GENERAL INFORMATION
Master of Science (Applied Statistics)
Programme
0. Introduction
1. Requirement For Graduation
2. Full Time and Part-Time Student
3. Programme Duration
4. Cost of the Programme
5. Courses Offered
6. Courses Synopsis
Mathematics Department, Universiti Putra
The programme will be conducted in English
during the weekend i.e Saturday and Sunday and the
first class starts at
All bachelor’s degree holders in mathematics or statistics with at least second class lower are eligible to apply. Other degree holders with a minimum of one year working experience will also be considered.
Under this programme, all registered students have to attend classes, do some assignments and sit for examinations like the undergraduate level. There will be no thesis but the students must take one project course, MTH 5989 (6 credit hours) under the supervision of a lecturer. In this course the students are expected to be capable of applying appropriate statistical methods to analyse dataset obtained in solving a specific problem. Students are required to write their findings in the form of a mini thesis.
i) Successfully completed 36 credit hours, i.e 10 courses @ 3 credit hours and one
project (6 credit hours).
ii) Attaining a minimum of 3.000 Cumulative Grade Point Average (CGPA).
Note : 1 Credit Hour means 1 lecture hour (50 minutes).
2. Full Time and Part-Time Student
The UPM School of Graduate Studies definition of
full time students : Students who have
registered for at least nine(9) credit hours per
semester.
and
part time students : Students who have
registered for a minimum of three(3) and less than nine(9) credit hours per semester.
i) Full Time Students: Minimum 2 Semesters (14
lecture weeks per semester).
ii) Part Time Students: They can study at their own pace but have to complete the same graduation requirement as full time student. Part time students can register a minimum of 3 credit hours per semester.
There are Two types of fees :
a) Basic fees: (To be paid at the School of Graduate Studies office)
i.e. RM1200.00* (first semester) and RM950.00* (second and subsequent
semesters).
b) Course/Credit fees: RM150* per credit hours (RM5400* for the
complete 36 credit hours) in addition to the basic fees. Payment should be made to Bendahari
Universiti Putra
* subject to change
The following table shows the distribution of
the payments of the credit fees.
|
Number of Courses Taken |
Credit Hours |
Fee per Credit Hours |
Total Payment |
|
5 |
15 |
RM150 |
RM 2250.00 |
|
4 |
12 |
RM150 |
RM 1800.00 |
|
3 |
9 |
RM150 |
RM 1350.00 |
|
2 |
6 |
RM150 |
RM 900.00 |
|
1 |
3 |
RM150 |
RM 450 |
|
Course Code |
Course Title |
Credit Hours |
|
|
1 |
Mathematical
Statistics |
3+0 |
|
|
2 |
Survey Sampling (Tinjauan Pensampelan) |
3+0 |
|
|
3 |
Design and Analysis of Experiments (Rekabentuk dan Analisis Ujikaji) |
3+0 |
|
|
4 |
Regression Analysis (Analisis Regresi) |
3+0 |
|
|
5 |
Project (Projek) |
0+6 |
5. Courses Offered
A. Compulsory Core Courses (18
Credit Hours)
Note : 3+0 means 3 credit
hours = 3 lecture hours (150 minutes) + lab work not credited.
0+6 : means 6 credit hours, no lectures and 6 hrs of research.
B. Electives / Optional Courses (Minimum of 18 Credit Hours)
|
No. |
Course Code |
Course Title |
Credit Hours |
|
1. |
Quality Control Technique (Teknik Kawalan Kualiti) |
3+0 |
|
|
2. |
Exploratory Data Analysis (Analisis Jelajahan) |
3+0 |
|
|
3. |
Categorical Data Analysis (Analisis Data Berkategori) |
3+0 |
|
|
4. |
Econometrics (Ekonometrik) |
3+0 |
|
|
5. |
Survival Analysis (Analisis Mandirian) |
3+0 |
|
|
6. |
Applied Statistical Modelling (Pemodelan Statistik Gunaan) |
3+0 |
|
|
7. |
Robust Statistics (Statistik Teguh) |
3+0 |
|
|
8. |
Theory of Non-Parametric Statistics (Teori Statistik Tak Berparameter) |
3+0 |
|
|
9. |
Applied Stochastic Process (Proses Statistik Gunaan) |
3+0 |
|
|
10. |
MultivariateAnalysis (Analisis Multivariat) |
3+0 |
|
|
11. |
Time Series Analysis (Analisis Siri Masa) |
3+0 |
|
|
12. |
Spatial Statistical Techniques (Teknik Statistik Ruang) |
3+0 |
C. Example of Master of
Science(Applied Statistics) Scheme.
