Unit-2 Organizing and displaying data

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).