Data Analysis - Revision history

EmoryFerguson at 20:17, 27 July 2017

2017-07-27T20:17:36Z

← Older revision		Revision as of 20:17, 27 July 2017
Line 3:		Line 3:
	The World Map is located under the Data Analysis option on the Main Menu of IFs.		The World Map is located under the Data Analysis option on the Main Menu of IFs.

	[[File:Worldmap1.png\|center]]		[[File:Worldmap1.png\|frame\|center\|World Map example]]

	The main function of the World Map is to display data in a visually dramatic format. Instead of representing country-related forecasts as lines in a graph, or columns in a table, the user is able to view the forecasts as shades of color imposed on a map of the world.		The main function of the World Map is to display data in a visually dramatic format. Instead of representing country-related forecasts as lines in a graph, or columns in a table, the user is able to view the forecasts as shades of color imposed on a map of the world.
Line 27:		Line 27:
	From the Main Menu, an option under Data Analysis provides users with the ability to examine the relationship between historical variables. From the Data Analysis menu, select Analyze Across Countries (Cross-Sectional) to reach the screen displayed below.		From the Main Menu, an option under Data Analysis provides users with the ability to examine the relationship between historical variables. From the Data Analysis menu, select Analyze Across Countries (Cross-Sectional) to reach the screen displayed below.

	[[File:Crosssectional1.png\|~~center~~]]		[[File:Crosssectional1.png\|frame\|right\|Variables across countries window]]

	To do a cross-sectional analysis, specify a dependent variable (a variable you want to understand the causes of) and one or more independent variables (the possible causes of change in the dependent variable). By convention, the dependent variable appears on the y-axis and the independent variable appears on the x-axis on a graph. To select a dependent variable first, scroll through the alphabetized variable list and left-click on any variable in which a user might be interested. Click Select to choose that variable. Users can also type a variable name in the simple text search box directly above the list, which filters series by prefix. Alternatively, there is a more sophisticated search feature available through the Search button at the bottom of the screen. From the search screen, a search on "female", for example, would find all results that contain the word, anywhere in the variable name or description. After selecting a dependent variable, either from the variable list or from the search form, a drop-down list will appear, specifying the year to be displayed. A cross-sectional display includes data for a single year, earliest available or most recent available for each country. The process described here is also used to assign independent variables. To reassign any variable, select the corresponding option button and simply load the new series.		To do a cross-sectional analysis, specify a dependent variable (a variable you want to understand the causes of) and one or more independent variables (the possible causes of change in the dependent variable). By convention, the dependent variable appears on the y-axis and the independent variable appears on the x-axis on a graph. To select a dependent variable first, scroll through the alphabetized variable list and left-click on any variable in which a user might be interested. Click Select to choose that variable. Users can also type a variable name in the simple text search box directly above the list, which filters series by prefix. Alternatively, there is a more sophisticated search feature available through the Search button at the bottom of the screen. From the search screen, a search on "female", for example, would find all results that contain the word, anywhere in the variable name or description. After selecting a dependent variable, either from the variable list or from the search form, a drop-down list will appear, specifying the year to be displayed. A cross-sectional display includes data for a single year, earliest available or most recent available for each country. The process described here is also used to assign independent variables. To reassign any variable, select the corresponding option button and simply load the new series.
Line 33:		Line 33:
	As a demonstration, plot a cross-sectional relationship between female education and reproduction rates. For the dependent variable choose total fertility rates, by selecting TFR from the list of variables. Left-click the variable and two options will appear: Select and Data Information. Click Select to choose that variable. The latter provides detailed information about the scope, availability and source of the data set. The ensuing drop-down list determines the year for which data will be displayed. For this example, choose 2010. Notice that TFR(2010) is then shown as the Dependent Variable. Next, choose an Independent Variable, the level of adult female education, by selecting EdYearsAge15Female for the same year. Click the Plot button to generate the graph displayed below.		As a demonstration, plot a cross-sectional relationship between female education and reproduction rates. For the dependent variable choose total fertility rates, by selecting TFR from the list of variables. Left-click the variable and two options will appear: Select and Data Information. Click Select to choose that variable. The latter provides detailed information about the scope, availability and source of the data set. The ensuing drop-down list determines the year for which data will be displayed. For this example, choose 2010. Notice that TFR(2010) is then shown as the Dependent Variable. Next, choose an Independent Variable, the level of adult female education, by selecting EdYearsAge15Female for the same year. Click the Plot button to generate the graph displayed below.

	[[File:Crosssectional2.png\|center]]		[[File:Crosssectional2.png\|frame\|center\|Scattergram of raw country data example]]

	To learn how to use various features on the scatter plot, click [[#Cross-Sectional_Scattergram\|here]].		To learn how to use various features on the scatter plot, click [[#Cross-Sectional_Scattergram\|here]].
Line 41:		Line 41:
	This section describes how to use the various features on the Scattergram, which appears after clicking the Plot button in the Analyze Across Countries (Cross-Sectional) option.		This section describes how to use the various features on the Scattergram, which appears after clicking the Plot button in the Analyze Across Countries (Cross-Sectional) option.

