Video Tutorial Transcripts

Contents

Video 1: Introduction
Video 2: Basic Navigation
Video 3: Bucket View
Video 4: Crosstab View
Video 5: Map View
Video 6: Changing the Settings
Video 7: Research Applications

Video 1: Introduction

Hello and welcome to the video tutorial series for the Suave program.

This tutorial series will show how you can analyze two types of surveys: a public opinion survey with anonymous respondents and a survey where you explore a collection of images and their metadata. An example of the first type of survey is the General Social Survey. An example of the second type of survey is a collection of camera trap photographs taken in Suriname as part of a project by Conservation International. Suave has been applied in many other disciplines–you can find examples on the project web page.

This video uses the first type of survey and covers the user interface. The user interface has three main parts: the main gallery, the toolbar panel, and the list of survey questions on the left filter panel.

The gallery will display the items of all of the survey respondents at once.
Moving the mouse over the portraits will highlight a single respondent. Using the mouse scroll wheel will zoom in or out around the location of the cursor. Using the slider in the toolbar panel will also zoom in or out around the center of the screen. When zoomed in, the user can pan the gallery using click-and-drag.

The toolbar panel includes the title of the survey and the number of respondents who pass the current filter in the red count box. In this case, there is no filter so the total number of respondents is displayed. For demonstration purposes, we are using the data from 2,044 respondents in the General Social Survey from 2010. This is a large survey conducted in the US since 1972. It is designed to explore opinions of US residents on a wide range of topics, including government, marriage, race relations, happiness, religion, and environment. To the right of the zoom slider, there is a drop-down menu. It has the list of survey questions that can be used to sort the items in the main display. Next is the row of view selection buttons, which will be explained in later videos. The currently selected view is Grid View.

The filter panel includes a search bar and the list of questions. In the next video, we will explain how to use the user interface to explore survey responses.

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Video 2: Basic Navigation

Hello and welcome to the video tutorial series for the Suave program.

In this video, we will cover exploring survey responses with Suave.

From the toolbar panel, we can choose Grid View, Bucket View, and Crosstab View.

Grid View is the first view and displays the respondents in the order of the responses to the question selected in the drop-down. For textual questions, this is alphabetical order; and for numerical questions, this is in numerical order.

We can use the search bar to change the question options both below the search bar and in the drop-down. By typing in “age,” only questions with the search term “age” will be shown. Changing the option in the drop-down will sort the gallery based on that question’s responses. By selecting “age of respondent,” the first person in the gallery will be 18 years old, while the last person in the gallery will be “89 or older.” Clicking the red “X” by the search bar will clear it and display all of the questions again.

Let’s type in “race.” Selecting a response under a survey question will display a subset of respondents with a matching response. The number in gray denotes the frequency of that response. Currently, these responses are sorted alphabetically, indicated by “Sort: A-Z.” To sort the responses by the number of responses, click “Sort: A-Z” and it will switch to “Sort: Quantity.” By checking the boxes “white” and “black” under “race of household” we can see the subset of respondents in white or black households. We can see the current filter at the top in the toolbar panel. To remove this filter, we can uncheck the response, click the red “X” by the question, or just click “Clear All.”

Filters for dates work similarly, but can have custom ranges. Let’s search for “year of birth.” By scrolling to the bottom and checking the box “Custom Range,” we can specify the month, date, and year. The dates can be set by clicking the red calendar icon, which will display a larger gray calendar. To pick a date, use the drop-down menus for month and year and click the correct gray box for the day. Clicking “Prev” or “Next” will move to the adjacent calendar month. To demonstrate, we will apply a filter for the respondents who were born during World War II. The first date should be set to September 1st, 1939. Alternatively, dates can just be typed in. We will type in the second date as May 8th, 1945.

