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1. ISSN 2289-8506 © 2013 Global Academy of Training & Research (GATR) Enterprise. All rights reserved.
Global Journal of Business and Social Science Review
Journal homepage: www.gatrenterprise.com/GATRJournals/index.html
Global J. Bus. Soc. Sci. Review 1 (3) 78 – 83 (2013)
Attitude of Students towards Statistics Application
Norizan Anwar1* , Aniza Jamaluddin2 and Hanis Diyana Kamarudin3
1,2,3
Faculty of Information Management, Universiti Teknologi MARA, Puncak Perdana Campus,
Section U10, 40150 Shah Alam, Selangor, Malaysia
ABSTRACT
Objective – This study aims to investigate the factors that influence the students’ statistics acceptance and its relationship.
Methodology/Technique – Method used to conduct this research is quantitative and this study is using simple random
sampling technique.
Findings – The findings of this study show that, out of three investigated independent variables, only two variables turned
out to be influential in predicting student’s statistics acceptance among undergraduate students of program Bachelor of
Science Information System Management (Hons) Faculty of Information Management Shah Alam, Malaysia.
Novelty – This study only caters students who took statistics with no mathematics qualification required in the entry level
of the program enrolment.
Type of Paper: Empirical
Keywords: Student’s Statistics Acceptance; Affect; Cognitive Competence; Value; Undergraduate Students.
JEL Classification: I20, I21, I23.
_______________________________________________________________________________________
1. Introduction
The statistics course provides vital resources for functioning effectively in making decisions based on
numerical data. Research in statistics education would be helpful to investigate the factors that influence the
students’ statistics acceptance and its relationship. Many statistics educators think that students’ attitudes
toward statistics are significant. The study was conducted among under-graduate students of program
IM221/IM225 (Bachelor of Science Information System Management (Hons), Faculty of Information
Management in Puncak Perdana Campus, Shah Alam, Malaysia. This program basically offers one (1) subject
statistics in semester 3.
2. Literature Review
Some people believe that statistics is useful both in professional and personal lives. Therefore, they might
recognize that statistics can be interesting and willing to invest the effort needed in statistical thinking and
skills learning even though realizing that statistics is not easy, but it also is not too difficult to learn (Gal,
* Paper Info: Received: July 19, 2013
Accepted: August 25, 2013
*
Corresponding author:
E-mail: norizananwar@gmail.com
Affiliation: Faculty of Information Management, Universiti Teknologi MARA, Malaysia

2. Norizan Anwar, Aniza Jamaluddin and Hanis Diyana Kamarudin
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Global J. Bus. Soc. Sci. Review 1 (3) 78 – 83 (2013)
Ginsburg, & Schau, 1997; Garfield, Hogg, Schau, &Whittinghill, 2002; Schau, Stevens, Dauphinee, & Del
Vecchio, 1995). Kirk (2002) reported that students believe an introductory statistics course to be demanding,
to involve lots of maths, and to be irrelevant to their career goals. Therefore, many students who completed the
introductory statistics course often have negative perceptions of the course and are dissatisfied with the
experience (Garfield 1997). However, the ultimate goal of statistics education is to produce individuals who
appropriately use statistical thinking. Most college students take only one statistics course which is the
introductory course.
According to Bradstreet 1996, many non-statistics majors in algebra-based introductory statistics courses
suffer from statistics anxiety and due to their negative attitude, some colleges and universities are currently
using an introductory statistics course as a main way to meet the general education requirement for
mathematics. Schield and Schield (2008) stated that about 61% of Augsburg students saw more value in
statistics after their course than before and the difference was not statistically significant. It was found that
these students had a statistically significant increase in their feeling of cognitive competence after their course
even though they found it more difficult than expected. However, Suanpang et. al. in their study indicated that
there is highly significant differences in students attitudes towards learning statistics online and using a
traditional approach. It has been also found that there is no significant difference between the attitude of
students studying on campus and those studying by distance.
Based on this literature, this paper is purposely conducted to investigate the factors that influence the
students' statistics acceptance and its relationship among undergraduate students of Bachelor of Science
Information System Management, Faculty of Information Management UiTM Puncak Perdana Campus.
3. Research Framework
Figure 1 shows the framework for studying factors that influence the student’s statistics acceptance and its
relationship. The framework is adopted and adapted from (Thapa & Bharti, 2012). Therefore, the dependent
variable is Student’s Statistics Acceptance (SSA). The independent variables were Affect (A), Cognitive
Competence (CC) and Value (V).
Figure 1: Research Framework
4. Methodology
4.1 Instruments and Method
The instrument used for collecting the data was a questionnaire. The questionnaire is adapted and adopted
from (Thapa & Bharti, 2012). Furthermore, some questions have made modification to suit and cater the
environment. The questionnaire is divided into 5 parts, where part A captures information on demographic,
Affect (A)
Cognitive Competence (CC)
Value (V)
Student's Statistics Acceptance