	[[File:Crosssectional3.png\|~~RTENOTITLE~~]]		[[File:Crosssectional3.png\|frame\|center\|Scattergram of raw country data example]]

	The '''Relationships''' option allows users to fit a line to the graph. To impose a line of relationship on the scatter plot as displayed above, choose Relationships from the toolbar, and the option Linear. Notice the r-squared value (a measure of the goodness of fit between the independent and dependent variable) and linear equation displayed at the top of the screen. Additional relationship types include: logarithmic, exponential, power, polynomial and logistic. To remove the line, click on No Regression.		The '''Relationships''' option allows users to fit a line to the graph. To impose a line of relationship on the scatter plot as displayed above, choose Relationships from the toolbar, and the option Linear. Notice the r-squared value (a measure of the goodness of fit between the independent and dependent variable) and linear equation displayed at the top of the screen. Additional relationship types include: logarithmic, exponential, power, polynomial and logistic. To remove the line, click on No Regression.
Line 55:		Line 55:
	Whereas [[#Analyze_Across_Countries_.28Cross-Sectional_Analysis.29\|cross-sectional analysis (Analyze Across Countries)]] concerns historical relationships between different variables, the primary purpose of the longitudinal analysis (Analyze Across Time) is to trace historical trends of individual data series. This option can be accessed from the Data Analysis option on the Main Menu of IFs.		Whereas [[#Analyze_Across_Countries_.28Cross-Sectional_Analysis.29\|cross-sectional analysis (Analyze Across Countries)]] concerns historical relationships between different variables, the primary purpose of the longitudinal analysis (Analyze Across Time) is to trace historical trends of individual data series. This option can be accessed from the Data Analysis option on the Main Menu of IFs.

	[[File:Longitudinal1.png\|~~center~~]]		[[File:Longitudinal1.png\|frame\|right\|Variables across time window]]

	To start with, pick any data series to load a dependent variable. Time is set as an independent variable by default. Users can select a variable by scrolling through the dependent variable list box, typing a variable name in the text box or with the more sophisticated, separate Search option, located at the bottom of the screen. Click Select Countries to specify the data that will appear in graphs. (Note that Use Groups , the button beneath Select Countries, is a toggle, switching from country to group selection or vice-versa; e.g. if groups are selected the toggle will read "Use Countries"). From the country selection screen, pick a country, a group or a decomposed group. Buttons on the right side of the country selection screen also allow users to switch aggregation to groups or decomposed groups. Continue back to the original screen for analysis over time and Plot the result.		To start with, pick any data series to load a dependent variable. Time is set as an independent variable by default. Users can select a variable by scrolling through the dependent variable list box, typing a variable name in the text box or with the more sophisticated, separate Search option, located at the bottom of the screen. Click Select Countries to specify the data that will appear in graphs. (Note that Use Groups , the button beneath Select Countries, is a toggle, switching from country to group selection or vice-versa; e.g. if groups are selected the toggle will read "Use Countries"). From the country selection screen, pick a country, a group or a decomposed group. Buttons on the right side of the country selection screen also allow users to switch aggregation to groups or decomposed groups. Continue back to the original screen for analysis over time and Plot the result.
Line 61:		Line 61:
	To demonstrate, pick a variable such as AidDon%GNI (aid donations as a percent of Gross National Income, the successor concept to Gross National Product). Click the Select Countries button and choose United States as a donor country. To generate the graph displayed below, click Plot. You will see the trend of U.S. aid commitment over time.		To demonstrate, pick a variable such as AidDon%GNI (aid donations as a percent of Gross National Income, the successor concept to Gross National Product). Click the Select Countries button and choose United States as a donor country. To generate the graph displayed below, click Plot. You will see the trend of U.S. aid commitment over time.

	[[File:Longitudinal2.png\|center]]		[[File:Longitudinal2.png\|frame\|center\|Graph of Longitudinal Data Example]]

	On the Graphical Display screen as shown above, options on the top menu bar allow users to go back to home screen, alter the scale, display a table, format titles and explore future trends. Under the Trend menu, users can impose extrapolations—linear, polynomial, logarithmic, exponential and s-curve—onto the chart. The sub-option, Extrapolation Setup, features customization options for polynomial, exponential and s-curve trend lines.		On the Graphical Display screen as shown above, options on the top menu bar allow users to go back to home screen, alter the scale, display a table, format titles and explore future trends. Under the Trend menu, users can impose extrapolations—linear, polynomial, logarithmic, exponential and s-curve—onto the chart. The sub-option, Extrapolation Setup, features customization options for polynomial, exponential and s-curve trend lines.
Line 79:		Line 79:
	By clicking on Show Computed Functions, you will be presented with a menu that looks similar to the one pictured below:		By clicking on Show Computed Functions, you will be presented with a menu that looks similar to the one pictured below:

	[[File:Functions.png\|center]]		[[File:Functions.png\|frame\|center\|Show Computed Functions menu]]

	The box that is located in the middle of your screen holds hundreds of functions. If you click on the Extend List option right above this box, it will display an expanded list of functions.		The box that is located in the middle of your screen holds hundreds of functions. If you click on the Extend List option right above this box, it will display an expanded list of functions.
Line 91:		Line 91:
	= <span style="font-size:xx-large;">Identify Group or Country/Region Members</span> =		= <span style="font-size:xx-large;">Identify Group or Country/Region Members</span> =

	To identify regions or group members used in IFs, click on Data Analysis on the Main Menu of IFs, and then select Identify Group or Country/Region Members.		To identify regions or group members used in IFs, click on Data Analysis on the Main Menu of IFs, and then select Identify Group or Country/Region Members.[[File:Identify.png\|frame\|right\|Identify Group or Country/Region Members window]]

	This feature of IFs allows users to identify which countries/regions are represented in certain groups. By clicking on any of the groups in the left-hand list, the members of that group will appear on the right hand side.		This feature of IFs allows users to identify which countries/regions are represented in certain groups. By clicking on any of the groups in the left-hand list, the members of that group will appear on the right hand side.

