In this week’s Discussion, you determined the benefits of visually displaying your data. You also learned that different types of data require different visual displays to adequately “tell the story” of the phenomena. Although the Discussion was difficult, what is even more difficult and challenging will be deciding on how best to display the data for presentation purposes. As you move further along in your dissertation or doctoral study, you will find that displaying data will be critical component in presenting a robust and clear capstone project.
For this Introduction to Quantitative Analysis Assignment, you will explore how to visually display data for optimal use.
To prepare for this Assignment:
- Review this week’s Learning Resources and consider visual displays of data.
- For additional support, review the Skill Builder: Unit of Analysis and the Skill Builder: Levels of Measurement, which you can find by navigating back to your Blackboard Course Home Page. From there, locate the Skill Builder link in the left navigation pane.
- Using the SPSS software, open the Afrobarometer dataset or the High School Longitudinal Study dataset (whichever you choose) found in this week’s Learning Resources.
- From the dataset you chose, choose one categorical and one continuous variable and perform the appropriate visual display for each variable.
- Once you visually display each variable, review Chapter 11 of the Wagner text to understand how to copy and paste your output into your Word document.
For this Assignment:
Write a 2- to 3-paragraph analysis of your results and include a copy and paste of the appropriate visual display of the data into your document.
Based on the results of your data, provide a brief explanation of what the implications for social change might be.
Use appropriate APA format. Refer to the APA manual for appropriate citation.
By Day 7
Submitthis Introduction to Quantitative Analysis: Visually Displaying Data Results Assignment.
General Guidance on Data Displays
Tuesday, February 19, 2013 Capstone Writing , Dissertation , Tech Tips 10 comments
By Tim McIndoo, Dissertation Editor
According to APA style, a table has a row–column structure; everything else is called a figure (chart,
map, graph, photograph, or drawing). This post won’t discuss the creation of a figure—the
possibilities are endless—except to say that figures are not enclosed in a box (as they are in the
APA Publication Manual). If you’ve not created a table before, it may take a little practice.
Here’s guidance on the (a) keyboard steps to create a table, (b) the opposite formatting of tables
and figures, and (c) the APA and Walden requirements.
A. Keyboard steps to create a table
In the Word toolbar, go to Table > Insert > Table > Table size. Pick the number of columns and rows
you think you’ll need. Make sure to add one each for the headers of the table and the stub column
(which lists the individual items).
Under AutoFit behavior, try AutoFit to Contents. That way, your table will automatically expand to
fit whatever data you put in the various cells. You can always change it later.
Under Table Style, try Table Normal. It’s standard, it’s simple, it’s clean.
B. Formatting tables and figures (and the three forms of notes used at the end of a table). Note
how tables and figures are formatted in opposite ways.
C. APA and Walden requirements
•
All cells in a table, and callouts in a figure, use sentence case.
•
APA style does not use boldface type or vertical lines in tables.
•
Do not put a box around a figure.
•
Make titles and captions concise, clear, and expressive. (APA 5.12 & 5.23)
•
Do not split a table unless it is too large to fit on one entire page. It works best to start
tables at the top of a page; that way, there will generally be enough space. It’s OK if the table
appears on the page following its first mention.
•
If a table is, indeed, too large for one page, then type (table continues) under the
table, flush right. Repeat the column headings (not the table title) at the top of the new page.
•
If a table or figure takes up 75% or more of a page, then set no text on that page.
•
If needed, use a different point size (or font) for the text of the table or figure,
but in any event, do not use smaller than 8-point type.
•
For numerous examples of tables, see APA Publication Manual, pp. 129–150; for numerous
examples of figures, see pp. 152–166. I would encourage studying them all closely. You can also
see several examples on the Writing Center website.
———————————————————————————————————
Tim McIndoo, who has been a dissertation editor since 2007, has more than 30 years of
editorial experience in the fields of medicine, science and technology, fiction, and education.
When it comes to APA style, he says, “I don’t write the rules; I just help users follow them.”
Share the knowledge!
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10 comments :
1.
