of direct magnitudes impossible. For example, Object A is twice as large as Object B is not a possibility in interval data. <\/span><\/p>\n

Learn more: <\/span>Variable Measurement Scales- Nominal, Ordinal, Interval and Ratio.<\/span><\/a><\/p>\n

Interval Data Analysis<\/b><\/h3>\n

Since interval data is quantitative analysis<\/a> data type almost all the methods used to analyze quantitative can be used. Here are a few examples:\u00a0\u00a0<\/span><\/p>\n

1. Trend analysis<\/b><\/p>\n

Trend analysis<\/span><\/a> is a popular interval data analysis technique, used to draw trends and insights by capturing survey data over a certain period of time. In other words, a trend analysis on interval data is conducted by capturing data using an interval scale survey in multiple iterations, using the same question.<\/span><\/p>\n

2. SWOT Analysis<\/b><\/p>\n

Analysis conducted to evaluate an organization\u2019s strengths, weaknesses, opportunities, and threats is called <\/span>SWOT analysis<\/span><\/a> and is widely used to evaluate interval data. Strengths and weaknesses are internal aspects of an organization while opportunities and threat are external to an organization. An organization can measure interval data to evaluate market competition as well as plan future marketing activities using the SWOT analysis results.<\/span><\/p>\n

LEARN ABOUT:<\/strong> Level of Analysis<\/a><\/em><\/p>\n

3. Conjoint Analysis <\/b><\/p>\n

Conjoint Analysis<\/span><\/a> is an advanced level market research technique usually implemented to analyze how individuals make complicated decisions in an interval scale. Which factors are important for customers before they make decisions where they have multiple options available at their disposal. <\/span><\/p>\n

4. TURF Analysis<\/b><\/p>\n

TURF analysis<\/span><\/a> stands for Totally Unduplicated Reach and Frequency analysis- is a method that allows a marketer to analyze the potential of market research for a combination of products and services. It evaluates the interval data of customers reached by a particular source of communication and its frequency. This analysis technique is used by researchers to understand whether a new product or service will be well-received in the target market or not. This unit of analysis<\/a> method was primarily used for designing media campaigns but has expanded to being used in product distribution and line analysis. <\/span><\/p>\n

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Key Characteristics of Interval Data<\/b><\/h3>\n

Here are a few characteristics of Interval data: <\/span><\/p>\n