	~~[[File:Identify.png\|center]]~~

	By clicking on Using Regions, the list of groups on the left hand side will become a list of countries/regions.		By clicking on Using Regions, the list of groups on the left hand side will become a list of countries/regions.

EmoryFerguson at 17:32, 21 July 2017

2017-07-21T17:32:53Z

← Older revision		Revision as of 17:32, 21 July 2017
Line 1:		Line 1:
	= World Map: Historic Data =		= <span style="font-size:xx-large;">World Map: Historic Data</span> =

	The World Map is located under the Data Analysis option on the Main Menu of IFs.		The World Map is located under the Data Analysis option on the Main Menu of IFs.

	[[File:Worldmap1.png\|~~RTENOTITLE~~]]		[[File:Worldmap1.png\|center]]

	The main function of the World Map is to display data in a visually dramatic format. Instead of representing country-related forecasts as lines in a graph, or columns in a table, the user is able to view the forecasts as shades of color imposed on a map of the world.		The main function of the World Map is to display data in a visually dramatic format. Instead of representing country-related forecasts as lines in a graph, or columns in a table, the user is able to view the forecasts as shades of color imposed on a map of the world.
Line 23:		Line 23:
	*Hovering over each country in the map displays the associated value of the data set, and left clicking on the map allows users to view either a detailed map of the country or a table of the data values by year.		*Hovering over each country in the map displays the associated value of the data set, and left clicking on the map allows users to view either a detailed map of the country or a table of the data values by year.

	= Analyze Across Countries (Cross-Sectional Analysis) =		= <span style="font-size:xx-large;">Analyze Across Countries (Cross-Sectional Analysis)</span> =

	From the Main Menu, an option under Data Analysis provides users with the ability to examine the relationship between historical variables. From the Data Analysis menu, select Analyze Across Countries (Cross-Sectional) to reach the screen displayed below.		From the Main Menu, an option under Data Analysis provides users with the ability to examine the relationship between historical variables. From the Data Analysis menu, select Analyze Across Countries (Cross-Sectional) to reach the screen displayed below.

	[[File:Crosssectional1.png\|~~RTENOTITLE~~]]		[[File:Crosssectional1.png\|center]]

	To do a cross-sectional analysis, specify a dependent variable (a variable you want to understand the causes of) and one or more independent variables (the possible causes of change in the dependent variable). By convention, the dependent variable appears on the y-axis and the independent variable appears on the x-axis on a graph. To select a dependent variable first, scroll through the alphabetized variable list and left-click on any variable in which a user might be interested. Click Select to choose that variable. Users can also type a variable name in the simple text search box directly above the list, which filters series by prefix. Alternatively, there is a more sophisticated search feature available through the Search button at the bottom of the screen. From the search screen, a search on "female", for example, would find all results that contain the word, anywhere in the variable name or description. After selecting a dependent variable, either from the variable list or from the search form, a drop-down list will appear, specifying the year to be displayed. A cross-sectional display includes data for a single year, earliest available or most recent available for each country. The process described here is also used to assign independent variables. To reassign any variable, select the corresponding option button and simply load the new series.		To do a cross-sectional analysis, specify a dependent variable (a variable you want to understand the causes of) and one or more independent variables (the possible causes of change in the dependent variable). By convention, the dependent variable appears on the y-axis and the independent variable appears on the x-axis on a graph. To select a dependent variable first, scroll through the alphabetized variable list and left-click on any variable in which a user might be interested. Click Select to choose that variable. Users can also type a variable name in the simple text search box directly above the list, which filters series by prefix. Alternatively, there is a more sophisticated search feature available through the Search button at the bottom of the screen. From the search screen, a search on "female", for example, would find all results that contain the word, anywhere in the variable name or description. After selecting a dependent variable, either from the variable list or from the search form, a drop-down list will appear, specifying the year to be displayed. A cross-sectional display includes data for a single year, earliest available or most recent available for each country. The process described here is also used to assign independent variables. To reassign any variable, select the corresponding option button and simply load the new series.
Line 33:		Line 33:
	As a demonstration, plot a cross-sectional relationship between female education and reproduction rates. For the dependent variable choose total fertility rates, by selecting TFR from the list of variables. Left-click the variable and two options will appear: Select and Data Information. Click Select to choose that variable. The latter provides detailed information about the scope, availability and source of the data set. The ensuing drop-down list determines the year for which data will be displayed. For this example, choose 2010. Notice that TFR(2010) is then shown as the Dependent Variable. Next, choose an Independent Variable, the level of adult female education, by selecting EdYearsAge15Female for the same year. Click the Plot button to generate the graph displayed below.		As a demonstration, plot a cross-sectional relationship between female education and reproduction rates. For the dependent variable choose total fertility rates, by selecting TFR from the list of variables. Left-click the variable and two options will appear: Select and Data Information. Click Select to choose that variable. The latter provides detailed information about the scope, availability and source of the data set. The ensuing drop-down list determines the year for which data will be displayed. For this example, choose 2010. Notice that TFR(2010) is then shown as the Dependent Variable. Next, choose an Independent Variable, the level of adult female education, by selecting EdYearsAge15Female for the same year. Click the Plot button to generate the graph displayed below.

