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Difference between revisions of "Data"

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Computer data is information processed or stored by a computer. This information may be in the form of text documents, images, audio clips, software programs, or other types of data. Computer data may be processed by the computer's CPU and is stored in files and folders on the computer's hard disk. At its most rudimentary level, computer data is a bunch of ones and zeros, known as binary data. Because all computer data is in binary format, it can be created, processed, saved, and stored digitally. This allows data to be transferred from one computer to another using a network connection or various media devices. It also does not deteriorate over time or lose quality after being used multiple times.<ref>What is Computer Data? [https://techterms.com/definition/data Techterms]</ref>
 
Computer data is information processed or stored by a computer. This information may be in the form of text documents, images, audio clips, software programs, or other types of data. Computer data may be processed by the computer's CPU and is stored in files and folders on the computer's hard disk. At its most rudimentary level, computer data is a bunch of ones and zeros, known as binary data. Because all computer data is in binary format, it can be created, processed, saved, and stored digitally. This allows data to be transferred from one computer to another using a network connection or various media devices. It also does not deteriorate over time or lose quality after being used multiple times.<ref>What is Computer Data? [https://techterms.com/definition/data Techterms]</ref>
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Five Characteristics Of Good Quality Data!
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One of the most important things to always remember is that not all data could be considered of fine quality hence making them limited in their usefulness. In order to fully realize the benefits of data, it has to be of high quality. This means that one should look out for certain characteristics in the data. These are:
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Data should be precise which means it should contain accurate information. Precision saves time of the user as well as their money.
 +
Data should be relevant and according to the requirements of the user. Hence the legitimacy of the data should be checked before considering it for usage.
 +
Data should be consistent and reliable. False data is worse than incomplete data or no data at all.
 +
Relevance of data is necessary in order for it to be of good quality and useful. Although in today’s world of dynamic data any relevant information is not complete at all times however at the time of its usage, the data has to be comprehensive and complete in its current form.
 +
A high quality data is unique to the requirement of the user. Moreover it is easily accessible and could be processed further with ease.
  
  
 
== Quantitative and Qualitative Data<ref>What Are Quantitative and Qualitative Data Types in Statistics? [https://www.chi2innovations.com/blog/discover-data-blog-series/data-types-101/ Chi Squared Innovations</ref> ==
 
== Quantitative and Qualitative Data<ref>What Are Quantitative and Qualitative Data Types in Statistics? [https://www.chi2innovations.com/blog/discover-data-blog-series/data-types-101/ Chi Squared Innovations</ref> ==
 
When it all boils down to it, all data that is collected are either measured or are an observed feature of interest, and at the highest level that gives us 2 kinds of data:
 
When it all boils down to it, all data that is collected are either measured or are an observed feature of interest, and at the highest level that gives us 2 kinds of data:
*Quantitative data: Quantitative data is information about quantities of things, things that we measure, and so we describe them in terms of numbers. As such, quantitative data are also called Numerical data. Quantitative data are used when a researcher is trying to quantify a problem, or address the "what" or "how many" aspects of a research question. It is data that can either be counted or compared on a numeric scale. For example, it could be the number of first year students at Macalester, or the ratings on a scale of 1-4 of the quality of food served at Cafe Mac. This data are usually gathered using instruments, such as a questionnaire which includes a ratings scale or a thermometer to collect weather data. Statistical analysis software, such as SPSS, is often used to analyze quantitative data.
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*Quantitative data: Quantitative data is information about quantities of things, things that we measure, and so we describe them in terms of numbers. As such, quantitative data are also called Numerical data. Quantitative data are used when a researcher is trying to quantify a problem, or address the "what" or "how many" aspects of a research question. It is data that can either be counted or compared on a numeric scale. For example, it could be the number of first year students at a University, or the ratings on a scale of 1-4 of the quality of food served at a restaurant. This data are usually gathered using instruments, such as a questionnaire which includes a ratings scale or a thermometer to collect weather data. Statistical analysis software, such as SPSS, is often used to analyze quantitative data.
 
*Qualitative data: On the other hand, qualitative data give us information about the qualities of things. They are observed phenomenon, not measured, and so we generally label them with names. Qualitative data are also known as Categorical data. Qualitative data describes qualities or characteristics. It is collected using questionnaires, interviews, or observation, and frequently appears in narrative form. For example, it could be notes taken during a focus group on the quality of the food at a restaurant, or responses from an open-ended questionnaire. Qualitative data may be difficult to precisely measure and analyze. The data may be in the form of descriptive words that can be examined for patterns or meaning, sometimes through the use of coding. Coding allows the researcher to categorize qualitative data to identify themes that correspond with the research questions and to perform quantitative analysis.
 