Filters for numerical data are applied differently. Let’s type in “age” again. Under the “age of respondent” question, there is a histogram with an adjustable slider. The slider handles on the right and left will set the minimum and maximum values. To create a filter for respondents 65 to 75, we will move the left slider handle until the lower range value changes to 65 and the right slider handle until the higher range value changes to 75.

Clicking on a single respondent in the main display will zoom in and bring up an information panel that displays all of their responses. One of the most useful features of the program is that you can zoom in on outliers and try to understand why they are different by looking at the responses they gave to other questions. Using the right and left arrow buttons on the information panel will move to an adjacent respondent. To close the information panel, click on the respondent in the main display again.

Clicking on a response in the profile will display all of the cards with a matching response. By clicking on “no” to the question “not married,” this will display all of the respondents who answered the same. Again, we can see this filter at the top in the toolbar panel. To remove this filter, we can just click “Clear All.”

Now we will introduce an example of exploring a sociological situation within Grid View. First, we will search for a question that asks the respondent if they find life exciting or dull. Let’s check the box for “dull.” Let’s apply another filter for people who responded “very happy” to their “general happiness.” Our list of people is down to five. How can we find a sociological explanation for this using our dataset? If we search for “religion,” we can see that all five of these individuals consider themselves protestant and were raised in protestant households. This observation could inspire further analysis.

In the next video, we will cover Bucket View, which displays the respondents in a histogram rather than a single array.

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Video 3: Bucket View

Hello and welcome to the video tutorial series for the Suave program.

This video covers Bucket View.

Bucket View is the second view in Suave. Selecting it will sort the respondents into a histogram based on the responses of the selected question in the drop-down. Let’s search for “r use computer.” Since we now have a question asking whether the respondent uses computers in the drop-down, putting it in Bucket View will split the respondents into two groups. Along the bottom, we can see the label of the response along with its frequency and percentage in the box in the lower left.

For variables with a large range of responses, Suave will automatically create intervals to group them together. Let’s use “age of respondent.” To view a specific range of responses the user can click on that interval, adding a filter on the left side. Now, the gallery only shows respondents who were 43 years old at the time of the survey.

To demonstrate how we can analyze patterns in survey responses with Bucket View, we will take a look at the relationship between happiness and work stress. Let’s search for “happiness” and select “general happiness” for the sorting variable. 16% of these respondents said they were “not too happy,” 58% said they were “pretty happy,” and 26% said they were “very happy.”

If we search for “stress” and specify for respondents with a low-stress work environment, this ratio changes significantly. Let’s clear this filter and try another one.

If we check “yes” for the “access to stress management” question, we can demonstrate a similar correlation.

If we search for “marriage” and make a filter for respondents with very happy marriages, our ratio is far different from the initial one.

In the next video, we will cover Crosstab View, which compares two variables at once.

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Video 4: Crosstab View

Hello and welcome to the video tutorial series for the Suave program.

This video covers Crosstab View.

Crosstab View is the third view in Suave. Instead of a single drop-down menu, there are now two drop-down menus. The first one specifies the variable in the x-axis, and the second one specifies the variable in the y-axis. Let’s put “general happiness” on the x-axis, and on the y-axis, “work arrangement at main job.” While in Bucket View we would have to compare each variable’s response individually, Crosstab View lets us view all of the respondents for both variables at once.

Each response has its own row or column and a red box with its percentage and frequency. The red box in the bottom left labeled “x^2” is the calculated chi-square value.

For our example, at a glance, we can see a typical ratio for “general happiness” for the “regular, permanent employee” respondents, but an atypical ratio for “independent contractor/consultant/freelance worker” respondents. Similar to Bucket View, filters can be easily applied by clicking on a specific interval and removed by either clicking the red “X” by the question on the filter panel.

Let’s try another one. If we change the y-axis variable to the survey question concerning whether the respondent considers him or herself a religious person, Crosstab View re-sorts the respondents according to the selected variables. Respondents who answered “not religious” to “moderately religious” exhibit similar patterns, but the “very religious” group has a jkkjjjjjjjjconsiderably high percentage of “very happy” individuals at 38%.