	[[File:Crosssectional2.png\|~~RTENOTITLE~~]]		[[File:Crosssectional2.png\|center]]

	To learn how to use various features on the scatter plot, click [[#Cross-Sectional_Scattergram\|here]].		To learn how to use various features on the scatter plot, click [[#Cross-Sectional_Scattergram\|here]].

	== Cross-Sectional Scattergram ==		== <span style="font-size:x-large;">Cross-Sectional Scattergram</span> ==

	This section describes how to use the various features on the Scattergram, which appears after clicking the Plot button in the Analyze Across Countries (Cross-Sectional) option.		This section describes how to use the various features on the Scattergram, which appears after clicking the Plot button in the Analyze Across Countries (Cross-Sectional) option.
Line 51:		Line 51:
	Clicking on '''Continue''' returns the user to the previous page.		Clicking on '''Continue''' returns the user to the previous page.

	= Analyze Across Time (Longitudinal Analysis) =		= <span style="font-size:xx-large;">Analyze Across Time (Longitudinal Analysis)</span> =

	Whereas [[#Analyze_Across_Countries_.28Cross-Sectional_Analysis.29\|cross-sectional analysis (Analyze Across Countries)]] concerns historical relationships between different variables, the primary purpose of the longitudinal analysis (Analyze Across Time) is		Whereas [[#Analyze_Across_Countries_.28Cross-Sectional_Analysis.29\|cross-sectional analysis (Analyze Across Countries)]] concerns historical relationships between different variables, the primary purpose of the longitudinal analysis (Analyze Across Time) is to trace historical trends of individual data series. This option can be accessed from the Data Analysis option on the Main Menu of IFs.

	[[File:Longitudinal1.png\|~~RTENOTITLE~~]]		[[File:Longitudinal1.png\|center]]

	To start with, pick any data series to load a dependent variable. Time is set as an independent variable by default. Users can select a variable by scrolling through the dependent variable list box, typing a variable name in the text box or with the more sophisticated, separate Search option, located at the bottom of the screen. Click Select Countries to specify the data that will appear in graphs. (Note that Use Groups , the button beneath Select Countries, is a toggle, switching from country to group selection or vice-versa; e.g. if groups are selected the toggle will read "Use Countries"). From the country selection screen, pick a country, a group or a decomposed group. Buttons on the right side of the country selection screen also allow users to switch aggregation to groups or decomposed groups. Continue back to the original screen for analysis over time and Plot the result.		To start with, pick any data series to load a dependent variable. Time is set as an independent variable by default. Users can select a variable by scrolling through the dependent variable list box, typing a variable name in the text box or with the more sophisticated, separate Search option, located at the bottom of the screen. Click Select Countries to specify the data that will appear in graphs. (Note that Use Groups , the button beneath Select Countries, is a toggle, switching from country to group selection or vice-versa; e.g. if groups are selected the toggle will read "Use Countries"). From the country selection screen, pick a country, a group or a decomposed group. Buttons on the right side of the country selection screen also allow users to switch aggregation to groups or decomposed groups. Continue back to the original screen for analysis over time and Plot the result.
Line 61:		Line 61:
	To demonstrate, pick a variable such as AidDon%GNI (aid donations as a percent of Gross National Income, the successor concept to Gross National Product). Click the Select Countries button and choose United States as a donor country. To generate the graph displayed below, click Plot. You will see the trend of U.S. aid commitment over time.		To demonstrate, pick a variable such as AidDon%GNI (aid donations as a percent of Gross National Income, the successor concept to Gross National Product). Click the Select Countries button and choose United States as a donor country. To generate the graph displayed below, click Plot. You will see the trend of U.S. aid commitment over time.

	[[File:Longitudinal2.png\|~~RTENOTITLE~~]]		[[File:Longitudinal2.png\|center]]

	On the Graphical Display screen as shown above, options on the top menu bar allow users to go back to home screen, alter the scale, display a table, format titles and explore future trends. Under the Trend menu, users can impose extrapolations—linear, polynomial, logarithmic, exponential and s-curve—onto the chart. The sub-option, Extrapolation Setup, features customization options for polynomial, exponential and s-curve trend lines.		On the Graphical Display screen as shown above, options on the top menu bar allow users to go back to home screen, alter the scale, display a table, format titles and explore future trends. Under the Trend menu, users can impose extrapolations—linear, polynomial, logarithmic, exponential and s-curve—onto the chart. The sub-option, Extrapolation Setup, features customization options for polynomial, exponential and s-curve trend lines.
Line 73:		Line 73:
	Exploration of maps, cross-sectional and longitudinal relationships, and relationships computed for IFs can give you much information about the apparent relationships among a wide range of global development indicators. Even if you never used IFs for forecasting, this data analysis capacity could significantly enhance your understanding of the world.		Exploration of maps, cross-sectional and longitudinal relationships, and relationships computed for IFs can give you much information about the apparent relationships among a wide range of global development indicators. Even if you never used IFs for forecasting, this data analysis capacity could significantly enhance your understanding of the world.

