This is a final presentation lab report I wrote for my Marketing 460: Information & Analysis class. Throughout the semester, my class conducted a UT-wide survey that asked questions ranging from demographic questions to specific questions about technology use. Then, utilizing SPSS, a statistical analysis program, my group and I analyzed the data we found and organized it into a presentation on the topic of women in the digital age. We designed the Lab Report in Canva.

1. WOMEN IN THE
DIGITAL AGE
REPORT BY KAITLYN SLACK, ELIZABETH
LYBRAND, & MIRA McKEE
MKT 460
JOHN DAVIS
TTH 12:30-2:00
A Data Analysis Project
Regarding UT Females and Their
Digital Usage

2. OUR EXPLORATION TOPIC
What describes a woman in the digital age? What
attributes define them, how do they interact with their
technology, and what makes them different from other
groups of people?
EXECUTIVE SUMMARY
CONCLUSION
OUR ANALYSIS: CROSSTABS
OUR ANALYSIS: REGRESSION
OUR ANALYSIS: CLUSTERS
POSSIBLE EXPLANATIONS
AREAS TO EXPLORE
CONTENTS:

3. A woman in the 21st century can be described by many characteristics.
Some may be working, some may stay at home, and some may do
both. With technology today, women have endless opportunities to
succeed in whatever they want to, but some may take the tool too far.
"Women are more at risk in developing addictive behaviors to activities
involving elements of social interaction" (Andreassen, 2017). This
describes the root of our analysis. Why are women more susceptible to
the social media drug? What characteristics make up a woman in this
day and age? These are the questions we set out to explore with this
data analysis.
EXECUTIVE SUMMARY
We began by running many crosstabs separating the data by gender,
especially targeting 5 questions that we thought would differentiate
them. The crosstabs showed us that on average, females are more
addicted to social media than males, they get their phones younger,
they're more distracted by having their phones out while studying,
and they are more productive with their technology than males.
A final analytical step we took was to look into the cluster analysis and
personas. We found Persona 3 to be the most feminine and
compared their data to the data of all the women in our data set. They
didn't use their phones much less, just for more productive activities.
After all of our analysis, we found that we needed a little more
information if we wanted to dive deeper into the data. We thought of
a few questions that would help us in our analysis of a typical woman
in the digital age.
We then ran a stepwise regression to tell us more about the actual top
indicative variables for a woman at UT. Our regression came back
with 10 variables, but the top 5 were gaming, pretending to be on their
phone, feeling guilty about their social media usage, the number of
hours a day spent on their phone, and wanting to cut down their
social media usage.

4. CROSSTABS
OUR ANALYSIS
Our sample includes both males (48.4%) and females (51.6%) on the UT
campus. In order to explore the characteristics of a female in the
digital age, we decided to run some crosstabs comparing males and
females. First, it is interesting to note that masculinity and femininity
are positively correlated with gender; in other words, males are more
likely to be masculine, and vice versa. Thus, women in the digital age
seem to adhere to a conventional view of gender. Also, more
traditionally, females are slightly more extroverted in males.
REGRESSION ANALYSIS
Then, the crosstabs started to get more interesting. With about 75% of
our respondents getting their first mobile smart device before the age
of 16, we noticed that more females tended to receive these devices
earlier than males. What might the impact of earlier use be on a
woman of the digital age? This led us to explore several behavioral
characteristics with our crosstabs.

5. CROSSTABS
OUR ANALYSIS
REGRESSION ANALYSIS
they felt addicted to social media (108) and had tried to decrease the
amount of time they spent on social media (109). Again, the difference
in males and females was emphasized by the males’ response. Men
strongly do not feel addicted to social media (122) and have not tried
to decrease the amount of time they spend on social media (118).
First, we looked at productivity
between males and females. The
index from this crosstabs is
inclusive, as both productive and
unproductive males and females are
within 6 points of the baseline.
Next, we looked at how distracted men and women are by social
media. At first, it appears that there is not much difference between
men (distracted index = 93) and women (106). However, this
difference is made more significant by males’ response that they are
not distracted by social media (not distracted index = 127, women =
75). There are over 50 points between men and women!
The fact that women are more easily
distracted by their devices and social
media led us to our next crosstabs,
looking at addiction and desire to cut
down on social media by gender. We
saw that females agreed more than
males with both of the sentiments—
With these indices, we felt like we had a basis of understanding about
a woman in the digital age. However, we wanted to know more about
what variables were most significantly correlated with gender.

