Choosing a method of data display - Revision history

Bosmana fem: /* General recommendation */

2023-04-14T05:33:32Z

General recommendation

← Older revision		Revision as of 05:33, 14 April 2023
Line 8:		Line 8:
	If you decide that a graph is the best way to present your information, then no matter what type of graph you use, you need to keep in mind the following 10 tips:<Ref>Statistics Canada, Statistics: Power from data! - Summary</ref>		If you decide that a graph is the best way to present your information, then no matter what type of graph you use, you need to keep in mind the following 10 tips:<Ref>Statistics Canada, Statistics: Power from data! - Summary</ref>

	* convey an important message		# convey an important message
	* decide on a clear purpose		# decide on a clear purpose
	* draw attention to the message, not the source		# draw attention to the message, not the source
	* experiment with various options and graph styles		# experiment with various options and graph styles
	* use simple design for complex data		# use simple design for complex data
	* make the data 'speak'		# make the data 'speak'
	* adapt graph presentation to suit the target audience		# adapt graph presentation to suit the target audience
	* ensure that the visual perception process is easy and accurate		# ensure that the visual perception process is easy and accurate
	* avoid distortion and ambiguity		# avoid distortion and ambiguity
	* optimize design and integrate style with text and tables		# optimize design and integrate style with text and tables
	* describing one variable		# describing one variable
	The first step is to describe one variable, which is crucial before ~~one starts to compare~~ two or more variables. The table below summarises the most common presentation formats for the different types of variables, from the "simplest" to the more "complex".		The first step is to describe one variable, which is crucial before comparing two or more variables. The table below summarises the most common presentation formats for the different types of variables, from the "simplest" to the more "complex".

	{\| class="wikitable"		{\| class="wikitable"
Line 55:		Line 55:
	\| style="font-weight:bold; color:#06D;" \| Histogram (also cumulative), Frequency polygon, Box-and-whisker plot, Violin plot, One-way scatter plot		\| style="font-weight:bold; color:#06D;" \| Histogram (also cumulative), Frequency polygon, Box-and-whisker plot, Violin plot, One-way scatter plot
	\|}		\|}

	==Describing two variables together==		==Describing two variables together==
	There are potentially 5x5 = 25 combinations of the types of variables mentioned in the table above; there are many potential graphs and tables to describe these. The important thing is that you understand what you want to show in those tables or graphs. For describing two variables (X and Y) together, the strategy is basically the following:		There are potentially 5x5 = 25 combinations of the types of variables mentioned in the table above; there are many potential graphs and tables to describe these. The important thing is that you understand what you want to show in those tables or graphs. For describing two variables (X and Y) together, the strategy is basically the following:

Bosmana fem at 05:32, 14 April 2023

2023-04-14T05:32:54Z

← Older revision		Revision as of 05:32, 14 April 2023
Line 1:		Line 1:
	General recommendation		==General recommendation==
	Before constructing any display of epidemiologic data, it is important to ~~first~~ determine the point to be conveyed. Are you highlighting a change from past patterns in the data? Are you showing a difference in incidence by geographic area or by some predetermined risk factor? What is the interpretation you want he reader to reach? Your answer to these questions will help to determine the choice of display <Ref>U.S. Dept. of Health and Human Services - Centers for Disease Control and Prevention (CDC). Self-study course 3030-G. Principles of epidemiology. An introduction to applied epidemiology and biostatistics. 2nd ed.</ref>.		Before constructing any display of epidemiologic data, it is important first to determine the point to be conveyed. Are you highlighting a change from past patterns in the data? Are you showing a difference in incidence by geographic area or by some predetermined risk factor? What is the interpretation you want the reader to reach? Your answer to these questions will help to determine the choice of display <Ref>U.S. Dept. of Health and Human Services - Centers for Disease Control and Prevention (CDC). Self-study course 3030-G. Principles of epidemiology. An introduction to applied epidemiology and biostatistics. 2nd ed.</ref>.