	= Show Computed Functions =		= <span style="font-size:xx-large;">Show Computed Functions</span> =

	To access Show Computed Functions, click on Data Analysis on the Main Menu of IFs.		To access Show Computed Functions, click on Data Analysis on the Main Menu of IFs.
Line 79:		Line 79:
	By clicking on Show Computed Functions, you will be presented with a menu that looks similar to the one pictured below:		By clicking on Show Computed Functions, you will be presented with a menu that looks similar to the one pictured below:

	[[File:Functions.png]]		[[File:Functions.png\|center]]

	The box that is located in the middle of your screen holds hundreds of functions. If you click on the Extend List option right above this box, it will display an expanded list of functions.		The box that is located in the middle of your screen holds hundreds of functions. If you click on the Extend List option right above this box, it will display an expanded list of functions.
Line 89:		Line 89:
	Select one or more of functions if you would like to see multiple relationships on one screen. In order to select more than one function, highlight the first function, hold the Ctrl key and select a second function.		Select one or more of functions if you would like to see multiple relationships on one screen. In order to select more than one function, highlight the first function, hold the Ctrl key and select a second function.

	= Identify Group or Country/Region Members =		= <span style="font-size:xx-large;">Identify Group or Country/Region Members</span> =

	To identify regions or group members used in IFs, click on Data Analysis on the Main Menu of IFs, and then select Identify Group or Country/Region Members.		To identify regions or group members used in IFs, click on Data Analysis on the Main Menu of IFs, and then select Identify Group or Country/Region Members.
Line 95:		Line 95:
	This feature of IFs allows users to identify which countries/regions are represented in certain groups. By clicking on any of the groups in the left-hand list, the members of that group will appear on the right hand side.		This feature of IFs allows users to identify which countries/regions are represented in certain groups. By clicking on any of the groups in the left-hand list, the members of that group will appear on the right hand side.

	[[File:Identify.png]]		[[File:Identify.png\|center]]

	By clicking on Using Regions, the list of groups on the left hand side will become a list of countries/regions.		By clicking on Using Regions, the list of groups on the left hand side will become a list of countries/regions.

CamrynDreyer at 16:52, 21 July 2017

2017-07-21T16:52:31Z

← Older revision		Revision as of 16:52, 21 July 2017
Line 53:		Line 53:
	= Analyze Across Time (Longitudinal Analysis) =		= Analyze Across Time (Longitudinal Analysis) =

	Whereas [~~http://www~~.~~du.edu/ifs/help/use~~-~~online/data/crosssectional/index~~.~~html~~ cross-sectional analysis (Analyze Across Countries)] concerns historical relationships between different variables, the primary purpose of the longitudinal analysis (Analyze Across Time) is		Whereas [[#Analyze_Across_Countries_.28Cross-Sectional_Analysis.29\|cross-sectional analysis (Analyze Across Countries)]] concerns historical relationships between different variables, the primary purpose of the longitudinal analysis (Analyze Across Time) is

	[[File:Longitudinal1.png]]		[[File:Longitudinal1.png\|RTENOTITLE]]

	To start with, pick any data series to load a dependent variable. Time is set as an independent variable by default. Users can select a variable by scrolling through the dependent variable list box, typing a variable name in the text box or with the more sophisticated, separate Search option, located at the bottom of the screen. Click Select Countries to specify the data that will appear in graphs. (Note that Use Groups , the button beneath Select Countries, is a toggle, switching from country to group selection or vice-versa; e.g. if groups are selected the toggle will read "Use Countries"). From the country selection screen, pick a country, a group or a decomposed group. Buttons on the right side of the country selection screen also allow users to switch aggregation to groups or decomposed groups. Continue back to the original screen for analysis over time and Plot the result.		To start with, pick any data series to load a dependent variable. Time is set as an independent variable by default. Users can select a variable by scrolling through the dependent variable list box, typing a variable name in the text box or with the more sophisticated, separate Search option, located at the bottom of the screen. Click Select Countries to specify the data that will appear in graphs. (Note that Use Groups , the button beneath Select Countries, is a toggle, switching from country to group selection or vice-versa; e.g. if groups are selected the toggle will read "Use Countries"). From the country selection screen, pick a country, a group or a decomposed group. Buttons on the right side of the country selection screen also allow users to switch aggregation to groups or decomposed groups. Continue back to the original screen for analysis over time and Plot the result.
Line 61:		Line 61:
	To demonstrate, pick a variable such as AidDon%GNI (aid donations as a percent of Gross National Income, the successor concept to Gross National Product). Click the Select Countries button and choose United States as a donor country. To generate the graph displayed below, click Plot. You will see the trend of U.S. aid commitment over time.		To demonstrate, pick a variable such as AidDon%GNI (aid donations as a percent of Gross National Income, the successor concept to Gross National Product). Click the Select Countries button and choose United States as a donor country. To generate the graph displayed below, click Plot. You will see the trend of U.S. aid commitment over time.

