unit-2 organizing and displaying data
TRANSCRIPT
Unit-2Organizing and displaying data
RajaBScN, DCHN, RN
Acknowledgement: Sumaira Inam
Tuesday, August 23, 2016
Objectives:After this lecture you will be able to;
“Understand how to Organize and Display Data”
1.For Quantitative Discrete2.For Quantitative Continuous Variables.3. Qualitative Variables.4. As tables, frequency distributions, bar graphs,histograms, frequency polygon; cumulative frequency.
After this lecture you will be able to;
“Understand how to Organize and Display Data”
1.For Quantitative Discrete2.For Quantitative Continuous Variables.3. Qualitative Variables.4. As tables, frequency distributions, bar graphs,histograms, frequency polygon; cumulative frequency.
What is Statistics?Statistics refers to Numerical Facts .
Example : Statistics of Births, Crimes, Accidents, Age,Chronic disease rates etc.
Most people use the word Data instead.
“Statistics is a mathematical science that is concerned
with the collection, analysis, interpretation or
explanation, and presentation of data.”
Statistics refers to Numerical Facts .
Example : Statistics of Births, Crimes, Accidents, Age,Chronic disease rates etc.
Most people use the word Data instead.
“Statistics is a mathematical science that is concerned
with the collection, analysis, interpretation or
explanation, and presentation of data.”
Once you have collected data(raw information), you mustdetermine the best strategy for organizing and analyzing it.
The right analysis approach will help to
understand and interpret findings.
Organizing & Displaying Data
Once you have collected data(raw information), you mustdetermine the best strategy for organizing and analyzing it.
The right analysis approach will help to
understand and interpret findings.
Cont…
II.Graphical Presentation Bar Graphs Pie Charts Frequency Polygon
I. Frequency Distribution
II.Graphical Presentation Bar Graphs Pie Charts Frequency Polygon
For Quantitative Discrete and Qualitative VariablesSingle Value Frequency Table, Cumulative andRelative Frequency tableBar DiagramPie Chart
For Quantitative Continuous Variables
For Quantitative Discrete and Qualitative VariablesSingle Value Frequency Table, Cumulative andRelative Frequency tableBar DiagramPie Chart
For Quantitative Continuous Variables
Frequency Table, Cumulative and Relative FrequencytableHistogramPie ChartFrequency Polygon
The organization of a set of data in a table, showing the
distribution of the data into classes or groups together with
the number of observations in each class or group is called
Frequency Distribution.
A tablelisting all theobserved values and the number oftheir occurrence.
Frequency Table
The organization of a set of data in a table, showing the
distribution of the data into classes or groups together with
the number of observations in each class or group is called
Frequency Distribution.
Example 2
Now suppose we need to construct a similar frequencytable for the age of patients with Heart related problemsin a clinic. The following data has been collected basedon a random sample of n=30 patients who went to theemergency room of the clinic for heart related problems.
• The measurements are:42, 38, 51, 53, 40, 68, 62, 36, 32, 45, 51, 67, 53, 59, 47,63, 52, 64, 61, 43, 56, 58, 66, 54, 56, 52, 40, 55, 71, 69.
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Now suppose we need to construct a similar frequencytable for the age of patients with Heart related problemsin a clinic. The following data has been collected basedon a random sample of n=30 patients who went to theemergency room of the clinic for heart related problems.
• The measurements are:42, 38, 51, 53, 40, 68, 62, 36, 32, 45, 51, 67, 53, 59, 47,63, 52, 64, 61, 43, 56, 58, 66, 54, 56, 52, 40, 55, 71, 69.
Steps• Arrange the data in ascending order:
32, 36, 38, 40, 40, 42, 43, 45, 47, 51, 51, 52, 52, 53, 53, 54, 55, 56,56, 58, 59, 61, 62, 63, 64, 66, 67, 68, 69, 71.
• Find range of the data, Rang =Max –MinRang =71- 32 =39
• Decide the number of classesThe number of classes or intervals depends on the number ofobservations but in general should range from 5 to 15.
• Calculate width of classesWidth = Range / # of classesWidth = 39/8=4.8 ≈ 5
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• Arrange the data in ascending order:
32, 36, 38, 40, 40, 42, 43, 45, 47, 51, 51, 52, 52, 53, 53, 54, 55, 56,56, 58, 59, 61, 62, 63, 64, 66, 67, 68, 69, 71.