|
|
SEMESTER 1 |
|
|
SEMESTER 2 |
|
|
Course Code |
Course Title |
Credit Hours |
Course Code |
Course Title |
Credit Hours |
|
MTH 5401 |
Mathematical Statistics |
3 |
MTH 5402 |
Survey Sampling |
3 |
|
MTH 5404 |
Regression Analysis |
3 |
MTH 5403 |
Design and Analysis of Experiments |
3 |
|
MTH 54xx |
9 |
MTH 54xx |
9 |
||
|
MTH 5989 |
Project |
3 |
MTH 5989 |
Project |
3 |
|
|
TOTAL |
18 |
|
TOTAL |
18 |
Course
Title : Statistik Bermatematik (Mathematical Statistics)
Course Code : MTH 5401(3+0)
Synopsis:
This course
begins with probability followed by the concept of random variable and its
distribution. Moments and its properties would be discussed and this
would be followed by special distributions. Students would also be
introduced to joint distributions, order statistics, limiting distributions and
sampling distributions. Point estimation, methods of estimation, properties of
good estimators like unbiasedness, minimum variance, etc. will also be
discussed. This will be followed by Bayes and Minimax estimators.
Sufficient statistic and its properties will be discussed including
factorization criterion and Rao-Blackwell Theorem. This will be followed
by completeness, exponential class and Lehman-Scheffe Theorem. Interval
estimation will also be discussed and finally students will be exposed to the
theory of hypothesis testing including the most powerful test, Neyman-Pearson
Lemma and likelihood ratio test.
Course
Title : Tinjauan Pensampelan (Survey Sampling)
Course Code : MTH 5402(3+0)
Synopsis:
This course discusses the theory and
application of commonly used sampling techniques. Topics include simple
random sample, cluster, ratio and regression estimates, stratified and
systematic samples and biases in sampel survey.)
Course
Title : Rekabentuk dan Analisis Ujikaji (Design and Analysis of
Experiments)
Course Code : MTH 5403(3+0)
Synopsis:
This course
begins with the introduction of analysis of variance which leads to the topic
of experimental design. This is followed by the study of selected designs
namely the completely randomised design, randomised block design, incomplete
randomised design, balanced incomplete randomised block design,
Latin square design, Youden square design, 2n and 3n factorial design and
analysis of covariance. For each design, the emphasised is on the
breakdown of total sum of squares. The course discussed both theory and
applications.
Course
Title : Analisis Regresi (Regression Analysis)
Course Code : MTH 5404(3+0)
Synopsis:
This course
covers simple linear regression, multiple regression, analysis of variance
approach to regression, diagnostics and remedial measures, qualitative
independent variables and model selection.
Course
Title : Analisis Data Interaktif (Interactive Data Analysis)
Course Code : MTH 5405(3+0)
Synopsis:
The course begins
with the introduction to several of the popular statistical computing packages.
Analyses and interpretations of output from these packages using real data. The
students will work on the case studies taken from recent literatures. Further
topics include introduction to statistical simulation,
Course
Title : Teknik Kawalan Kualiti Berstatistik (Statistical Quality Control
Techniques)
Course Code : MTH 5406(3+0)
Synopsis:
This course
introduces the quality management ideas, philosophy, practice of quality
systems and standards. Statistical process control, process
capability analysis and traditional acceptance sampling will then be
discussed. Finally, the principle of experimental design for
industrial experimentation and Taguchi approach will also be discussed.
Course
Title : Analisis Jelajahan Data (Exploratory Data Analysis)
Course Code : MTH 5407(3+0)
Synopsis:
This course deals
with various techniques of exploring a set of data. Topics include
techniques of describing a data set using visual displays (such as
stem-and-leaf diagrams, histograms, box plots and
x-y plots) and calculation of sample
statistics, re-expressing values in
a data set using transformations, plot of relationships between variables
residual analysis in regression and design of experiments models, median polish
method in two-way tables, rootogram, data smoothing and schematic
plots. Statistical package(s) (chosen by a lecturer) will be used in this
course.
Course
Title : Analisis Data Berkategori (Categorical Data Analysis)
Course Code : MTH 5408(3+0)
Synopsis :
This course
discusses the analysis of data for categorical variables. The topics
include description of and inferences for two-way contigency tables, models for
binary response variables, loglinear models, fitting loglinear and logit
models, building loglinear models and loglinear-logit models for ordinal
variables.