	[[File:Longitudinal2.png]]		[[File:Longitudinal2.png\|RTENOTITLE]]

	On the Graphical Display screen as shown above, options on the top menu bar allow users to go back to home screen, alter the scale, display a table, format titles and explore future trends. Under the Trend menu, users can impose extrapolations—linear, polynomial, logarithmic, exponential and s-curve—onto the chart. The sub-option, Extrapolation Setup, features customization options for polynomial, exponential and s-curve trend lines.		On the Graphical Display screen as shown above, options on the top menu bar allow users to go back to home screen, alter the scale, display a table, format titles and explore future trends. Under the Trend menu, users can impose extrapolations—linear, polynomial, logarithmic, exponential and s-curve—onto the chart. The sub-option, Extrapolation Setup, features customization options for polynomial, exponential and s-curve trend lines.
Line 67:		Line 67:
	An additional feature of the longitudinal analysis is the ability to look more closely at the data set in which a user might be interested. Left-click on any variable and a small window with two options will appear: Select and Data Information. Click Data Information in order to access detailed information as to the scope, availability and properties of the data set in question.		An additional feature of the longitudinal analysis is the ability to look more closely at the data set in which a user might be interested. Left-click on any variable and a small window with two options will appear: Select and Data Information. Click Data Information in order to access detailed information as to the scope, availability and properties of the data set in question.

	Some other features of this section of IFs include the [~~http://www.du.edu/ifs/help/use-online/repeated/computations.html~~ Computations] button and the [~~http://www.du.edu/ifs/help/use-online/repeated/general/table.html~~ Table]button.		Some other features of this section of IFs include the [[Repeated_Features#Computations\|Computations]] button and the [[Repeated_Features#Table_Use\|Table]] button.

	Other than the default setting, treating time as an independent variable, which allows users to look at a historical trend of one variable over time, two other types of analysis are also available in the model: treatment of time As Points and As Time. When the Treatment of Time check box labeled As Points is active, the data points become years and users can look at the relationship between two variables as x- and y-axes. The third option, treatment of time as time, facilitates side-by-side comparison of longitudinal trends with two different variables on the same display (the x-axis is time, in this case).		Other than the default setting, treating time as an independent variable, which allows users to look at a historical trend of one variable over time, two other types of analysis are also available in the model: treatment of time As Points and As Time. When the Treatment of Time check box labeled As Points is active, the data points become years and users can look at the relationship between two variables as x- and y-axes. The third option, treatment of time as time, facilitates side-by-side comparison of longitudinal trends with two different variables on the same display (the x-axis is time, in this case).

CamrynDreyer at 16:48, 21 July 2017

2017-07-21T16:48:54Z

← Older revision		Revision as of 16:48, 21 July 2017
Line 35:		Line 35:
	[[File:Crosssectional2.png\|RTENOTITLE]]		[[File:Crosssectional2.png\|RTENOTITLE]]

	To learn how to use various features on the scatter plot, click [[#Cross-Sectional_Scattergram~~ ~~\|here]].		To learn how to use various features on the scatter plot, click [[#Cross-Sectional_Scattergram\|here]].

	== Cross-Sectional Scattergram~~ ~~ ==		== Cross-Sectional Scattergram ==

	This section describes how to use the various features on the Scattergram, which appears after clicking the Plot button in the Analyze Across Countries (Cross-Sectional) option.		This section describes how to use the various features on the Scattergram, which appears after clicking the Plot button in the Analyze Across Countries (Cross-Sectional) option.

CamrynDreyer at 16:48, 21 July 2017

2017-07-21T16:48:14Z

← Older revision		Revision as of 16:48, 21 July 2017
Line 35:		Line 35:
	[[File:Crosssectional2.png\|RTENOTITLE]]		[[File:Crosssectional2.png\|RTENOTITLE]]

	To learn how to use various features on the scatter plot, click [[#Cross-Sectional_Scattergram\|here]].		To learn how to use various features on the scatter plot, click [[#Cross-Sectional_Scattergram \|here]].

	== Cross-Sectional Scattergram  ==		== Cross-Sectional Scattergram  ==

CamrynDreyer at 16:47, 21 July 2017

2017-07-21T16:47:31Z

← Older revision		Revision as of 16:47, 21 July 2017
Line 27:		Line 27:
	From the Main Menu, an option under Data Analysis provides users with the ability to examine the relationship between historical variables. From the Data Analysis menu, select Analyze Across Countries (Cross-Sectional) to reach the screen displayed below.		From the Main Menu, an option under Data Analysis provides users with the ability to examine the relationship between historical variables. From the Data Analysis menu, select Analyze Across Countries (Cross-Sectional) to reach the screen displayed below.