	As a general recommendation, use a table for precise numbers, for large amounts of numbers, and if there is a great range between the largest and smallest figures. Use a graph ~~for showing~~ trends and relationships, displaying changes over time, and ~~for~~ explaining a point vividly. Use ~~either~~ a table or a graph for comparisons, and ~~for~~ showing parts of a whole <Ref>Bigwood S, Spore M. Presenting numbers, tables and charts. Oxford University Press, New York, 2003 p. 84</ref>.		As a general recommendation, use a table for precise numbers, for large amounts of numbers, and if there is a great range between the largest and smallest figures. Use a graph to show trends and relationships, displaying changes over time and explaining a point vividly. Use a table or a graph for comparisons and showing parts of a whole <Ref>Bigwood S, Spore M. Presenting numbers, tables and charts. Oxford University Press, New York, 2003 p. 84</ref>.

	~~Often the~~ choice between presenting data in a table or graph is arbitrary as both will work. ~~In general~~ when presenting lots of data e.g. in an annual report it is best to vary how the data is presented ~~by making use of both~~ tables and graphs. A graphical presentation of data ~~has the advantage of enabling~~ a person to visualise a relationship between data i.e. proportions in groups. There is also a subjective nature to this as some individuals find it easier to interpret tables while others find a visual representation ~~more easy~~ to interpret.		The choice between presenting data in a table or graph is often arbitrary as both will work. Generally, when presenting lots of data, e.g. in an annual report, it is best to vary how the data is presented using tables and graphs. A graphical presentation of data can enable a person to visualise a relationship between data, i.e. proportions in groups. There is also a subjective nature to this as some individuals find it easier to interpret tables while others find a visual representation easier to interpret.

	If you decide that a graph is the best way to present your information, then no matter what type of graph you use, you need to keep in mind the following 10 tips <Ref>Statistics Canada, Statistics: Power from data! - Summary</ref>:		If you decide that a graph is the best way to present your information, then no matter what type of graph you use, you need to keep in mind the following 10 tips:<Ref>Statistics Canada, Statistics: Power from data! - Summary</ref>

	* convey an important message		* convey an important message
Line 19:		Line 19:
	* optimize design and integrate style with text and tables		* optimize design and integrate style with text and tables
	* describing one variable		* describing one variable
	The first step is to describe one variable which is crucial before one starts to compare two or more variables. The table below summarises the most common presentation formats for the different types of variables, from the "simplest" to the more "complex".		The first step is to describe one variable, which is crucial before one starts to compare two or more variables. The table below summarises the most common presentation formats for the different types of variables, from the "simplest" to the more "complex".

	{\| class="wikitable"		{\| class="wikitable"
Line 55:		Line 55:
	\| style="font-weight:bold; color:#06D;" \| Histogram (also cumulative), Frequency polygon, Box-and-whisker plot, Violin plot, One-way scatter plot		\| style="font-weight:bold; color:#06D;" \| Histogram (also cumulative), Frequency polygon, Box-and-whisker plot, Violin plot, One-way scatter plot
	\|}		\|}
	Describing two variables together		==Describing two variables together==
	There are potentially 5x5 = 25 combinations of the types of variables mentioned in the table above; there are many potential graphs and tables to describe these. The important thing is that you understand what you ~~wants~~ to show in those tables or graphs. For describing two variables (X and Y) together the strategy is basically the following:		There are potentially 5x5 = 25 combinations of the types of variables mentioned in the table above; there are many potential graphs and tables to describe these. The important thing is that you understand what you want to show in those tables or graphs. For describing two variables (X and Y) together, the strategy is basically the following:

	First, consider one variable as the "outcome" (Y) and the other as the "factor" (X), i.e. explanatory variable. Then describe ~~the~~ outcome (Y) ~~in each group~~ that you can make with the factor (X). Remember that the outcome will be described according to its nature as explained above (univariate description).		First, consider one variable as the "outcome" (Y) and the other as the "factor" (X), i.e. explanatory variable. Then describe each group's outcome (Y) that you can make with the factor (X). Remember that the outcome will be described according to its nature as explained above (univariate description).

	Below you find a simple summary of describing two variables together.		Below you will find a simple summary of describing two variables together.