3. Norizan Anwar, Aniza Jamaluddin and Hanis Diyana Kamarudin
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Global J. Bus. Soc. Sci. Review 1 (3) 78 – 83 (2013)
part B to part E capture information for measuring the independent and dependent variables. Items used in Part
A were 4 questions, Part B were 6 questions, Part C were 6 questions, Part D were 9 questions and Part E were
7 questions. As an overall, there are all total of 32 items used in the questionnaire. All measures for the variables
shown in Figure 1 were using several scale style. As Part B to Part E using a Likert scale with five extremes
with 1 for “Strongly Disagree”, 2 for “Disagree”, 3 for “Undecided / Neutral”, 4 for “Agree” and 5 for
“Strongly Agree”.
Table 1: Items in Instrument
Affect (A)
B1 I like statistics.
B2 Feel insecure to do statistics problems.
B3 Frustrated over using statistic tests.
B4 Under stress during statistics class.
B5 Enjoy taking statistics courses.
B6 Afraid of learning statistics.
Cognitive Competence (CC)
C1 Trouble in understanding statistics.
C2 No idea of what’s going on in statistics.
C3 Makes lot of math errors in statistics.
C4 I can learn statistics.
C5 I understand statistics equations.
C6 Find difficult to understand statistics concepts.
Value (V)
D1 Statistics is worthless
D2 Statistics as a part of my professional training
D3 Statistical skills will be more employable
D4 Statistics is not useful to the typical professional
D5 Statistical thinking is not applicable outside job
D6 Use statistics in everyday life
D7 Statistics conclusions are rarely presented
D8 No application for statistics in my profession
D9 Statistics is irrelevant in my life
Student’s Statistics Acceptance (SSA)
E1 Statistics formulas are easy to understand.
E2 Statistics is a complicated subject.
E3 Statistics is quickly learned by most people.
E4 Learning requires a great deal of discipline.
E5 Statistics involves massive computations.
E6 Statistics is highly technical.
E7 Learn a new way of thinking to do statistics.
4.2 Population and Sampling
The study was conducted among under-graduate students of program IM221/IM225 (Bachelor of Science
Information System Management (Hons), Faculty of Information Management in Puncak Perdana Campus,
Shah Alam, Malaysia. This program basically offers one (1) subject statistics in semester 3. Thus, the
questionnaire was distributed to only semester 3 and above. Students in semester 1 and 2 were excluded.
Furthermore, this study also captured from the difference mode of study, which either the students are in full
time mode or part time mode (e.g. undergraduate program offer PLK (Pelajar Luar Kampus) and E-PJJ
(Elektronik-Pelajar Jarak Jauh). This study is using simple random sampling, 230 questionnaires were
distributed to these information professionals. 210 questionnaires were returned, however 10 questionnaires

4. Norizan Anwar, Aniza Jamaluddin and Hanis Diyana Kamarudin
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Global J. Bus. Soc. Sci. Review 1 (3) 78 – 83 (2013)
were found unusable after data cleaning is made and 200 for data analysis. Statistical Package for the Social
Sciences version 20 is used to analyze the data.
5. Results and Discussion
5.1 Respondents Profile
Table 2 presents the respondent’s demographic profile. 116 out of all respondents are male and 84 are
female. Looking to the semester, majority of the respondents are semester 3 while the minority i.e. 17% is in
others semester. In term of study mode, 71% were full time students, 21% were e-PJJ students and 8% were
PLK students.
Table 2: Respondents Profile
Characteristics Items Frequency Percentage
Gender
Female 84 42%
Male 116 58%
Semester
3 61 30%
4 46 23%
5 29 14%
6 47 24%
Others 17 8%
Study Mode
Full Time 142 71%
e-PJJ 42 21%
PLK 16 8%
5.2 Reliability Analysis
Reliability analysis was performed to ensure the scale’s internal or reliability consistency strength. Table 3
indicated that all variables are above the recommended cut-off value which were 0.6. Hence suggesting that
the scale used in the study was highly reliable (Nunnally, 1978).
Table 3: Reliability Analysis
Variables No. of Items Cronbach's Alpha
Affect (A) 6 0.735
Cognitive Competence (CC) 6 0.716
Value (V) 9 0.772
Student’s Statistics Acceptance (SSA) 7 0.796
5.3 Correlation Analysis
Table 4 and 5 exhibits the details of correlation coefficients across all variables. Hence, according to
(Bryman & Crammer, 2001), it is provisioned when any study measure strengths of a relationship.
Table 4: Correlation Analysis
Correlations
Variables SSA A CC V
SSA 1.000 0.452 0.245 0.554
A 0.452 1.000 0.470 0.597
CC 0.245 0.470 1.000 0.316
V 0.554 0.597 0.316 1.000

