Page 152 - buku panduan 20192020

Faculty of Science Handbook, Session 2019/2020

SIQ3009 FOUNDATION OF ISLAMIC FINANCE 2. Benjamin, B., & Pollard, J. H. (1993). The analysis of
mortality and other actuarial statistics. Institute and
Introduction to Islamic finance and its practices; Riba, Faculty of Actuaries.
gharar and maisir; Musharkah, mudharabah and 3. London, Dick. (1998). Survival models and their
murabahah; Ijarah, salam and istisna’; Çomparison of estimation. ACTEX Publications.
Islamic and conventional financial systems; Islamic 4. Peter J. Smith. (2002). Analysis of failure and survival
financial institutions and products, Islamic banking and data. Chapman & Hall.
takaful, Islamic investment instruments; Capital market in 5. Collett, D. (2015). Modelling survival data in medical
an Islamic framework, leasing, securitization and sukuk; research. CRS Press.
Modeling Islamic financial products using mathematical
software; Regulatory framework for Islamic financial
institutions in Malaysia. SIT1001 PROBABILITY AND STATISTICS I

Assessment: Properties of probability. Counting techniques. Conditional
Continuous Assessment: 50% probability. Independent events. Bayes Theorem.
Final Examination: 50%
Discrete random variables. Mathematical Expectation.
Medium of Instruction: Discrete distributions: uniform, hypergeometric, Bernoulli,
English binomial, geometric, negative binomial and Poisson.
Moment generating function.
Soft Skills:
CS3, CTPS3 Continuous random variables and its mathematical
expectation. Continuous distributions: uniform, exponential,
References: gamma, chi-squared and Normal distributions.
1. Taqi Usmani, M. (1998). An introduction to Islamic
finance. Arham Shamsi. Distribution of function of one random variable.
2. El-Gamal, M. A. (2006). Islamic finance: Law,
economics, and practice. Cambridge University Press. Sampling distribution theory: Independent random
3. Iqbal, Z., & Mirakhor, A. (2011). An introduction to variables. Distributions of sum of independent random
Islamic finance: Theory and practice (Vol. 687). John variables. Random functions related to the normal
Wiley & Sons. distribution. Central limit theorem. Approximation for
4. Mirakhor, A., & Krichene, N. (2014). Introductory discrete distributions. Limiting moment generating
mathematics and statistics for Islamic finance. John functions.
Wiley & Sons.
5. Hassan, M.K., Kayed, R.N., & Oseni, U.A. (2013). Assessment:
Introduction to Islamic banking and finance: Principles Continuous Assessment: 40%
and practice. Pearson Education Limited. Final Examination: 60%

Medium of Instruction:
SIQ3010 SURVIVAL MODEL English

Estimation of lifetime distributions: lifetime distributions, Soft Skills:
cohort studies, censoring, Kaplan-Meier estimates, Cox CS2, CTPS2, EM2
regression model and its estimation.
References:
Markov models: Multi-state Markov models, Kolmogorov 1. R. V. Hogg, & E. A. Tanis. (2010). Probability and
th
forward equations, estimation of the force of mortality, statistical inference (8 ed.). Pearson.
estimation of multi-state model transition intensities. 2. R. V. Hogg, J. McKean, & A. T. Craig. (2012).
th
Introduction to mathematical statistics (7 ed.).
Binomial and Poisson models of mortality: Binomial model Pearson.
of mortality, uniform and constant force of mortality 3. H.J. Larson. (1982). Introduction to probability theory
rd
assumptions, maximum likelihood estimator for the rate of and statistical inference (3 ed.). Wiley.
mortality, Poisson models.

Graduation and statistical tests: methods of graduating SIT2001 PROBABILITY AND STATISTICS II
crude estimates, Chi-square test, standardised deviation
test, sign test, grouping of sign test, serial correlations test. Distributions of two and more dimensional random
variables. Correlation coefficient. Conditional distributions.
Exposed to risk: Exact exposed to risk, approximate Bivariate normal distribution. Transformation of two random
exposed to risk using census data. variables. Distributions of order statistics.

Assessment: Biased and unbiased estimators. Method of moments.
Continuous Assessment: 40% Method of maximum likelihood. Confidence interval for:
Final Examination: 60% mean, proportion and variance of single population;
difference between two means, difference between two
Medium of Instruction: proportions and ratio of variances.
English
Hypothesis testing for: mean, proportion and variance of
Soft Skills: single population; difference between two means,
CS3, CTPS3 difference between two proportions and ratio of variances.
Chi-square goodness-of-fit tests and contingency tables.
References: Power of a statistical test. Best critical region. Likelihood
1. Elandt-Johnson, R. C., & Johnson, N. L. (1999). ratio test. Chebyschev's inequality. Rao-Cramer's
Survival models and data analysis. John Wiley. inequality. Convergence in probability and distribution.
Asymptotic distribution of maximum likelihood estimator.

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