*Qualitative data: On the other hand, qualitative data give us information about the qualities of things. They are observed phenomenon, not measured, and so we generally label them with names. Qualitative data are also known as Categorical data. Qualitative data describes qualities or characteristics. It is collected using questionnaires, interviews, or observation, and frequently appears in narrative form. For example, it could be notes taken during a focus group on the quality of the food at a restaurant, or responses from an open-ended questionnaire. Qualitative data may be difficult to precisely measure and analyze. The data may be in the form of descriptive words that can be examined for patterns or meaning, sometimes through the use of coding. Coding allows the researcher to categorize qualitative data to identify themes that correspond with the research questions and to perform quantitative analysis.

Revision as of 16:58, 6 April 2021

Data is distinct pieces of information, usually formatted in a special way. Data can exist in a variety of forms — as numbers or text on pieces of paper, as bits and bytes stored in electronic memory, or as facts stored in a person's mind. Since the mid-1900s, people have used the word data to mean computer information that is transmitted or stored. Strictly speaking, data is the plural of datum, a single piece of information. In practice, however, people use data as both the singular and plural form of the word, and as a mass noun.[1]


Data is more than just data[2]

In the Reference Model for an Open Archival Information System (OAIS) (Wikipedia), data is defined as "[a] reinterpretable representation of information in a formalized manner suitable for communication, interpretation, or processing. Examples of data include a sequence of bits, a table of numbers, the characters on a page, the recording of sounds made by a person speaking, or a moon rock specimen." Types of data include:

  • observational data
  • laboratory experimental data
  • computer simulation
  • textual analysis
  • physical artifacts or relics

For social science, data is generally numeric files originating from social research methodologies or administrative records, from which statistics are produced. It also includes, however, more data formats such as audio, video, geospatial and other digital content that are germane to social science research. Digital text is becoming increasingly important in the humanities and arts. Research in these areas may think of data in the form of textual information, semantic elements, and text objects.

Computer data is information processed or stored by a computer. This information may be in the form of text documents, images, audio clips, software programs, or other types of data. Computer data may be processed by the computer's CPU and is stored in files and folders on the computer's hard disk. At its most rudimentary level, computer data is a bunch of ones and zeros, known as binary data. Because all computer data is in binary format, it can be created, processed, saved, and stored digitally. This allows data to be transferred from one computer to another using a network connection or various media devices. It also does not deteriorate over time or lose quality after being used multiple times.[3]


Five Characteristics Of Good Quality Data! One of the most important things to always remember is that not all data could be considered of fine quality hence making them limited in their usefulness. In order to fully realize the benefits of data, it has to be of high quality. This means that one should look out for certain characteristics in the data. These are:

Data should be precise which means it should contain accurate information. Precision saves time of the user as well as their money. Data should be relevant and according to the requirements of the user. Hence the legitimacy of the data should be checked before considering it for usage. Data should be consistent and reliable. False data is worse than incomplete data or no data at all. Relevance of data is necessary in order for it to be of good quality and useful. Although in today’s world of dynamic data any relevant information is not complete at all times however at the time of its usage, the data has to be comprehensive and complete in its current form. A high quality data is unique to the requirement of the user. Moreover it is easily accessible and could be processed further with ease.


Quantitative and Qualitative Data[4]

When it all boils down to it, all data that is collected are either measured or are an observed feature of interest, and at the highest level that gives us 2 kinds of data:

  • Quantitative data: Quantitative data is information about quantities of things, things that we measure, and so we describe them in terms of numbers. As such, quantitative data are also called Numerical data. Quantitative data are used when a researcher is trying to quantify a problem, or address the "what" or "how many" aspects of a research question. It is data that can either be counted or compared on a numeric scale. For example, it could be the number of first year students at a University, or the ratings on a scale of 1-4 of the quality of food served at a restaurant. This data are usually gathered using instruments, such as a questionnaire which includes a ratings scale or a thermometer to collect weather data. Statistical analysis software, such as SPSS, is often used to analyze quantitative data.
  • Qualitative data: On the other hand, qualitative data give us information about the qualities of things. They are observed phenomenon, not measured, and so we generally label them with names. Qualitative data are also known as Categorical data. Qualitative data describes qualities or characteristics. It is collected using questionnaires, interviews, or observation, and frequently appears in narrative form. For example, it could be notes taken during a focus group on the quality of the food at a restaurant, or responses from an open-ended questionnaire. Qualitative data may be difficult to precisely measure and analyze. The data may be in the form of descriptive words that can be examined for patterns or meaning, sometimes through the use of coding. Coding allows the researcher to categorize qualitative data to identify themes that correspond with the research questions and to perform quantitative analysis.
  1. Definition - What is the Meaning of Data? Webopedia
  2. Data is more than just data University of Minnesota
  3. What is Computer Data? Techterms
  4. What Are Quantitative and Qualitative Data Types in Statistics? [https://www.chi2innovations.com/blog/discover-data-blog-series/data-types-101/ Chi Squared Innovations