	[[File:Crosssectional1.png]]		[[File:Crosssectional1.png\|RTENOTITLE]]

	To do a cross-sectional analysis, specify a dependent variable (a variable you want to understand the causes of) and one or more independent variables (the possible causes of change in the dependent variable). By convention, the dependent variable appears on the y-axis and the independent variable appears on the x-axis on a graph. To select a dependent variable first, scroll through the alphabetized variable list and left-click on any variable in which a user might be interested. Click Select to choose that variable. Users can also type a variable name in the simple text search box directly above the list, which filters series by prefix. Alternatively, there is a more sophisticated search feature available through the Search button at the bottom of the screen. From the search screen, a search on "female", for example, would find all results that contain the word, anywhere in the variable name or description. After selecting a dependent variable, either from the variable list or from the search form, a drop-down list will appear, specifying the year to be displayed. A cross-sectional display includes data for a single year, earliest available or most recent available for each country. The process described here is also used to assign independent variables. To reassign any variable, select the corresponding option button and simply load the new series.		To do a cross-sectional analysis, specify a dependent variable (a variable you want to understand the causes of) and one or more independent variables (the possible causes of change in the dependent variable). By convention, the dependent variable appears on the y-axis and the independent variable appears on the x-axis on a graph. To select a dependent variable first, scroll through the alphabetized variable list and left-click on any variable in which a user might be interested. Click Select to choose that variable. Users can also type a variable name in the simple text search box directly above the list, which filters series by prefix. Alternatively, there is a more sophisticated search feature available through the Search button at the bottom of the screen. From the search screen, a search on "female", for example, would find all results that contain the word, anywhere in the variable name or description. After selecting a dependent variable, either from the variable list or from the search form, a drop-down list will appear, specifying the year to be displayed. A cross-sectional display includes data for a single year, earliest available or most recent available for each country. The process described here is also used to assign independent variables. To reassign any variable, select the corresponding option button and simply load the new series.
Line 33:		Line 33:
	As a demonstration, plot a cross-sectional relationship between female education and reproduction rates. For the dependent variable choose total fertility rates, by selecting TFR from the list of variables. Left-click the variable and two options will appear: Select and Data Information. Click Select to choose that variable. The latter provides detailed information about the scope, availability and source of the data set. The ensuing drop-down list determines the year for which data will be displayed. For this example, choose 2010. Notice that TFR(2010) is then shown as the Dependent Variable. Next, choose an Independent Variable, the level of adult female education, by selecting EdYearsAge15Female for the same year. Click the Plot button to generate the graph displayed below.		As a demonstration, plot a cross-sectional relationship between female education and reproduction rates. For the dependent variable choose total fertility rates, by selecting TFR from the list of variables. Left-click the variable and two options will appear: Select and Data Information. Click Select to choose that variable. The latter provides detailed information about the scope, availability and source of the data set. The ensuing drop-down list determines the year for which data will be displayed. For this example, choose 2010. Notice that TFR(2010) is then shown as the Dependent Variable. Next, choose an Independent Variable, the level of adult female education, by selecting EdYearsAge15Female for the same year. Click the Plot button to generate the graph displayed below.

	[[File:Crosssectional2.png]]		[[File:Crosssectional2.png\|RTENOTITLE]]

	To learn how to use various features on the scatter plot, click [~~http://www.du.edu/ifs/help/use~~-~~online/data/crosssectional/scattergram.html~~ here].		To learn how to use various features on the scatter plot, click [[#Cross-Sectional_Scattergram\|here]].

	== Cross-Sectional Scattergram  ==		== Cross-Sectional Scattergram  ==
Line 41:		Line 41:
	This section describes how to use the various features on the Scattergram, which appears after clicking the Plot button in the Analyze Across Countries (Cross-Sectional) option.		This section describes how to use the various features on the Scattergram, which appears after clicking the Plot button in the Analyze Across Countries (Cross-Sectional) option.

	[[File:Crosssectional3.png]]		[[File:Crosssectional3.png\|RTENOTITLE]]

	The '''Relationships''' option allows users to fit a line to the graph. To impose a line of relationship on the scatter plot as displayed above, choose Relationships from the toolbar, and the option Linear. Notice the r-squared value (a measure of the goodness of fit between the independent and dependent variable) and linear equation displayed at the top of the screen. Additional relationship types include: logarithmic, exponential, power, polynomial and logistic. To remove the line, click on No Regression.		The '''Relationships''' option allows users to fit a line to the graph. To impose a line of relationship on the scatter plot as displayed above, choose Relationships from the toolbar, and the option Linear. Notice the r-squared value (a measure of the goodness of fit between the independent and dependent variable) and linear equation displayed at the top of the screen. Additional relationship types include: logarithmic, exponential, power, polynomial and logistic. To remove the line, click on No Regression.

CamrynDreyer at 16:46, 21 July 2017

2017-07-21T16:46:24Z

← Older revision		Revision as of 16:46, 21 July 2017
Line 3:		Line 3:
	The World Map is located under the Data Analysis option on the Main Menu of IFs.		The World Map is located under the Data Analysis option on the Main Menu of IFs.

	[[File:Worldmap1.png]]		[[File:Worldmap1.png\|RTENOTITLE]]

	The main function of the World Map is to display data in a visually dramatic format. Instead of representing country-related forecasts as lines in a graph, or columns in a table, the user is able to view the forecasts as shades of color imposed on a map of the world.		The main function of the World Map is to display data in a visually dramatic format. Instead of representing country-related forecasts as lines in a graph, or columns in a table, the user is able to view the forecasts as shades of color imposed on a map of the world.