	{\| class="wikitable" style="color:#222;"		{\| class="wikitable" style="color:#222;"
Line 85:		Line 85:
	\|}		\|}

	There are typical table formats for presenting results of cohort and case-control studies.		There are typical table formats for presenting the results of cohort and case-control studies.

	Time series		==Time series==
	Time series is a special case of describing two variables where the factor (X) variable is always the "time". Selecting a method of displaying time series data is based on certain conditions <Ref>U.S. Dept. of Health and Human Services - Centers for Disease Control and Prevention (CDC). Self-study course 3030-G. Principles of epidemiology. An introduction to applied epidemiology and biostatistics. 2nd ed. p. 264 </ref>.		Time series is a special case of describing two variables where the factor (X) variable is always the "time". Selecting a method of displaying time series data is based on certain conditions <Ref>U.S. Dept. of Health and Human Services - Centers for Disease Control and Prevention (CDC). Self-study course 3030-G. Principles of epidemiology. An introduction to applied epidemiology and biostatistics. 2nd ed. p. 264 </ref>.

Bosmana fem: /* FEM PAGE CONTRIBUTORS */

2023-04-10T21:18:21Z

FEM PAGE CONTRIBUTORS

← Older revision		Revision as of 21:18, 10 April 2023
Line 123:		Line 123:


	==FEM PAGE CONTRIBUTORS==		<div style="display: inline-block; width: 25%; vertical-align: top; border: 1px solid #000; background-color: #d7effc; padding: 10px; margin: 5px;">
			'''FEM PAGE CONTRIBUTORS 2007'''
	;Editor		;Editor
	:Agnes Hajdu		:Agnes Hajdu
Line 132:		Line 133:
	:Lisa Lazareck		:Lisa Lazareck
	:Agnes Hajdu		:Agnes Hajdu
			</div>

	[[Category:Informing Action / Improving Knowledge]]		[[Category:Informing Action / Improving Knowledge]]

Bosmana fem at 07:28, 29 March 2023

2023-03-29T07:28:57Z

← Older revision		Revision as of 07:28, 29 March 2023
Line 62:		Line 62:
	Below you find a simple summary of describing two variables together.		Below you find a simple summary of describing two variables together.

	{\| class="wikitable"		{\| class="wikitable" style="color:#222;"
	\|- style="font-weight:bold; text-align:center~~; vertical-align:bottom~~;"		\|- style="font-weight:bold; text-align:center;"
	! colspan="4" \| Describing TWO variables together		! colspan="4" \| Describing TWO variables together
	\|- style="font-weight:bold; vertical-align:bottom;"		\|- style="font-weight:bold; vertical-align:bottom;"
	\| Variable		\| Variable
Line 70:		Line 70:
	\| Table		\| Table
	\| Graph		\| Graph
	\|-		\|- style="vertical-align:bottom;"
	\| style="vertical-align:bottom;" \| Two categorical variables		\| Two categorical variables
	\| style="vertical-align:~~bottom~~;" \| Identify relationships, patterns in the data		\| rowspan="3" style="text-align:center; vertical-align:middle;" \| Identify relationships, patterns in the data
	\| style="text-decoration:underline; color:#0563C1;" \| Contingency table		\| style="text-decoration:underline; color:#0563C1;" \| Contingency table
	\| style="~~vertical-align:bottom;~~ font-weight:bold; color:#~~06D~~;" ~~\| [[Bar_graphs#Grouped_bar_graphs~~\|Grouped bar graph]], ~~[[Bar_graphs#Stacked_bar_graphs\|~~Stacked bar graph]], ~~[[Bar_graphs#Component_bar_graphs\|~~Component bar graph]], Mosaic plot		\| style="font-weight:bold; color:#0645AD;" \| Grouped bar graph, Stacked bar graph, Component bar graph, Mosaic plot
	\|-		\|- style="vertical-align:bottom;"
	\| style="vertical-align:bottom;" \| Two numerical variables		\| Two numerical variables
	\| style="text-decoration:underline; color:#0563C1;" \| Contingency table (group frequencies)		\| style="text-decoration:underline; color:#0563C1;" \| Contingency table (group frequencies)
	\| style="~~vertical-align:bottom;~~ font-weight:bold; color:#06D;" \| Line graph (also cumulative), Scatter plot (with or without regression line)		\| style="font-weight:bold; color:#06D;" \| Line graph (also cumulative), Scatter plot (with or without regression line)
	\| style="vertical-align:bottom;" \|		\|- style="vertical-align:bottom;"
	\|-		\| One categorical and one numerical variable
	~~\| style="vertical-align:bottom;"~~ \| One categorical and one numerical variable		\| style="text-decoration:underline; color:#0563C1;" \| Contingency table, Table of descriptive statistics (mean, median, mode, etc)
	\| style="text-decoration:underline; color:#0563C1;" \| Contingency table, Table of descriptive statistics (mean, median, mode, etc)		\| style="font-weight:bold; color:#06D;" \| Scatter plot, Box-and-whisker plot, Bar graph (showing mean or median with ± standard deviation)
	\| style="~~vertical-align:bottom;~~ font-weight:bold; color:#06D;" \| Scatter plot, Box-and-whisker plot, Bar graph (showing mean or median with ± standard deviation)
	~~\| style="vertical-align:bottom;" \|~~
	\|}		\|}

