CHAPTER 1
Introduction and Background:
Statistics
is a branch of mathematics that deals with the analysis and interpretation of
numerical data in terms of samples and populations.
Statistics
we say is a broad programme that has no limitations. It is used in our daily
life activities such as Marketing, Banking and Finance, and domestically has an
effect on everybody.
Based on
statistics; forecasting, modelling, and proper planning are drawn by
individuals, groups and a nation as a whole.
Statistical
methods and equations can be applied to a data set in order to analyse and
interpret results, explain variations in data, or predict future data. A few
examples of statistical information we can calculate are:
·
Average
value (mean)
·
Most
frequently occurring value (mode)
·
On
average, how much each measurement deviates from the mean (standard deviation)
Statistics
is important in the field of engineering, it provides tools to analyse collected
data. For example, a chemical engineer may wish to analyse temperature measurements
from a mixing tank. Statistical Methods can be used to determine how reliable
and reproducible the temperature measurements are, how much the temperature
varies within the data set, what future temperatures of the tank may be, and
how confident the engineer can be in the temperature measurements made.
STATEMENT OF THE
PROBLEM
Table 1.1
From
graph 1.1, It can be seen that from the trend analysis, the numerical strength
of statistics students in Koforidua Polytechnic from the academic year 2001/2002
students enrolled to offer the programme statistics has reduced.
Herein therefore, analysing the
numerical strength of statistics students in Koforidua Polytechnic is very low
as compared to other programmes.
HYPOTHESIS
Ho: The numerical strength of
statistics students in Koforidua Polytechnic is weak
H1: The numerical strength of statistics students
in Koforidua Polytechnic is strong
OBJECTIVES:
1. General Objective:
Ø To access the poor
numerical strength of statistics students in Koforidua Polytechnic and find
solutions to them.
2. Specific Objectives:
Ø The reasons behind why
most students do not have interest in Statistics
Ø Why students see statistics as being difficult
Ø To establish measures to
increase the numerical strength of statistics students in Koforidua Polytechnic
Research
Questions
The
following research questions were raised to guide the conduct of the study.
i.
The
gender of the respondent
ii.
The
course the respondent offered at SHS
iii.
The
school of the respondent
iv.
The
programme the respondent is offering
v.
Did
the respondent choose the programme by him/her?
vi.
If
YES/NO, why is the respondent offering the programme
vii.
Is the
respondent interested in the programme they are offering
viii.
Why
the respondent did choose statistics
ix.
What
the respondent know about statistics
x.
Would
the respondent have accepted statistics if it was offered to them
xi.
Why do
the respondent think why students are not interested in statistics
xii.
Does
the respondent have friends who are offering statistics
xiii.
Does
the comments of their friends encourage or discourage
CHAPTER 2
LITERATURE REVIEW
As most of us know, most people in
Koforidua Polytechnic are here with the hope of giving themselves the
foundation that they need to be successful in life or the skill that they need
to find a good job. Every year, more than one thousand students are admitted to
offer different programmes rather than statistics. For instance, about 96.3% of
the student population offer different programmes whilst 3.7% offer statistics.
From the information above, the numerical strength of statistics students in
Koforidua Polytechnic is weak compared to other programmes due to some of the
following reason or information we gathered from students in Koforidua
Polytechnic. Many reseachers have tried to determine why most students prefer
to offer other programmes instead of statistics in
Koforidua Polytechnic but they cannot find exclusive reasons. One might think
that the programme statistics is a difficult programme compared to other
programmes in Koforidua Polytechnic and that is not exactly true.
CHAPTER 3
METHODOLOGY
Sampling Technique
The target population used is the
Koforidua Polytechnic student population. Samples of fifty students were used
by using the simple random sampling technique (23 male and 27 female). The
reason for selecting the variable is because the students are the major
stakeholders of the numerical strength of statistics students in Koforidua
Polytechnic.
Data Collection Procedure
23 male and 27 female were randomly
selected for the purpose of this study. We went round the school to administer
the questionnaire in various schools and departments.
Research Instruments
The main instrument used for this
study was a designed questionnaire on students’ views on the numerical strength
of statistics students in Koforidua Polytechnic. The questionnaire contains two
sections; Q1-Q5 sought information on personal data of the respondent and from
Q6-Q13 propel about the knowledge of the respondent about statistics. In all,
the questionnaire contains thirteen (13) items seeking information about the
reduction of the number of statistics students in Koforidua polytechnic
CHAPTER 4
RESULTS
The
thirteen (13) research questions raise
for this study were
answered using frequency count and percentage.
Question 1:
The
gender of the respondent
From the
sample that was used (fifty) the number of male is 23 and that of female is 27
which constituents 46% and 54% respectively.
Question
2:
The
course the respondent offered at SHS
Fig
1.0
|
Fig. 1.1
The graph of courses the respondents offered at SHS. The
courses are General Science with frequency 4 (8.0%), Visual Arts with
frequency 3(6.0%), Business with frequency 16 (32.0%), General Arts has a
frequency of 12 (24.0%), Home Economics with frequency of 6 (12.0%),
Electrical Installation and Building and Construction both had a frequency of
3 (6.0%), A frequency of 2 (4.0%) for metal work and finally Draughtsmanship
had a frequency of 1(2.0%)
Question 3
The school of the respondent
Fig 1.1
School
of Business and Management Studies (SBMS) had the highest frequency of 50
(64.0%) with School of Applied Science and technology (SAST) and School of
Engineering (SOE) having a common frequency of 9 (18.0%).