5. Norizan Anwar, Aniza Jamaluddin and Hanis Diyana Kamarudin
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Global J. Bus. Soc. Sci. Review 1 (3) 78 – 83 (2013)
Table 5: Detail Correlation Analysis
Independent Variable Dependent
Variable
r value Correlation Analysis
Affect (A) Student’s
Statistics
Acceptance
(SSA)
0.452 Positive Moderate Relationship
Cognitive Competence (CC) 0.245 Positive Weak Relationship
Value (V) 0.554
Positive Strong Relationship
5.4 Regression Analysis
To this effect, the following equation is formulated i.e. factors that influence Student’s Statistics Acceptance
(SSA) = β1 A + β2 CC + β3 V + ξ. Table 6 and 7 exhibits the results of the multiple regression analysis. R
square value recorded of 0.331 as shown in Table 6. Hence implying that 33.1% variance in SSA can be
explained by the combination of the independent variables which are Affect (A), Cognitive Competence (CC)
and Value (V).
Table 6: Model Summary of Regression Analysis between Independent Variables and Dependent Variables
Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 0.575a
0.331 0.320 0.45532
a. Predictors: (Constant), A, CC, V
a. Dependent Variable: SSA
The results showed that, out of three (3) investigated independent variables, only two (2) variables turned out
to be influential in predicting SSA. These variables were Affect (t = 2.290, p < 0.05) and Value (t = 6.042, p <
0.05). The other one (1) variable is found not to be significant as the recorded p-values were greater than 0.05.
Hence, based on the results, the equation is revised to SSA = 0.154 A + 0.415 V + 1.543.
Table 7: Coefficient Table for Variables Predicting SSA
Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1
(Constant) 1.543 0.219 7.032 0.000
A 0.154 0.067 0.180 2.290 0.023
CC 0.020 0.064 0.021 0.318 0.751
V 0.415 0.069 0.441 6.042 0.000
a. Dependent Variable: SSA
6. Conclusions and Recommendation
The objectives of this study is to measure factors that influence the acceptance of statistics subject among
students in semester 3 and above who already taken the subject of IMS502 (Data analysis for decision making).
Based on the analysis and finding above, the results showed that, out of three (3) investigated independent
variables, only two (2) variables turned out to be influential in predicting SSA which are affect and value.
Align with other studies, such measuring bachelor and master students conducted by Slootmaeckers (2012)
shows that the attitudes of the students have an effect on the learning of statistics. Meanwhile, a few studies
conducted using SAT and SATS-36 by Judi, et. al. (2011) and Vanhoof, et. al. (2011) respectively. There are
about six components in the assessment, i.e. affect, cognitive ability, value, difficulty, interest and effort.
However SAT-36 has undergone certain modification. Therefore, Vanhoof, et. al. (2011) emphasis to all
researchers or lecturer out there to use the improved version for future research. Their studies found that

6. Norizan Anwar, Aniza Jamaluddin and Hanis Diyana Kamarudin
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Global J. Bus. Soc. Sci. Review 1 (3) 78 – 83 (2013)
majority students have a positive attitude towards statistics. Consistently finding shows by Thapa& Bharti
(2012) where positive attitude found towards the use and application of statistics.
The learning value of statistics subject gives a lot benefits to the students. Whenever the students able to
portray a good thinking skills, applying knowledge acquired in daily life and enjoyed throughout the class, it
comes from positive attitude of the students (Judi, et. al., 2011). It will be good if the students stay focused and
able to see the value of statistics for their future development at the beginning of their statistics introductory
class (Slootmaeckers, 2012).
Acknowledgements
Many thanks to management of Faculty of Information Management, Puncak Perdana Campus, Universiti
Teknologi MARA (UiTM) for their support. On top, our thanks are also to Nor Hafiza Binti Che Ani and Siti
Balkis Binti Hussien for all their assistance in data collection and entry collaboration.
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