Bosmana fem at 07:25, 29 March 2023

2023-03-29T07:25:31Z

Bosmana fem at 07:11, 29 March 2023

2023-03-29T07:11:29Z

← Older revision		Revision as of 07:11, 29 March 2023
Line 42:		Line 42:
	\| Ordinal (categorical (ordered)		\| Ordinal (categorical (ordered)
	\| Describe with proportions		\| Describe with proportions
	\| style="font-weight:bold; color:#06D;" \| [[Tables#Frequency_distribution_table\|Frequency distribution table]] (also cumulative)		\| style="font-weight:bold; color:#06D;" \| [[Tables#Frequency_distribution_table\|Frequency distribution table]] (also [[Tables#Cumulative_frequency_distribution_table\|cumulative]])
	\| style="font-weight:bold; color:#06D;" \| Bar graph(also cumulative), Pie graph		\| style="font-weight:bold; color:#06D;" \| Bar graph(also cumulative), Pie graph
	\|- style="vertical-align:bottom;"		\|- style="vertical-align:bottom;"
	\| Numerical discrete		\| Numerical discrete
	\| Describe with proportions, means and standard deviation		\| Describe with proportions, means and standard deviation
	\| style="font-weight:bold; color:#06D;" \| [[Tables#Frequency_distribution_table\|Frequency distribution table]] (also cumulative), Table of descriptive statistics		\| style="font-weight:bold; color:#06D;" \| [[Tables#Frequency_distribution_table\|Frequency distribution table]] (also [[Tables#Cumulative_frequency_distribution_table\|cumulative]]), Table of descriptive statistics
	\| style="font-weight:bold; color:#06D;" \| Bar graph (also cumulative), Histogram (if large number of values)		\| style="font-weight:bold; color:#06D;" \| Bar graph (also cumulative), Histogram (if large number of values)
	\|- style="vertical-align:bottom;"		\|- style="vertical-align:bottom;"

Bosmana fem at 07:09, 29 March 2023

2023-03-29T07:09:43Z

Bosmana fem at 07:07, 29 March 2023

2023-03-29T07:07:37Z

← Older revision		Revision as of 07:07, 29 March 2023
Line 32:		Line 32:
	\| style="vertical-align:bottom;" \| Binary / dichotomous		\| style="vertical-align:bottom;" \| Binary / dichotomous
	\| style="vertical-align:bottom;" \| Describe with proportions		\| style="vertical-align:bottom;" \| Describe with proportions
	\| style="text-decoration:underline; color:#0563C1;" \| Frequency distribution table		\| style="text-decoration:underline; color:#0563C1;" \| [[Tables#Frequency_distribution_table\|Frequency distribution table]]
	\| style="vertical-align:bottom; font-weight:bold; color:#06D;" \| Bar graph, Pie graph		\| style="vertical-align:bottom; font-weight:bold; color:#06D;" \| Bar graph, Pie graph
	\|-		\|-