Question
4
The programme the respondent is offering
Fig 1.2
|
|
|
|
|
Purchasing and Supply (PS) had the highest frequency of 12
(24%) followed by Accountancy with frequency of 10 (20.0%). Marketing and
Hospitality also had common frequency of 6(12.0%). Building Technology (BT) 4
(8.0%), Electricals with Secretariaship and Management also had a frequency of 3
(6.0%), Mechanical and Computer Science had a frequency of 2 (4.0%). Computer
Network and Entrepreneurship had the least frequency of 1 (2.0%).
Question 5
Did the
respondent choose the programme by him/herself?
Fig 1.3
46 of the
sample (92.0%) chose the programme by themselves and 4 (8.0%) did not choose
the programme by themselves.
Question 6
If YES/NO, why is the
respondent offering the programme?
Fig 1.4
25 (46.0%)
from the sample chose their respective programmes because of their aspirations in
life, 14 (28.0%) for convenience that is making things easy for them, 8 of them
also chose their programmes because of easy acquisition of Jobs and lastly, the
fourth group is because of their courses they offered back at the Senior High
School (SHS).
Question 7
Is the
respondent interested in the programme they are offering?
Fig 1.5
48
(96.0%) are interested in their respective programme of study and only 2 (4.0%)
are not interested in their programmes being offered.
Question
8
Why the
respondent did not choose statistics
Fig 1.6
Majority
of the sample 54.0% ( 27 out of 50) did not choose statistics because they have
no interest in the programme , 22% (11 of 50) also had no knowledge about the programme
while the remaining 24% also have
reasons such as weak in Mathematics, Job opportunities and very difficult.
Question 9
What the
respondent know about statistics
Fig 1.7
15
(30.0%) of the sample knew something about statistics that was relevant to the
programme, 12 with a percentage of 24.0 also knew something about the programme
but was irrelevant and 23 (46.0%) knew nothing about the programme.
Question
10
Would the
respondent have accepted statistics if it was offered to them?
Fig 1.8
Only 3
(6.0%) out of the sample would have accepted the programme if it was offered to
them but the majority of the sample (47 which is 94.0% of the sample) would
have turned down the offer.
Question
11
Why do
the respondents think students are not interested in statistics?
Fig1. 9
30.0% thus,
15 of the sample think student are not interested statistics because they weak
in Mathematics, 26.0% (13 out of 50) also dislike statistics because it involves
tedious calculations, also 13 (26.0%) have the perception that the programme is
very difficult, some (10 out of 50 which constituents 20.0%) think inadequate
education about the programme contributes to students not having interest in
statistics, and finally, 2 (4.0%) dislike the programme because of job
opportunities.
Question
12
Does the
respondent have friends who are offering statistics?
Fig 2.0
33
(66.0%) have friends who are offering statistics whilst 17 (34.0%) do not have
friends offering the programme.
Question
13
Do the
comments of their friends encourage or discourage them
Fig 2.1
30.0% of
students offering the programme (15 out of the sample) encourage their friends
and 36.0% (18) also discourage their friends through their comments about the
programme.
CHAPTER 5
FINDINGS AND
ANALYSIS
From our
research it was observed that the weak numerical strength of statistics
students in Koforidua Polytechnic is due to:
I.
The
programmes the respondents are offering corresponds with the courses they
offered in Senior High School.
II.
Most of the respondents have weak Mathematical
background.
III.
Inadequate
education about the programme; that is, the respondents do not know anything
about the programme; they have the perception that the programme is difficult.
IV.
We
found out from the respondents that, statistics involves tedious and much
calculations which prevents them from offering the programme statistics even
though some have mathematical background.
V.
The
students are concerned about their job opportunity after completion. The
respondents do not know the jobs available after offering the programme
VI.
It is
the aspiration of some of the respondents to engage in a particular field
pertaining to the programme they are offering now. For instance, it has always
been the dream of most Business students to be Accountants.
VII.
The
respondents are offering the programme at their convenience. Example, some of
the students have jobs available which is linked to the programmes they are
offering after completion, others have no choice than to offer the programme they
were offered, some also think the programme they are offering are easy to pass.
VIII.
Most
students offering statistics discourage students from offering the programme.
CHAPTER 6
CONCLUSION AND RECOMMENDATIONS
Comparing Fig. 1.0 to 1.1 and Fig 1.2, it could be seen that most of the
respondents offered business and relating that to Fig 1.4 which tells us why
the respondents are offering their respective programmes is mostly based on
what they wish to aspire in future and is making the probability to offer
statistics low. Also, the calculation aspect involved in statistics programme
puts much fear into students from offering the programmes.
Besides,
from Fig 2.1, it shows that most of the statistics students discourage others
and that prevents them from offering the programme.
Therefore, we conclude that, the
programmes offered at the Senior High School, the weak mathematics background,
the calculations involved in statistics, the discouraging words from some
statistics students, inadequate education about the programme, aspirations, job
opportunities and for the convenience are the contributing factors to the weak
numerical strength of statistics students in Koforidua Polytechnic.
Recommendations:
Based on the findings of this research work, it is recommended
that:
a. Effective Education; Ghana
Association of Statistics Students (GASS), and other stakeholders in the
education industry should organize periodic seminars and workshops for
students, parents, teachers and school administrators on the importance of
statistics.
b.
Students
offering statistics should have a positive mind set about the programme
c. Teachers teaching Elective
Mathematics in the various Senior High Schools should be qualified.
d.
The
administration should offer the students with good Mathematics background and
most especially Elective Mathematics and Economics to offer statistics during
admissions.
REFERENCES:
a. The
office of the Head of Department (HOD) of Statistics
b. The
student body (Koforidua Polytechnic)
agyemanduah2013@gmail.com
agyemanduah941@yahoo.com
