Basic Analysis (MBA)

This document provides a basic analysis of MBA data, including data handling, descriptive analysis, and methods used. It also includes results and references.

Running head: Basic Analysis (MBA)
1
Student
Institution
Course
Date

Basic Analysis (MBA)
2
Table of continent
Data handling..........................................................................................................................................3
Descriptive Analysis.....................................................................................................................................4
PART 2.......................................................................................................................................................14
Methods....................................................................................................................................................14
Results.......................................................................................................................................................14
References.................................................................................................................................................15

Basic Analysis (MBA)
3
1. Data handling
a) Below is the screenshot of the variables entered in SPSS. It contains 24 rows and six rows which
include: Age, Exam Marks, Paper Marks, Sex, Year in college, IQ
b) The screenshot below shows the variable labels, value labels and scaling indicators to the
variables
Descriptive Analysis

Basic Analysis (MBA)
4
a) This part aims to use descriptive to summarize the metric variables. Below is the output of
the analysis (Verma, 2012)
b) This part aims to record sex variable such the male are assigned the value zero, and the
female is assigned the value one. Below is the screenshot of the results
c) This part aims to use descriptive to summarize non-metric variables. Below are the results
from the output
It has been obtained that out of the total students 11 (45.8 %) are Male and 13 (54.2 %) are female.

Basic Analysis (MBA)
5
d) Below is the pie chart for Year in college variable (Janert, 2010)
e) This part aims at obtaining the histogram of IQ and including the normal distribution curve.
Below is the result of the output obtained.

Basic Analysis (MBA)
6
f) This part aims to create a scatter diagram with IQ on the x-axis and exam grade on the
y-axis and conclude what the result implies.

Basic Analysis (MBA)
7
From the graph, one can notice that as the IQ increases also the examination marks increases.
Therefore, IQ and examination marks are directly proportional, and they are positively
correlated. Lastly, a unit increase in IQ increases the examination by 0.341 (R linear).
g) This part aims to sketch a scatter plot with Sex as the x-axis and IQ as the y-axis.
Later, the results should be concluded. Below is the graphical representation of the
results.
The scatter plot above shows no relationship between male and female concerning IQ.
Compute the mean IQ for males and females. Conclusion
h) This part aims to compute the mean IQ for males and females later, the results should be
concluded

Basic Analysis (MBA)
8
The mean IQ for the Male was obtained to be 101.18, and that of women was obtained to be 101. It can
be noticed that the two means are almost similar which means that there is no big difference between
the mean of Male and the female. However, there is a slight difference in the standard deviation. This
means that the Male had a higher IQ compared to Female; that’s why there is a slight difference.
i) This part aims to create a dummy variable IQdum such that IQ with values equals or greater
than 100 are assigned the value 1, and the rest are assigned the value 0. Below is the
screenshot of the results obtained
j) This part aims to create a cross tabulation between IQdum and Year in college. Below are the
results obtained

Basic Analysis (MBA)
9
1. Data Analysis
a) This part aims to determine whether the exam grade was significantly higher than 75
The answer is yes. The exam grade was significantly greater than 75; this is because the mean grade
obtained is 82 which is significantly greater than 75.
b) This part aims to determine whether there is a significant difference between the exam grade
for Male and Female. An Independent sample test is used to test the assumptions. Below is the
output obtained from the independent sample test

Basic Analysis (MBA)
10
To test our question, we check on the significance value. In this scenario, the significance value obtained
is 0.087. Since the value is greater than 0.05, then it can be concluded that it fails to show a statistical
significance to say that there is a difference in exam grade between the Male and the Female. Therefore,
there is no significant difference in exam grade obtained between the Male and Female.
c) This part aims to determine whether there is a significant difference between exam grade and
paper grade. Below is the output of the results (Rasch, Kubinger, & Moder 2011).

Basic Analysis (MBA)
11
To answer the question, we look at the significance value. In this case, the significant value is given by
0.328. Since the significance value is greater than 0.05, then it fails to have statistical evidence to show
that there is a difference between the exam grade and the paper grade. Therefore, it can be concluded
that there is no significant difference between the exam grade and the paper grade. However, there is
evidence that the two variables are related. This is because the correlation obtained is 0.626. This means
that the two variables have a 62.6 % relationship.
d) This part aims to determine whether there is a significant difference between the paper grades
between the four-year groups. Below is the output obtained
The table below shows the sum of squares of, mean squared and significance values between the
groups and within the groups. To test whether there is a significant difference between the paper
grades between the four-year group, we focus on the significance values. The significance value
obtained is greater than 0.05, and therefore it fails to show any statistically significant difference
between the paper grades between the four years groups and therefore, it can be concluded that
there is no significant difference between the paper grades between the four-year groups.
e) This part aims to determine whether the representative of the IQ level shows that 50 % of the
population has IQ level less than 100 and the remaining 50 % has IQ greater or equal to 100.
Below is the results of the output