Course
Title : Kaedah Ekonometrik (Econometrics Methods)
Course Code : MTH 5409(3+0)
Synopsis:
Topics for
discussion include nature of econometrics, estimation and properties of single
equation models, general linear restriction dynamic models, multicollinearity,
dummy variable, specification error, stochastic regressors, heteroscedesticity,
autocorelation, lagged variables, errors in variables, variable parameter
models, qualitative dependent variables, pooling of time series and cross
section data. The course ends with discussion on simultaneous equation systems,
identification problem, estimation of simultaneous equation systems, ILS, 2SLS,
3SLS, linear restriction and least variance ratio.
Course
Title : Analisis Mandirian (Survival Analysis)
Course Code : MTH 5410(3+0)
Synopsis :
This course
will emphasize on statistical techniques for analyzing positive-valued random
variable in particular failure time data of a phsical component, the time to
death of biological unit, the number of ringgit that a health insurance
company pays in a particular case and other related cases. Topics include
survival concepts, parametric models encompassing exponential, gamma, Weibull,
lognormal distributions and others, Kaplan-Meier survival curve, Cox
proportional hazard model, nonparametric methods for one sample and two
samples, accelerated time models and goodness of fit.
Course
Title : Pemodelan Statistik Gunaan (Applied Statistical
Modelling)
Course Code :
MTH 5411(3+0)
Synopsis :
The course begins
with the introduction of topics on nature and statistical features of financial
market data, environmental statistics, industrial and engineering statistics,
agricultural statistics and biostatistics. Selected important models from these
areas will be studied.
Course
Title : Statistik Teguh (Robust Statistics)
Course Code : MTH 5412(3+0)
Synopsis:
This course
discusses the analysis of data in the present of outliers in the data
set. The topics include the estimation of a robust location and scale
parameter, robust regression, residuals and influence in
regression. The construction of outlier diagnostics is also discussed.
Course
Title : Teori Statistik Tak Berparameter (Theory of Non Parametric
Statistics)
Course Code : MTH 5413(3+0)
Synopsis:
This course
emphasizes on statistical inference problems in which the assumption of
normality of the underlying population distributions is dropped. The
course starts with a topic on ordered statistics and the runs test for
randomness. This is followed by location tests for one sample, two
independent and related samples and finding their asymptotic efficiencies
relative to the corresponding parametric tests. The location problem is
extended to the case of more than two samples. Subsequent topics will be
centred on the general linear rank statistics for two samples problem,
goodness-of-fit tests for one and two samples. The course ends with a
topic on the measures of association including their tests of significance.
Course
Title : Proses Stokastik Gunaan (Applied Stochastic Process)
Course Code : MTH 5414(3+0)
Synopsis:
The course begins
with discussion on basic concepts of stochastic processes, before introducing
renewal processes and random walks, fluctuation theory, stationary processes
and spectral analysis. Further discussions include topics on Markov chains and
processes, birth and death processes, diffusion processes. The course
ends with discussions on the use of simulation in probability models and
stochastic processes as an aid to analysis and for the development of
understanding and insight.
Course
Title : Analisis Multivariat (Multivariat Analysis)
Course Code : MTH 5415(3+0)
Synopsis :
This course
begins with the study on basic properties of random vectors. This is
followed by topics on the multivariate normal distribution theory, estimation
and hypothesis testing. Several multivariate techniques will be discussed
as the knowledge of the techniques is an essential first step in understanding
multivariate analysis.
Course
Title : Analisis Siri Masa (Time Series Analysis)
Course Code :
MTH 5416(3+0)
Synopsis:
This course
begins by introducing the objective of time series analysis, estimation of
trend seasonal patterns, stationary processes and ARMA process.This will be
followed by forecasting stationary time series and several algortihms
will be discussed. Estimation,
diagnostic and randomness test and also order selection criteria will be
discussed. This is followed by an introduction to spectral
analysis. Students will also be required to carry out pratical time
series
modelling and forecasting.
Course
Title : Teknik Statistik Ruang (Spatial Statistics Techniques)
Course Code : MTH 5418(3+0)
Synopsis:
The course begins
with a brief overview of spatial analysis followed by the concept of spatial
autocorrelation and various measures of autocorrelation. Spatial
point processes will then be discussed followed by quadrat analysis and
distance method). The course ends with a discussion of spatial models.
Course
Title : Projek (Project)
Course Code : MTH 5989(0+6)
Synopsis:
This course
expects students capable of using an appropriate statistical methods to analyse
real data for a specific problem. The students are also expected to
understand and implement methods found from a latest journals to a real
data. The results of the study will be presented in a seminar.
Prepared by
Prof. Madya Dr. Kassim Haron (Program
Coordinator)
Address: A2.12, Second
Floor,
Mathematics
Building Block B (Annex)
Tel :
03-89466830
Email: kassim@fsas.upm.edu.my or
kassimhr@putra.upm.edu.my