Bosmana fem at 06:43, 29 March 2023

2023-03-29T06:43:17Z

Show changes

Bosmana fem: Created page with " Category:Informing Action / Improving Knowledge"

2023-03-22T22:07:56Z

Created page with " Category:Informing Action / Improving Knowledge"

New page

[[Category:Informing Action / Improving Knowledge]]

← Older revision		Revision as of 07:07, 29 March 2023
Line 32:		Line 32:
	\| style="vertical-align:bottom;" \| Binary / dichotomous		\| style="vertical-align:bottom;" \| Binary / dichotomous
	\| style="vertical-align:bottom;" \| Describe with proportions		\| style="vertical-align:bottom;" \| Describe with proportions
	\| style="text-decoration:underline; color:#0563C1;" \| Frequency distribution table		\| style="text-decoration:underline; color:#0563C1;" \| [[Tables#Frequency_distribution_table\|Frequency distribution table]]
	\| style="vertical-align:bottom; font-weight:bold; color:#06D;" \| Bar graph, Pie graph		\| style="vertical-align:bottom; font-weight:bold; color:#06D;" \| Bar graph, Pie graph
	\|-		\|-

← Older revision		Revision as of 07:25, 29 March 2023
Line 33:		Line 33:
	\| style="vertical-align:bottom;" \| Describe with proportions		\| style="vertical-align:bottom;" \| Describe with proportions
	\| style="text-decoration:underline; color:#0563C1;" \| [[Tables#Frequency_distribution_table\|Frequency distribution table]]		\| style="text-decoration:underline; color:#0563C1;" \| [[Tables#Frequency_distribution_table\|Frequency distribution table]]
	\| style="vertical-align:bottom; font-weight:bold; color:#06D;" \| Bar graph, Pie graph		\| style="vertical-align:bottom; font-weight:bold; color:#06D;" \| [[Bar graphs\|Bar graph]], Pie graph
	\|-		\|-
	\| style="vertical-align:bottom;" \| Nominal (categorical not ordered)		\| style="vertical-align:bottom;" \| Nominal (categorical not ordered)
	\| style="vertical-align:bottom;" \| Describe with proportions		\| style="vertical-align:bottom;" \| Describe with proportions
	\| style="text-decoration:underline; color:#0563C1;" \| [[Tables#Frequency_distribution_table\|Frequency distribution table]]		\| style="text-decoration:underline; color:#0563C1;" \| [[Tables#Frequency_distribution_table\|Frequency distribution table]]
	\| style="vertical-align:bottom; font-weight:bold; color:#06D;" \| Bar graph, Pie graph		\| style="vertical-align:bottom; font-weight:bold; color:#06D;" \| [[Bar graphs\|Bar graph]], Pie graph
	\|- style="vertical-align:bottom;"		\|- style="vertical-align:bottom;"
	\| Ordinal (categorical (ordered)		\| Ordinal (categorical (ordered)
	\| Describe with proportions		\| Describe with proportions
	\| style="font-weight:bold; color:#06D;" \| [[Tables#Frequency_distribution_table\|Frequency distribution table]] (also [[Tables#Cumulative_frequency_distribution_table\|cumulative]])		\| style="font-weight:bold; color:#06D;" \| [[Tables#Frequency_distribution_table\|Frequency distribution table]] (also [[Tables#Cumulative_frequency_distribution_table\|cumulative]])
	\| style="font-weight:bold; color:#06D;" \| Bar graph(also cumulative), Pie graph		\| style="font-weight:bold; color:#06D;" \| [[Bar graphs\|Bar graph]](also cumulative), Pie graph
	\|- style="vertical-align:bottom;"		\|- style="vertical-align:bottom;"
	\| Numerical discrete		\| Numerical discrete
	\| Describe with proportions, means and standard deviation		\| Describe with proportions, means and standard deviation
