What is meant by grouped data and ungrouped data?
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Data can be presented as simply a list of numbers or descriptions, or it can be organized into groups. In this lesson, you'll learn how to tell the difference between grouped and ungrouped data and how to turn ungrouped data into grouped data.
What Is Data?
Suppose you decided to record the temperature outside your house every day for a month. Is this data? What if you asked each of your friends what their favorite ice cream flavor was and then wrote down their answers? Would that information be data? Both of these would give you data. In fact, the word data is used to refer to any kind of information that you collect and record. It can include words, numbers, measurements, and more.
Data can be quantitative or qualitative. Quantitative data is numerical, so your record of temperatures would be quantitative data. Qualitative data records a description of something in words, like your friends' favorite ice cream flavors.
Once you've collected data, what can you do with it? The first step is to organize it. To do this, you need to know how to create grouped data from ungrouped data.
Ungrouped Data
When conducting any kind of experiment, you first need to collect the data. Initially, this data will be a list of numbers or other characteristics that will not be organized in any way. This is called raw data, or ungrouped data because it has not been sorted into any groups or categories.
For example, imagine you're teaching a statistics course and you want to analyze the test scores of your students. You would first need to gather the scores, which initially would be ungrouped and not organized in any way.
Grouped Data
Unlike ungrouped data, grouped data has been organized into several groups. To create grouped data, the raw data is sorted into groups, and a table showing how many data points occur in each group is created.
Let's look at those test scores again and think about how they could be grouped. There are many ways to group this data. For example, you could record how many students scored in each 20-point range. Alternatively, you could separate the scores by letter grade. If 90-100 is an A, 80-89 is a B, 70-79 is a C, 60-69 is a D, and 0-59 is an F, it might make sense to group the raw data into these five groups. This would change the frequency distribution a lot, even though the ungrouped data remained the same.
What Is Data?
Suppose you decided to record the temperature outside your house every day for a month. Is this data? What if you asked each of your friends what their favorite ice cream flavor was and then wrote down their answers? Would that information be data? Both of these would give you data. In fact, the word data is used to refer to any kind of information that you collect and record. It can include words, numbers, measurements, and more.
Data can be quantitative or qualitative. Quantitative data is numerical, so your record of temperatures would be quantitative data. Qualitative data records a description of something in words, like your friends' favorite ice cream flavors.
Once you've collected data, what can you do with it? The first step is to organize it. To do this, you need to know how to create grouped data from ungrouped data.
Ungrouped Data
When conducting any kind of experiment, you first need to collect the data. Initially, this data will be a list of numbers or other characteristics that will not be organized in any way. This is called raw data, or ungrouped data because it has not been sorted into any groups or categories.
For example, imagine you're teaching a statistics course and you want to analyze the test scores of your students. You would first need to gather the scores, which initially would be ungrouped and not organized in any way.
Grouped Data
Unlike ungrouped data, grouped data has been organized into several groups. To create grouped data, the raw data is sorted into groups, and a table showing how many data points occur in each group is created.
Let's look at those test scores again and think about how they could be grouped. There are many ways to group this data. For example, you could record how many students scored in each 20-point range. Alternatively, you could separate the scores by letter grade. If 90-100 is an A, 80-89 is a B, 70-79 is a C, 60-69 is a D, and 0-59 is an F, it might make sense to group the raw data into these five groups. This would change the frequency distribution a lot, even though the ungrouped data remained the same.
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Data is often described as ungrouped or grouped. Ungrouped data is data given as indi- vidual data points. Grouped data is data given in intervals. Ungrouped data without a frequency distribution.
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