Module Handbook
Module Name: 
Lab.
Session of Statistics 
Module Level: 
Bachelor 
Abbreviation,
if applicable: 
MAS 115 
Subheading, if applicable: 
 
Courses included in
the module, if applicable: 
 
Semester/term: 
IV 
Module coordinator(s): 
Drs. Suliyanto, M.Si 
Lecturer(s): 
Drs. Suliyanto, M.Si Drs. Eko Tjahjono, M.Si Ir. Elly Ana, M.Si Drs. Sediono, M.Si Dr. Nur Chamidah, M.Si Marisa Rifada, S.Si., M.Si 
Language: 
Bahasa Indonesia 
Classification within the curriculum 
Compulsory Course / 
Teaching format / class hours per week during semester: 
2 hours lectures (50 min /
hour) 
Workload: 
2 hours lectures,2 hour structural
activities, 2 hours individual
study, 14 week per semester, and total
84 hours per semester 2.6 ECTS 
Credit Points: 
1 
Requirements: 
 
Learning goals/competencies: 
General Competence (Knowledge) Students can analyze the
data simply with the help of Software Minitab and can
interpret its output. Specific
Competence
: With
MINITAB software properly, students
are considered : 1. Being able to make presentation of
data in tables and diagrams 2. Being
able to calculate measures of central tendency, layout and dissemination of data
to a single data and group 3. Being able to calculate the probability of random variable that
distributed
discrete and continuous 4. Being able to
calculate the probability of random variable which has the probability of a
random variable that has an average sampling distribution, proportion, and
variance 5. Being able to
calculate the confidence interval for average parameters, proportion, and
variance 6. Being able to
do test hypothesis for average parameters, proportion, and variance of
population 7. Being able to
perform a test of freedom between the two factors and multiple proportions 8. Being able to
test the normality of data with methods KolmogorovSmirnov test and
homogeneity of variance test several populations with Bartlet 9. Being able to
test the similarity of the average of a completely randomized design,
randomized complete block design and factorial analysis 10. Being able to
perform simple linear regression model analysis 
Content: 
This
course is delivered by means of laboratory experiments computer to deepen the
students' ability to process and interpret data using MINITAB software for
material descriptive statistics, measures of central tendency and
dissemination of data, the probability distribution of discrete and
continuous, sampling distributions, confidence intervals, hypothesis testing,
test freedom and some proportion, test of normality and homogeneity of
variance, analysis of variance, simple linear regression, and regression
model fit test. 
Soft skill attribute 
Honest,
Discipline, Expression of Ideas, Cooperate, and Active 
Study/exam achievements: 
Students are considered to be competent and pass if at least get 40 of Final score. Final score (NA) is calculated as follow: 10% score of softskill + 20% assignment + 35% UTS + 35% UAS Final index is defined as follow: A
:
75 – 100 AB : 70  74.99 B :
65  69.99 BC :
60  64.99 C :
55  59.99 D :
40  54.99 E :
0  39.99 
Forms of Media: 
Computer, LCD projectors and whiteboards 
Learning Methods 
Lecture and assessments 
Literature: 
1. Dowdy S, Weardon S, and Chilko D, 2004. Statistics For Research, Third
Edition, John Wiley & Sons, Inc, Canada. 2. Steel, Robert G.D and Torrie, James
H ( Penerjemah Sumantri, Bambang), 1980, Prinsip
Dan Prosedur Statistik Suatu Pendekatan Biometrika, Penerbit PT Gramedia
Pustaka Utama, Jakarta. 3. Walpole, RE,1995, Pengantar
Statistika, Edisi III, Gramedia, Jakarta. 4. Walpole, RE & Myers, RH,1995, Ilmu Peluang dan Statistika untuk Insinyur dan Ilmuwan, Penerjemah : Sembiring, RK, Edisi IV,
Penerbit ITB, Bandung. 
Notes: 