CamrynDreyer at 16:44, 21 July 2017

2017-07-21T16:44:55Z

← Older revision		Revision as of 16:44, 21 July 2017
Line 53:		Line 53:
	= Analyze Across Time (Longitudinal Analysis) =		= Analyze Across Time (Longitudinal Analysis) =

	Whereas [http://www.du.edu/ifs/help/use-online/data/crosssectional/index.html cross-sectional analysis (Analyze Across Countries)] concerns historical relationships between different variables, the primary purpose of the longitudinal analysis (Analyze Across Time) is ~~to trace historical trends of individual data series. This option can be accessed from the Data Analysis option on the Main Menu of IFs.~~		Whereas [http://www.du.edu/ifs/help/use-online/data/crosssectional/index.html cross-sectional analysis (Analyze Across Countries)] concerns historical relationships between different variables, the primary purpose of the longitudinal analysis (Analyze Across Time) is

	~~http~~:~~//www~~.~~du.edu/ifs/help/use-online/data/longitudinal.html~~		[[File:Longitudinal1.png]]

	To start with, pick any data series to load a dependent variable. Time is set as an independent variable by default. Users can select a variable by scrolling through the dependent variable list box, typing a variable name in the text box or with the more sophisticated, separate Search option, located at the bottom of the screen. Click Select Countries to specify the data that will appear in graphs. (Note that Use Groups , the button beneath Select Countries, is a toggle, switching from country to group selection or vice-versa; e.g. if groups are selected the toggle will read "Use Countries"). From the country selection screen, pick a country, a group or a decomposed group. Buttons on the right side of the country selection screen also allow users to switch aggregation to groups or decomposed groups. Continue back to the original screen for analysis over time and Plot the result.		To start with, pick any data series to load a dependent variable. Time is set as an independent variable by default. Users can select a variable by scrolling through the dependent variable list box, typing a variable name in the text box or with the more sophisticated, separate Search option, located at the bottom of the screen. Click Select Countries to specify the data that will appear in graphs. (Note that Use Groups , the button beneath Select Countries, is a toggle, switching from country to group selection or vice-versa; e.g. if groups are selected the toggle will read "Use Countries"). From the country selection screen, pick a country, a group or a decomposed group. Buttons on the right side of the country selection screen also allow users to switch aggregation to groups or decomposed groups. Continue back to the original screen for analysis over time and Plot the result.
Line 61:		Line 61:
	To demonstrate, pick a variable such as AidDon%GNI (aid donations as a percent of Gross National Income, the successor concept to Gross National Product). Click the Select Countries button and choose United States as a donor country. To generate the graph displayed below, click Plot. You will see the trend of U.S. aid commitment over time.		To demonstrate, pick a variable such as AidDon%GNI (aid donations as a percent of Gross National Income, the successor concept to Gross National Product). Click the Select Countries button and choose United States as a donor country. To generate the graph displayed below, click Plot. You will see the trend of U.S. aid commitment over time.

	~~http~~:~~//www~~.~~du.edu/ifs/help/use-online/data/longitudinal.html~~		[[File:Longitudinal2.png]]

	On the Graphical Display screen as shown above, options on the top menu bar allow users to go back to home screen, alter the scale, display a table, format titles and explore future trends. Under the Trend menu, users can impose extrapolations—linear, polynomial, logarithmic, exponential and s-curve—onto the chart. The sub-option, Extrapolation Setup, features customization options for polynomial, exponential and s-curve trend lines.		On the Graphical Display screen as shown above, options on the top menu bar allow users to go back to home screen, alter the scale, display a table, format titles and explore future trends. Under the Trend menu, users can impose extrapolations—linear, polynomial, logarithmic, exponential and s-curve—onto the chart. The sub-option, Extrapolation Setup, features customization options for polynomial, exponential and s-curve trend lines.

CamrynDreyer at 16:43, 21 July 2017

2017-07-21T16:43:25Z

← Older revision		Revision as of 16:43, 21 July 2017
Line 95:		Line 95:
	This feature of IFs allows users to identify which countries/regions are represented in certain groups. By clicking on any of the groups in the left-hand list, the members of that group will appear on the right hand side.		This feature of IFs allows users to identify which countries/regions are represented in certain groups. By clicking on any of the groups in the left-hand list, the members of that group will appear on the right hand side.

	~~http~~:~~//www~~.~~du.edu/ifs/help/use-online/data/identify.html~~		[[File:Identify.png]]

	By clicking on Using Regions, the list of groups on the left hand side will become a list of countries/regions.		By clicking on Using Regions, the list of groups on the left hand side will become a list of countries/regions.

CamrynDreyer at 16:42, 21 July 2017

2017-07-21T16:42:35Z

← Older revision		Revision as of 16:42, 21 July 2017
Line 79:		Line 79:
	By clicking on Show Computed Functions, you will be presented with a menu that looks similar to the one pictured below:		By clicking on Show Computed Functions, you will be presented with a menu that looks similar to the one pictured below:

	~~http~~:~~//www~~.~~du.edu/ifs/help/use-online/data/show.html~~		[[File:Functions.png]]

	The box that is located in the middle of your screen holds hundreds of functions. If you click on the Extend List option right above this box, it will display an expanded list of functions.		The box that is located in the middle of your screen holds hundreds of functions. If you click on the Extend List option right above this box, it will display an expanded list of functions.