• Find range of the data, Rang =Max –MinRang =71- 32 =39
• Decide the number of classesThe number of classes or intervals depends on the number ofobservations but in general should range from 5 to 15.
• Calculate width of classesWidth = Range / # of classesWidth = 39/8=4.8 ≈ 5
Frequency tableNo of children Frequency Relative Frequency Cumulative
FrequencyCumulative
RelativeFrequency
32-37′ 2 2/30=0.067 2 2/30=0.067
37-42′ 3 3/30=0.100 5 5/30=0.167
42-47′ 3 3/30=0.100 8 8/30=0.267
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42-47′ 3 3/30=0.100 8 8/30=0.267
47-52′ 3 3/30=0.100 11 11/30=0.367
52-57′ 8 8/30=0.267 19 19/30=0.633
57-62′ 3 3/30=0.100 22 22/30=0.733
62-67′ 4 4/30=0.134 26 26/30=0.867
67-72′ 4 4/30=0.134 30 30/30=1.00
Total 30 1
Assignment
“To produce a meaningful pattern for the overalldistribution of data from which conclusions can bedrawn.”
Frequency statistics are the main descriptive statistics
used with discrete variables.
Purpose of Frequency Table
“To produce a meaningful pattern for the overalldistribution of data from which conclusions can bedrawn.”
Frequency statistics are the main descriptive statistics
used with discrete variables.
Graphical Representation of Data
• The second way of displaying data is by use of graphs. It givesthe user a nice overview of the essential features of the data.
• Graphs are Geometrical designs.• Convey information at a glance.
Graphs:• Self explanatory• Must have title• Simple & clean
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• The second way of displaying data is by use of graphs. It givesthe user a nice overview of the essential features of the data.
• Graphs are Geometrical designs.• Convey information at a glance.
Graphs:• Self explanatory• Must have title• Simple & clean
Histograms
• Histogram is a most common graphical presentation.
• It consists of a horizontal axis, which shows the frequency (or
relative frequency) of observation.
• A Histogram is a graphical representation of a frequency
distribution for continuous data.
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• Histogram is a most common graphical presentation.
• It consists of a horizontal axis, which shows the frequency (or
relative frequency) of observation.
• A Histogram is a graphical representation of a frequency
distribution for continuous data.
Histogram
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Scatter plots
• To know the relationships between two
quantitative variables.
• A scatter diagram plots the value of one variable
against the value of another variable.
• It can be used to reveal whether a relationship
exists and the type of relationship that exists.
• To know the relationships between two
quantitative variables.
• A scatter diagram plots the value of one variable
against the value of another variable.
• It can be used to reveal whether a relationship
exists and the type of relationship that exists.
Scatter plots
Frequency polygons
• Another commonly used graph is the frequency polygon.
• It uses the same axes as the histogram.
• Frequency polygons are superior to histograms in providing
means of comparing two frequency distributions (shapes).
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• Another commonly used graph is the frequency polygon.
• It uses the same axes as the histogram.
• Frequency polygons are superior to histograms in providing
means of comparing two frequency distributions (shapes).
Frequency polygons
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Bar chart• A simple bar diagram is constructed for an immediate
comparison.
• Bar Charts are used for graphical representation of Categoricaldata - Nominal and Ordinal data.
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Multiple Bar chart• Multiple bar diagrams are constructed to represent
two or more than two variables for the purpose ofcomparison.
• Multiple bar diagrams are constructed to representtwo or more than two variables for the purpose ofcomparison.
Pie chart
• It is also known as the sector Diagram, is an effective way of
displaying the percentage breakdown of data by category.
• The Pie Chart is an alternative to the Bar Chart for Nominal and
Ordinal data.
• The proportion of the Pie represents the category’s percentage in
the population or sample.
• Must identify slices.
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• It is also known as the sector Diagram, is an effective way of
displaying the percentage breakdown of data by category.
• The Pie Chart is an alternative to the Bar Chart for Nominal and
Ordinal data.
• The proportion of the Pie represents the category’s percentage in
the population or sample.
• Must identify slices.
Pie chart
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Reference:
• Kuzma. J. W, Bohnenblust. S. E. Basic Statistics for thehealth Sciences ( 5th Edition).