	\| style="font-weight:bold; color:#06D;" \| [[Tables#Frequency_distribution_table\|Frequency distribution table]] (also [[Tables#Cumulative_frequency_distribution_table\|cumulative]]), Table of descriptive statistics		\| style="font-weight:bold; color:#06D;" \| [[Tables#Frequency_distribution_table\|Frequency distribution table]] (also [[Tables#Cumulative_frequency_distribution_table\|cumulative]]), Table of descriptive statistics
	\| style="font-weight:bold; color:#06D;" \| Bar graph (also cumulative), Histogram (if large number of values)		\| style="font-weight:bold; color:#06D;" \| [[Bar graphs\|Bar graph]](also cumulative), Histogram (if large number of values)
	\|- style="vertical-align:bottom;"		\|- style="vertical-align:bottom;"
	\| Numerical continuous		\| Numerical continuous
	\| Describe with means, medians, standard deviation, quartiles		\| Describe with means, medians, standard deviation, quartiles
	\| style="font-weight:bold; color:#06D;" \| [[Tables#Frequency_distribution_table\|Frequency distribution table]] (group frequencies or cumulative), Table of descriptive statistics		\| style="font-weight:bold; color:#06D;" \| [[Tables#Frequency_distribution_table\|Frequency distribution table]] (group frequencies or cumulative), Table of descriptive statistics
	\| style="font-weight:bold; color:#06D;" \| Histogram (also cumulative), Frequency polygon, Box-and-whisker plot, Violin plot, One-way scatter plot		\| style="font-weight:bold; color:#06D;" \| Histogram (also cumulative), Frequency polygon, Box-and-whisker plot, Violin plot, One-way scatter plot
	\|}		\|}
	Describing two variables together		Describing two variables together
Line 74:		Line 74:
	\| style="vertical-align:bottom;" \| Identify relationships, patterns in the data		\| style="vertical-align:bottom;" \| Identify relationships, patterns in the data
	\| style="text-decoration:underline; color:#0563C1;" \| Contingency table		\| style="text-decoration:underline; color:#0563C1;" \| Contingency table
	\| style="vertical-align:bottom; font-weight:bold; color:#06D;" \| Grouped bar graph, Stacked bar graph, Component bar graph, Mosaic plot		\| style="vertical-align:bottom; font-weight:bold; color:#06D;" \| [[Bar_graphs#Grouped_bar_graphs\|Grouped bar graph]], [[Bar_graphs#Stacked_bar_graphs\|Stacked bar graph]], [[Bar_graphs#Component_bar_graphs\|Component bar graph]], Mosaic plot
	\|-		\|-
	\| style="vertical-align:bottom;" \| Two numerical variables		\| style="vertical-align:bottom;" \| Two numerical variables
Line 83:		Line 83:
	\| style="vertical-align:bottom;" \| One categorical and one numerical variable		\| style="vertical-align:bottom;" \| One categorical and one numerical variable
	\| style="text-decoration:underline; color:#0563C1;" \| Contingency table, Table of descriptive statistics (mean, median, mode, etc)		\| style="text-decoration:underline; color:#0563C1;" \| Contingency table, Table of descriptive statistics (mean, median, mode, etc)
	\| style="vertical-align:bottom; font-weight:bold; color:#06D;" \| Scatter plot, Box-and-whisker plot, Bar graph (showing mean or median with ± standard deviation)		\| style="vertical-align:bottom; font-weight:bold; color:#06D;" \| Scatter plot, Box-and-whisker plot, Bar graph (showing mean or median with ± standard deviation)
	\| style="vertical-align:bottom;" \|		\| style="vertical-align:bottom;" \|
	\|}		\|}

