Abstract The American Intellectual Union collected data from its employees and using that information it is important to examine each and every aspect of the data to get a clear picture of the makeup of the company’s employees. Throughout this report one quantitative and one qualitative variable will be analyzed. Introduction Gender and job satisfaction are two vital components in the workplace to help managers understand the behavior of their employees. Within the data selection, we get to choose from two points of information, qualitative and quantitative data. Chosen Variables There are several other variables that can be collected to be useful to a business but for the purpose of this report, it will focus only on gender and extrinsic job satisfaction. Difference in variable types It is important to know what the difference in the two data sets are before one can make an appropriate choice. Understanding the difference is quiet simple. Qualitative data deals with things that cannot be measured or things that are descriptive; such as smells, colors, or tastes (Bluman, 2010). One can think of it as ‘qualit’ative = ‘qualit’y. The gender is a great example of qualitative data. The codes are set to male as 1 and female as 2. Quantitative data deals with things that are measured and numbers, such as speed, ages, height, time, length, etc. (Bluman, 2010). One can think of it as ‘quantit’ative – ‘quantit’y. The extrinsic job satisfaction shows an example of this by the values provided in a range from 1 to 7. Mean, median, and mode are referred to as the measures of central tendency. The mean is simply the average; the sum of all the set data divided by the number of that data. The median is the middle; if the data was put in numerical order, the number in the middle would be the median. The mode is the number that appears most frequent. In some cases, it is possible to have no mode or to have more than one (Schultzkie, 2011). Explanation of descriptive statistics The median is 1. This measure is actually meaningless. While there’s a gender group 1, it cannot be sorted from smallest to the largest. The mode is 1. This is useful for this group. It suggests that most of the people in this group are 1; in this case male. The mean is 1.39. This is meaningless as well. Since there are only 2 groups, there can’t be a 1.39 group. The standard deviation is 0.49 and the variance is 0.24. Explanation of descriptive statistics The median is 5.6. This is useful for this group. The mode is 5.6. This is also useful in this group. The mean is 5.413888889. This is valid for a variable. The standard deviation is 0.488234591 and the variance is 0.238373016. Description of Chart A pie chart can be used to show part of something and how it relates to a whole. This type of chart is needed when showing percentages. It takes a circle and divides it into pieces, one per each category. The width of each piece is determined by the points in each category. For.

1. Abstract
The American Intellectual Union collected data from its
employees and using that information it is important to examine
each and every aspect of the data to get a clear picture of the
makeup of the company’s employees. Throughout this report
one quantitative and one qualitative variable will be analyzed.
Introduction
Gender and job satisfaction are two vital components in the
workplace to help managers understand the behavior of their
employees. Within the data selection, we get to choose from two
points of information, qualitative and quantitative data.
Chosen Variables
There are several other variables that can be collected to be
useful to a business but for the purpose of this report, it will
focus only on gender and extrinsic job satisfaction.
Difference in variable types
It is important to know what the difference in the two data sets
are before one can make an appropriate choice. Understanding
the difference is quiet simple. Qualitative data deals with things
that cannot be measured or things that are descriptive; such as
smells, colors, or tastes (Bluman, 2010). One can think of it as
‘qualit’ative = ‘qualit’y. The gender is a great example of
qualitative data. The codes are set to male as 1 and female as 2.
Quantitative data deals with things that are measured and
numbers, such as speed, ages, height, time, length, etc.
(Bluman, 2010). One can think of it as ‘quantit’ative –
‘quantit’y. The extrinsic job satisfaction shows an example of
this by the values provided in a range from 1 to 7.
Mean, median, and mode are referred to as the measures of
central tendency. The mean is simply the average; the sum of all
the set data divided by the number of that data. The median is
the middle; if the data was put in numerical order, the number
in the middle would be the median. The mode is the number that