Basic Analysis (MBA)
12
From the results above, it is evidence that the sample does not represent 50 % of those with IQ less
than 100 and the remaining 50 % with IQ greater or equal to 100. This is because the table shows
that those who had IQ less than 100 were 58.3 % and not 50 %. Likewise, those who had IQ greater
or equal to 100 were 41.7 % and not 50 %.
f) This part aims to determine the correlation matrix of the relevant variables and discuss the
results. The variables selected were exam grade, paper grade, and IQ. Below is the output of the
results (Yan et al. 2013).

Basic Analysis (MBA)
13
It can be seen that the exam marks and paper marks had a high positive correlation of 62.6 %. The correlation
between the exam marks and IQ is a medium and positive, i.e. they correlate 58.4 %, and the correlation
between IQ and the paper marks is a strong and positive, i.e. 74.9 %.
Do a multiple regression analysis to explain the variance in paper grades using the independent
variables of age; sex (dummy coded); and IQ, and interpret the results
g) This part aims to conduct a multiple regression analysis to explain the variance I paper grade
using age, sex, and IQ as the independent variables and then to interpret the results.
Below are the results obtained after the regression
The results show that 62.4 % of the independent variables explained the variance in the paper grades.
Also, a grade of 43.328 is not affected by age, sex, and IQ. 1 unit of IQ increases the paper grade by 2.93.
One unit of age increases the grade by 0.412.

Basic Analysis (MBA)
14
PART 2
Methods
The data collection involved five participants. Participant 1 was a male and senior executive. A face to
face interview was conducted and he agreed to the recording session. He gave out concise answers and
he said that enjoyed working at the IT Company. He gave out two main points: that people can either
get rewarded or get punished when working. He said that one can get rewarded due to client’s
satisfaction, technical knowledge and also due to general performances. On the other hand one can be
punished due to dishonesty and ethical problems.
Participant 2 is a female and she too agreed to the recording session. She owns a company where she
has been working for 18 months and she loves working for herself. She is so official as she uses and
prefers EMAILS to calls. She encourages hard work in any situation and she says that people who work
hard are the heroes of the company and it doesn’t matter the position of the employee.
Participant 3 is a female who had just acquired an entry job. The interview was recorded. She is still
working to improve her skills in the company because she has no knowledge about the Company
progress. She states that President of the Company and the employees who work to bring money to the
company are the heroes of the company
Participant 4 is a female who is an administrative officer. She seems to be lacking some creativity in the
work space. She said that working beyond and above what is really expected should be rewarded. She
said that people get punished for frequently coming late of absenting themselves from the Company.
Participant 5 is a hiring manager and he too agreed the session to be recorded. He works at hiring
people and he states that the problem the new recruit face is that they don’t know their worth.
There are 4 four themes that came out lively:
i) Rewards and punishment
ii) Workplace culture
iii) Heroes of the Company
iv) Application of school knowledge at the work place
Results
There is a positive relationship between i and ii. Participant 1 shows a positive relationship between
these themes. Participant 2, 3 and 4 shows a negative relationship between the two themes. Participant
1 shows a positive relationship between themes ii and iii. Participant 4 shows a positive relationship but
Participant 2 shows a negative relationship while Participant 3 shows a neutral relationship between
theme ii and iii. There is a relationship between theme ii and them iv. Just like skills are related to the
environment of the workplace. Participant 2 and 3 stated that basic grammar and time management
are their primary skills. Participant 4 and 5 believes learning is a gradual process.

Basic Analysis (MBA)
15
References
Janert, P. K. (2010). Gnuplot in action: understanding data with graphs. Manning.Available from
www-bs2.informatik.uni-tuebingen.de/services/nilse/books/GnuplotinAction.pdf
Rasch, D., Kubinger, K. D., & Moder, K. (2011). The two-sample t test: pre-testing its assumptions does
not pay off. Statistical papers, 52(1), 219-231.
Verma, J. P. (2012). Data analysis in management with SPSS software. Springer Science & Business
Media. Availlable from
https://www.springer.com/gp/book/9788132207856
Yan, X., Guo, J., Liu, S., Cheng, X., & Wang, Y. (2013, May). Learning topics in short texts by non-
negative matrix factorization on term correlation matrix. In proceedings of the 2013 SIAM
International Conference on Data Mining (pp. 749-757). Society for Industrial and Applied
Mathematics.