AnonymousSeptember 3, 2016 at 11:51 PM
I could not find anywhere in the apa Pub manual or at the Walden writing
site, how to put the table on the page – is it centered on the page or flush
left and must the table extend all the way to the right margin even if there
is not enough columns in the table to get it there
Reply
Replies
1.
Walden Writing CenterSeptember 6, 2016 at 9:12 AM
Thanks for your question! Tables should be flush left, but do
not need to extend all the way to the right margin if there are
only a couple of columns. Here’s a link to a page with more
information
on
table
formatting:
http://academicguides.waldenu.edu/writingcenter/apa/table
sandfigures/tables
Reply
2.
UnknownJune 20, 2017 at 8:04 PM
Is there a rule at Walden to use consistent font size for all tables? I have a
table that can be well represented by using 8 pt. Arial. However, most of
my tables can be represented with 11 point font. Thanks.
Reply
Replies
1.
Walden Writing CenterJune 21, 2017 at 1:06 PM
This is a great question, Dorothy. APA says that unless the
university or publisher has other requirements, 12 point font is
recommended. However, font size in tables can be adjusted to
meet university or publisher requirements/preferences. For
students, it is best to ask your instructor or chair or whoever
the final audience is for the document to see what font sizes
are appropriate. Thanks for stopping by!
Reply
3.
AnonymousSeptember 5, 2017 at 5:31 PM
I’m using a bar chart to display nominal data and to discuss the pros and
cons of why I chose that particular display. How do I cite the graph in the
text? What is the APA recommendations for citing the display in my
references? The APA examples given in this helpful hint appears to focus on
tables instead of charts. Thank you.
Reply
Replies
1.
Walden Writing CenterSeptember 6, 2017 at 9:47 AM
Data displays would be labeled and then the label would be
cited as you refer to the data display (for example, “Table 1”
or “Figure 1”). If you are not including the data displays in the
paper but in an appendix, then the appendix would be cited
(for example, “Appendix A”). Data displays would not be
included in the reference list. Our website provides additional
examples for labeling and formatting tables and figures:
http://bit.ly/2wHH7Il.
Reply
4.
UnknownDecember 4, 2018 at 4:00 PM
I am trying to remove the box from around my figure that I created from
SPSS. Thanks
Reply
Replies
1.
Walden Writing CenterDecember 5, 2018 at 9:32 AM
You’re welcome! We’re glad this post helped. The Academic
Skills Center also has Microsoft Word support if you have any
issues with MS Word formatting: http://bit.ly/2KVbB0x
Reply
5.
AnonymousDecember 4, 2018 at 5:57 PM
The blog post says when continuing a table to the next page not to put the
table title. I believe Walden wants us to include the Table title plus
“continues” above the continuation of the table. Please advise.
Reply
Replies
1.
Walden Writing CenterDecember 5, 2018 at 9:26 AM
It’s best to not split a table onto two pages; instead start the
table on a new page. If a table is large and covers over a page,
including “table continues” and repeating the column headings
on the next page can help readers follow the material. If your
professor or committee recommends differently, I would defer
to
your
professor
or
committee.
You can also contact the Walden editor team for guidance on
data displays for capstone work such as doctoral dissertations
and studies: editor@waldenu.edu.
MODULE 5
VISUAL DISPLAYS FOR CONTINUOUS VARIABLES
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•
previous: Visual Displays of Categorical Variables: Summary
•
next: Identifying Continuous Variables
•
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20
Current Module | Pages 20 – 23
Visual Displays for Continuous
Variables Introduction
Learning Objectives
•
Evaluate visual displays of data for continuous variables.
A researcher conducted a study in which she observed students’ scores on an examination. One of the
first steps in analyzing a sample of data is to examine the distribution of values for variables in the data
set. The distribution of the data tells her about the frequency with which various values are observed.
Distributions can be examined in visual displays such as tables and graphs. A good graph or table is
informative and allows researchers to identify and communicate important characteristics of the data.
Different approaches are taken for visually displaying categorical and continuous variables.
Visual Displays of Categorical
Variables Introduction
Learning Objectives
•
Evaluate visual displays of categorical variables.
