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Video: Difference Between Grouped and Ungrouped Data
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.
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Percentile Rank in Statistics: Definition & Formula
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Difference Between Grouped and Ungrouped Data
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0:04 What Is Data?
1:04 Ungrouped Data
1:40 Grouped Data
2:36 Grouping of NonNumerical Data
3:19 Lesson Summary
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Betsy Chesnutt
Betsy teaches college physics, biology, and engineering and has a Ph.D. in Biomedical Engineering
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 20point range. Alternatively, you could separate the scores by letter grade. If 90100 is an A, 8089 is a B, 7079 is a C, 6069 is a D, and 059 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.
Grouping of NonNumerical Data
Many types of data, like the test score data, are numerical. However, this is certainly not the only type of data you can group. If you owned a clothing store and wanted to keep track of how many of each color shirt you’d sold, you would collect data on each sale. The raw data would be qualitative and would look something like this:
This raw, ungrouped data can be grouped to create numerical data, which can be analyzed using statistics. To group the data, you would make a group for each color of shirt and then count the total number of shirts sold in each color. This grouped data could then be organized in a chart.
Lesson Summary
Data is any kind of collected and recorded information. It can be numerical (quantitative data) or descriptive (qualitative data). Data is first collected as ungrouped data, which is just a list of the data that isn’t organized in any way. To create grouped data, you need to separate the ungrouped data into different categories and then create a table that shows the relative frequency that each category occurs in the raw data.
Learning Outcomes
After watching the video, you should be prepared to:
 Distinguish between quantitative data and qualitative data
 Explain what ungrouped data is
 Describe what grouped data is
 Recall how nonnumerical data is grouped
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Ch 1. TECEP Principles of Statistics:…
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TECEP Principles of Statistics: Measurement
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Frequency & Relative Frequency Tables: Definition & Examples
4:48
Cumulative Frequency Tables: Definition, Uses & Examples
5:17
Difference Between Grouped and Ungrouped Data
3:58
3:32
Next Lesson
Percentile Rank in Statistics: Definition & Formula
Understanding Bar Graphs and Pie Charts
9:36
What is an Area Chart? – Definition & Examples
Creating & Interpreting Frequency Polygons: Process & Examples
5:48
Skewed Distribution: Examples & Definition
5:09
Scatterplots and Line Graphs: Definitions and Uses
7:17
What is a TwoWay Table?
3:40
Creating & Interpreting Histograms: Process & Examples
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TECEP Principles of Statistics: Summarizing Data
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TECEP Principles of Statistics: Central Tendency & Variability
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TECEP Principles of Statistics: Probability
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TECEP Principles of Statistics: Probability Distributions
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TECEP Principles of Statistics: Correlation
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TECEP Principles of Statistics: Regression
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TECEP Principles of Statistics: Population, Samples & Probability
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TECEP Principles of Statistics: Hypothesis Testing & Estimation
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TECEP Principles of Statistics: tTests
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TECEP Principles of Statistics: ANOVA
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Difference between grouped and ungrouped data
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Difference between grouped and ungrouped data
 1.
Course Title: Business Statistics
BBA (Hons)
2nd
Semester
Lecture No:2
Course Instructor: Atiq ur Rehman Shah
Lecturer, Federal Urdu University of Arts,
Science & Technology, Islamabad
+923455271959
[email protected] 2.
Learning Objectives
• Recognize the difference between
grouped and ungrouped data
• Construct a frequency distribution
• Data Range3.
Ungrouped Versus Grouped
Data
• Ungrouped data
• have not been summarized in any way
• are also called raw data
• Grouped data
• have been organized into a frequency
distribution4.
Example of Ungrouped Data
42
30
53
50
52
30
55
49
61
74
26
58
40
40
28
36
30
33
31
37
32
37
30
32
23
32
58
43
30
29
34
50
47
31
35
26
64
46
40
43
57
30
49
40
25
50
52
32
60
54
Ages of a Sample of
Managers from
Urban Child Care
Centers in the
United States5.
Frequency Distribution of
Child Care Manager’s Ages
Class Interval Frequency
20under 30 6
30under 40 18
40under 50 11
50under 60 11
60under 70 3
70under 80 16.
Data Range
42
30
53
50
52
30
55
49
61
74
26
58
40
40
28
36
30
33
31
37
32
37
30
32
23
32
58
43
30
29
34
50
47
31
35
26
64
46
40
43
57
30
49
40
25
50
52
32
60
54
Smallest
Largest
Range = Largest – Smallest
= 74 – 23
= 517.
Data Range
42
30
53
50
52
30
55
49
61
74
26
58
40
40
28
36
30
33
31
37
32
37
30
32
23
32
58
43
30
29
34
50
47
31
35
26
64
46
40
43
57
30
49
40
25
50
52
32
60
54
Smallest
Largest
Range = Largest – Smallest
= 74 – 23
= 51
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Difference between grouped and ungrouped data?
Business Statistics (Short Q & A) I.Com Part 2
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Difference between grouped and ungrouped data?
GROUPED DATA is when there are a large number of possible outcomes; we will usually need to group the data.
E.g. the ages of 200 people entering a park on a Saturday afternoon. The ages have been grouped into the classes 09, 1019, 2029, etc.
UNGROUPED DATA is the opposite of grouped data with only one possible answer. E.g. the ages of 200 people entering a park on a Saturday afternoon. The ages are: 27, 8, 10, and 49 etc.
State the formula of arithmetic mean
The arithmetic mean is the average of a series of numbers.
How It Works/Example:
The formula for calculating the arithmetic mean is:
Arithmetic mean = (X1 + X2 + X3 + … +XN) / N
Source: http://www.investinganswers.com/financialdictionary/ratioanalysis/arithmeticmean2546
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