← Older revision		Revision as of 07:09, 29 March 2023
Line 8:		Line 8:
	If you decide that a graph is the best way to present your information, then no matter what type of graph you use, you need to keep in mind the following 10 tips <Ref>Statistics Canada, Statistics: Power from data! - Summary</ref>:		If you decide that a graph is the best way to present your information, then no matter what type of graph you use, you need to keep in mind the following 10 tips <Ref>Statistics Canada, Statistics: Power from data! - Summary</ref>:

	convey an important message		* convey an important message
	decide on a clear purpose		* decide on a clear purpose
	draw attention to the message, not the source		* draw attention to the message, not the source
	experiment with various options and graph styles		* experiment with various options and graph styles
	use simple design for complex data		* use simple design for complex data
	make the data 'speak'		* make the data 'speak'
	adapt graph presentation to suit the target audience		* adapt graph presentation to suit the target audience
	ensure that the visual perception process is easy and accurate		* ensure that the visual perception process is easy and accurate
	avoid distortion and ambiguity		* avoid distortion and ambiguity
	optimize design and integrate style with text and tables		* optimize design and integrate style with text and tables
	~~Describing~~ one variable		* describing one variable
	The first step is to describe one variable which is crucial before one starts to compare two or more variables. The table below summarises the most common presentation formats for the different types of variables, from the "simplest" to the more "complex".		The first step is to describe one variable which is crucial before one starts to compare two or more variables. The table below summarises the most common presentation formats for the different types of variables, from the "simplest" to the more "complex".

Line 37:		Line 37:
	\| style="vertical-align:bottom;" \| Nominal (categorical not ordered)		\| style="vertical-align:bottom;" \| Nominal (categorical not ordered)
	\| style="vertical-align:bottom;" \| Describe with proportions		\| style="vertical-align:bottom;" \| Describe with proportions
	\| style="text-decoration:underline; color:#0563C1;" \| Frequency distribution table		\| style="text-decoration:underline; color:#0563C1;" \| [[Tables#Frequency_distribution_table\|Frequency distribution table]]
	\| style="vertical-align:bottom; font-weight:bold; color:#06D;" \| Bar graph, Pie graph		\| style="vertical-align:bottom; font-weight:bold; color:#06D;" \| Bar graph, Pie graph
	\|- style="vertical-align:bottom;"		\|- style="vertical-align:bottom;"
	\| Ordinal (categorical (ordered)		\| Ordinal (categorical (ordered)
	\| Describe with proportions		\| Describe with proportions
	\| style="font-weight:bold; color:#06D;" \| Frequency distribution table (also cumulative)		\| style="font-weight:bold; color:#06D;" \| [[Tables#Frequency_distribution_table\|Frequency distribution table]] (also cumulative)
	\| style="font-weight:bold; color:#06D;" \| Bar graph(also cumulative), Pie graph		\| style="font-weight:bold; color:#06D;" \| Bar graph(also cumulative), Pie graph
	\|- style="vertical-align:bottom;"		\|- style="vertical-align:bottom;"
	\| Numerical discrete		\| Numerical discrete
	\| Describe with proportions, means and standard deviation		\| Describe with proportions, means and standard deviation
	\| style="font-weight:bold; color:#06D;" \| Frequency distribution table (also cumulative), Table of descriptive statistics		\| style="font-weight:bold; color:#06D;" \| [[Tables#Frequency_distribution_table\|Frequency distribution table]] (also cumulative), Table of descriptive statistics
	\| style="font-weight:bold; color:#06D;" \| Bar graph (also cumulative), Histogram (if large number of values)		\| style="font-weight:bold; color:#06D;" \| Bar graph (also cumulative), Histogram (if large number of values)
	\|- style="vertical-align:bottom;"		\|- style="vertical-align:bottom;"
	\| Numerical continuous		\| Numerical continuous
	\| Describe with means, medians, standard deviation, quartiles		\| Describe with means, medians, standard deviation, quartiles
	\| style="font-weight:bold; color:#06D;" \| Frequency distribution table (group frequencies or cumulative), Table of descriptive statistics		\| style="font-weight:bold; color:#06D;" \| [[Tables#Frequency_distribution_table\|Frequency distribution table]] (group frequencies or cumulative), Table of descriptive statistics
	\| style="font-weight:bold; color:#06D;" \| Histogram (also cumulative), Frequency polygon, Box-and-whisker plot, Violin plot, One-way scatter plot		\| style="font-weight:bold; color:#06D;" \| Histogram (also cumulative), Frequency polygon, Box-and-whisker plot, Violin plot, One-way scatter plot
	\|}		\|}