In the next video, we will cover Graph View, Table View, and Time View, three other view controls in Suave.

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Video 5: Map View

Hello and welcome to the video tutorial series for the Suave program.

This video covers Map View.

Map View is a view control that uses a Google Maps interface. For this video tutorial example, we are using a different survey that includes geographical information. This survey in particular includes 245 animal photos that were taken in the Central Suriname Nature Reserve.

Map View can be navigated using the controls on the left or interacting directly with the map. Clicking the arrows will pan the map. The slider adjusts the zoom. Panning and zooming is also possible with clicking and dragging and using the mouse wheel. In the upper right there are options to change the display to satellite imagery or to toggle terrain.

The right panel has a legend labeling the colored markers. Changing the selection in the drop-down menu will change the legend labels and markers according to the dataset. To demonstrate, let’s change the primary sort control to “moon phase.”

Clicking on an marker in the map will center the display around the marker and change the right panel to an information panel. TO exit the information panel, click the marker again.

Applying and removing filters works similarly in Map View as they do in other views. Let’s apply a filter for animals of the “puma” genus.

When a filter changes the number of markers visible on the map, the map will automatically zoom in and reposition itself.

In the next video, we will cover the settings menu.

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Video 6: Changing the Settings

Hello and welcome to the video tutorial series for the Suave program.

This video covers the settings menu.

The settings menu is found by clicking the link on the bottom of the filter panel.

By default, views only show the respondents who answered the question for the question currently selected in the drop-down menu. This can be changed by clicking “Settings” and checking the box called “Display missing values.”

To demonstrate this, if I go to Bucket View and change the drop-down selection to whether the respondent ever took a high school biology class, there are 107 who did not and 496 who did, totaling about 600 who responded to that particular question, which is a small fraction of the 2044 respondents of the survey. If we go into the settings menu and check the box for “Display missing values” and click “Submit,” we can see that another “bucket” was created for the respondents who provided no information for this question.

The other part of the settings menu changes the visible variables. To demonstrate this, I will first remove all of the variables by clicking “Deselect All.” I can double-click to select variables individually, or I can select large groups at a time by typing in a search term such as “income” and clicking “Select All.” By clicking “submit” and returning to the program, we can see that only the variables we selected are visible in the filter panel and the drop-down.

In the next video, we will explore additional research applications of Suave.

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Video 7: Research Applications

Hello and welcome to the video tutorial series for the Suave program.

This video covers more research applications.

We’re going to use “general happiness” as the main sort control. Many sociological studies focus on correlations between happiness and different lifestyles. Let’s open up Crosstab View and set “people fair or try to take advantage” as the alternate sort control. We can see that this variable has a large effect on general happiness.

Another interesting one is “promotions are handled fairly.” The respondents who felt that other people were unfair were much less frequently in the “very happy” category.

Let’s put “job satisfaction in general” in the primary sort control and “respondent works for whom” in the alternate sort control. Examining the response of “non-profit organization” reveals that none of these individuals have poor job satisfaction and that 52% consider themselves “very satisfied.” Meanwhile, 4% of respondents who work for “private companies” stated they were “not at all satisfied” and only 42% of respondents stated they were “very satisfied.”

Let’s move on from the sociological study to an ecological one. Here we can use Suave to study patterns in these animals. In Crosstab View, we can easily view information an environmental researcher may need. If we set the primary sort control to “temperature” and the alternate sort control to “species.”

Here we can see that even photos taken of the animals on different days have similar patterns in what temperature they were taken in. This feature quickly and easily displays what temperatures result in what reactions from these species. This information has valuable implications for forming hypotheses relating to how these species are able to adapt to changing environmental factors such as climate change.

That concludes the video on advanced research applications of Suave. The Suave program website is besuave.azurewebsites.net and includes many other resources for its users. Thank you for your attention.

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