A researcher asks students how they perceived their body weight. They might respond
with overweight, underweight, or just about right, in which case each student is a unit of analysis, the
answer options represent categories of responses, each answer option is a value, and all of the students’
responses comprises a data set. One of the first steps in analyzing a sample of data such as this one is
to examine what is referred to as the distribution of values for the data set’s variables.
Visual displays of data help researchers communicate the distribution and other key information (the
story they are telling with their data) both effectively and efficiently, including for their own exploration. Put
another way, visual displays of data allow researchers to quickly identify interesting aspects of their data
(for example, are the study’s participants predominately satisfied with their body weight?), and to do so
more efficiently than merely using words. Researchers take different approaches for visually displaying
categorical and continuous variables. This skill builder focuses on visual displays for the former.
Identifying Categorical Variables
Categorical variables are those that have a small number of possible values. Usually, categorical
variables involve nominal or ordinal levels of measurement. For example, political party affiliation is an
example of a nominal, categorical variable. This variable places individuals into one of just a few
categories (e.g. Democrat, Republican, or Independent). An example of an ordinal, categorical variable is
highest grade completed, with categories of less than high school, high school diploma, and more than
high school. Again, this variable has just a small number of possible values. You will typically use
categorical methods of displaying data, such as a bar chart or a pie chart, when the number of categories
is less than 10 or 12. If there are too many categories, the displays become messy and difficult to read.
Also keep in mind that pie charts and bar charts are not typically used for non-categorical variables. An
example of a non-categorical variable would be students’ percentile ranking on a standardized math test;
this variable has a large range of values and students aren’t simply placed into one of a limited number of
categories.
Learn by Doing
Hints, displayed below
Which of the following variables would (YES) or would not (NO) be considered
a categorical variable amenable to a categorical visual display?
Table of multiple choice questions
Yes
No
Weight
perception
with values
of
underweight,
about right,
and
overweight
An
individual’s
weight
measured in
whole
pounds
Hair color
coded as
black,
brown,
blonde, red,
or other
Getting back to the study of body image, presume that the researcher actually has a random sample of
1,200 U.S. college students who were asked the question of how they perceive their body weight as part
of a larger survey. The following table shows part of the responses collected:
Body Image
Student
Body Image
student 25
overweight
student 26
about right
student 27
underweight
student 28
about right
student 29
about right
Here is some information that would be interesting to get from these data:
•
What percentage of the sampled students fall into each category?
•
How are students divided across the three body image categories? Are they
equally divided? If not, do the percentages follow some other kind of pattern?
There is no way to answer these questions by looking at the raw data, which are in the form of a
long list of 1,200 responses, and thus not very manageable. However, both of these questions can
be easily answered once the researcher summarizes how often each of the categories occurs and
looks at the frequency distribution of the different values for the variable Body Image.
Creating a table that presents the different values (categories) for the variable Body Image is the first
step to take to summarize the distribution of a categorical variable. For example, the table below
shows how many times the value “About right” occurs (count), and, more importantly, how often this
value occurs (relative frequency) as a percentage. To convert the counts to percentages, divide the
frequency (855) by the total number of observations (1200) to obtain the relative frequency, and
multiply by 100 to convert to a percentage.
Body Image Distribution
Category
Count
Percent
About right
855
(855/1200) * 100 = 71.3%
Overweight
235
(235/1200) * 100 = 19.6%
Underweight
110
(110/1200) * 100 = 9.2%
Total
n = 1200
100%
Did I Get This
What are the correct percentages for each of the two remaining values
(“Overweight” and “Underweight”) for the Body Image variable displayed in the
table below? Drag each percentage to its correct location.
Accessible mode
Screen reader users: use the accessible mode button above and use alt+down arrow to open the combo
boxes.
Category
Count
Percent
About right
855
(855/1200) ∗ 100=71.3%
Overweight
235
Underweight
110
Total
n=1200
100%
(235/1200) ∗ 100=19.6%
( 110/1200) ∗ 100=9.2%
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•
previous: Unit 2: Visual Displays for Categorical and Continuous Variables
•
next: Visual Displays of Categorical Variables: Graphical Displays
•
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