6. REGRESSION ANALYSIS
OUR ANALYSIS
Moving forward with our analysis, we wanted to explore whether or
not the 5 original questions that we used to differentiate were
actually among the top 5 variables. We ran a stepwise regression
analysis with Gender as the Dependent Variable. Through this
procedure, we found out the top 10 traits of a woman on UT's
campus, in which direction (positively or negatively) the trait implies
an individual is likely to be a woman, and how strongly an identifier
of a woman the trait is. Below are the top 5 most indicative traits of
women at UT.
REGRESSION ANALYSIS
We were a little surprised to find some of the results of the
regression analysis we ran. Gaming was the most indicative trait of
UT women, but correlated negatively (meaning if an individual
spends less time gaming, they're more likely to be female. We
assumed that "pretending to be on your phone to avoid talking to
people" was a gender-neutral phenomenon, but apparently it's more
common in women! The last three variables in the top 5 did not
surprise us at all, however. Through our crosstabs, we saw that
women were more addicted and likely to want to cut down, so the
regression confirmed our assumption there.

7. CLUSTER ANALYSIS
OUR ANALYSIS
REGRESSION ANALYSIS
After we explored differences between females and males, we wanted
to look at the personas to see if there were any significant trends.
We noticed that Persona 3 was the most female, so we decided to
compare and contrast females in general to Persona 3. Most
significantly, we noticed that Persona 3 was the most productive
persona. This seemed to be a contradiction! How can females be both
the second most distracted by their phones and the most productive?
We then set out to figure out why this persona was more productive
than the average female. We ran a regression to find the variables
that most significantly affected productivity among women. Our
results showed us that this persona, this group of women, were only
using their devices for productive activities (R2 = 18.7%). In other
words, this group of women does not use their devices for social
media or entertainment. This difference points to why other women
are more distracted—they are using their devices for a wider variety
of purposes, naturally increasing the probability of distraction.

8. POSSIBLE EXPLANATIONS
In order to explain the digital characteristics of a woman that we
discovered, we came up with a few opinions as to why the women act
the way they do.
GOT THEIR PHONES YOUNGER:
To answer the question as to why women got their phone earlier, we looked
at it from a parent's perspective. Young women are more vulnerable in
general compared to young men, so they get their phones earlier in order to
be able to call their parent at any time. Parents know where their child is at
all times through the tracking capabilities of the smartphone. One other
explanation we had was the pressure that young women feel as they go
through grade school to fit in (e.g., by having a phone like their friends).
MORE DISTRACTED WHILE STUDYING:
We feel the reason as to why women are more distracted by their phones
while studying is because they do not consider social interactions as
“distractions.” They feel that texting a friend is a necessary reason to
interrupt their studying. Women also turn to social media where men turn
to gaming as their distraction of choice while studying.
MORE ADDICTED TO SOCIAL MEDIA:
The social media gender divide in today’s society is part of the reason
women are more addicted to social media than men. They feel more
pressure to take care of their image they cater to that on social media
platforms. The fact that social media can be accessed at any time of the day
also shows why women are more addicted.

9. POSSIBLE EXPLANATIONS
PRETEND TO BE ON PHONE:
When it comes to women pretending to be on their phone to avoid certain
people can be explained through safety issues. They tend to feel safer when
they do not talk to strangers while walking alone. Women also tend to
worry about being on time more than men so this could explain why they'd
avoid talking to people while walking to class or to a meeting.
MORE GUILTY ABOUT BEING ON SOCIAL MEDIA:
The last topic we discussed was why women feel more guilty for being on
social media. We believe today’s society creates a standard for young women
in that they are the reason social media sites are so popular. People do not
always see their social media use as a good thing. The social media
platforms such as Instagram and Twitter are considered to be a leisure
activity for women, so they feel more guilty about scrolling through their
feed.
AREAS TO EXPLORE:
As we analyzed our data, we realized that if we could do this survey
and research project over again, we would've done some things
differently. If we had asked a few more questions in our survey we
could come up with better answers for our questions. For example,
we would've liked to know a person’s description of ‘constructive
activities’ because we felt that women could've had a different
idea/definition than men. Additionally, distinguishing these
categories of smartphone capabilities would help us to have a better
description of a woman in this digital age. Finally, we thought women
might be more honest if being surveyed by a woman, so that could've
been an unintended variable influencing certain answers.

10. CONCLUSION
Only time and further analysis will tell if our findings
contribute to problems faced by women in the digital age, or
if they are simply facts of life for females at UT.
Through our experiences as women growing up in a fast-paced and
ever-changing world, we had an intense curiosity about the defining
characteristics of these 'women in the digital age.' We ran many
crosstabs between men and women that told us about some of the
differences between the genders. Next, we ran a stepwise regression
that told us the top 10 most indicative variables of a woman on UT's
campus. We then explored the cluster analysis that created four
personas and analyzed the difference between Persona 3, a highly
female persona, and the rest of the female population. Finally, we
gave possible explanations for our findings and even listed some
areas to consider exploring and questions to consider asking in the
future.
Thanks to our newfound understanding of women in the digital age,
we have a better gauge of the world, half of UT's campus, and
ourselves.