2. appears most frequent. In some cases, it is possible to have no
mode or to have more than one (Schultzkie, 2011).
Explanation of descriptive statistics
The median is 1. This measure is actually meaningless. While
there’s a gender group 1, it cannot be sorted from smallest to
the largest.
The mode is 1. This is useful for this group. It suggests that
most of the people in this group are 1; in this case male.
The mean is 1.39. This is meaningless as well. Since there are
only 2 groups, there can’t be a 1.39 group.
The standard deviation is 0.49 and the variance is 0.24.
Explanation of descriptive statistics
The median is 5.6. This is useful for this group.
The mode is 5.6. This is also useful in this group.
The mean is 5.413888889. This is valid for a variable.
The standard deviation is 0.488234591 and the variance is
0.238373016.
Description of Chart
A pie chart can be used to show part of something and how
it relates to a whole. This type of chart is needed when showing
percentages. It takes a circle and divides it into pieces, one per
each category. The width of each piece is determined by the
points in each category.
For the gender group, you can see the pie chart above. The
chart shows 22 males and 14 females. This helps confirm that
the mode was 1 showing there are more males than females in
the workplace for this company.
Chart/Graph for quantitative variable
Description of Chart
A histogram shows a graphical display of classified frequencies.
It’s a table that shows what proportions fall into several or
many specific categories. It contains intervals for values that
the variables take and each are associated with a bar that is

3. represented by the number of points that fall into that interval.
For extrinsic job satisfaction, a histogram was used. As seen
above, the intervals start at 4.6-5 and end at 6.6-7.
Explanation of standard deviation and variance
The measures of variability and spread of distribution
about the means are standard deviation and variance. The
average amounts by which the scores in distribution differ from
means, ignoring signs of difference is called standard deviation.
The square root of variance is called standard deviation. We
already found out that the mean of the qualitative variable is
useless; therefore the qualitative variable a standard deviation
and variance cannot be used for the mean, but can be used for
the quantitative variables.
Importance of charts and graphs
Graphs and charts are illustrations that represent numerical
quantities and facts in a visual form. Graphs are used for many
types of data and can be done in several types such as circle,
line, or bar. They are vital because they make it easier when
comparing numbers and making facts more understandable.
They make raw data easier and quicker to read and can display
the important information of that data. Charts can show large
amounts of data in a single graph or chart and make it easier to
comprehend the relationship between the different parts of all
the data (Bluman, 2010).
Conclusion
After investigating two variables; gender and extrinsic, it
can be seen that the company is made up of mostly males and
noticed that most of the measures are actually useless. With
extrinsic it was seen that median and mode were the same and
the mean was slightly different indicating a pretty normal
distribution.
Moral Dilemma

4. The moral dilemma in this case is an attorney’s emotional
conflict with his professional obligations. Attorney Frank
Armani empathizes with father of a victim and debates with
disclosing confidential information that would breech the client/
attorney agreement. “A right versus right situation occurs when
one is faced with an urgent and intricate situation that makes
you make choices about your integrity and moral
character” (Badaracco Jr., 2009). The client of the attorney has
the right to a fair case. The rights of the client are not to be
violated by the attorney due to moral conflicts of the attorney.
“The Constitution of the United States of America and
Amendment V has the strongest claim for due process of law
and rights to liberty until proven guilty in a court of law where
breaking the right to confidentiality would harm due process
and rights to liberty (Badaracco& West, 1990).
Model
I made my decision through the reading Right vs. Right. The
attorney was faced with protecting his client and disclosing
confidential information and sympathizing with a father. The
attorney had to chose between integrity and moral character this
is a clear right vs. right.
Right vs. Right
The decision I made was right vs. right. Attorney Frank
Armani’s moral obligation is to his client. As an attorney you
must honor client and attorney confidential agreements. “The
requirement that an attorney may not reveal communications,
conversations and letters between himself/ herself and his/her
client, under the theory that a person should be able to speak
freely and honestly with his/her attorney without fear of future
revelation” (dictionary law, 2013).Outside of the legal world it
is hard to understand how not disclosing important information
is morally correct. Society would have it that giving the father
some peace and empathizing with his lost is morally correct.
However, sometimes client information may conflict with
personal morals. Since it is important to practice good ethics in
business it is essential to honor all legally binding documents

5. despite personal emotions.
Personal application
This week’s assignment can be applied in real life. Do legal
obligations trump personal obligations? We have legal
obligations as citizen and in some professions. However, we all
have emotions and empathize with others. As professionals in
business we must make ethical choices and abide by the laws set
before us. This applies to personal lives in when we have
sensitive information that is not ours to disclose. In our
professional lives we protect our jobs by following the
guidelines and provisions of our jobs. In medical offices we
cannot disclose patient information without the consent of the
patient. Lawyers, family members, press ect. often attempt to
retrieve confidential patient information. If a person inquires
information on a patient regardless of the reason we cannot
even disclose if the patient is in the building. It is an attempt to
protect the patient’s privacy. This scenario applies to the
Armani case and the medical field.