Overview

Credit Hours - 3

Overview  

This course will focus on modelling categorical data. The basic aim of the course is to equip students with the basic skills in the analysis of discrete data. Contents include: contingency tables, general tests, binomial data, measures of association, logistic regression, logit models for multinomial responses (nominal and ordinal), log-linear models for contingency tables, Poisson model, model building/selection, and diagnostics. 

Credit Hours - 3

Overview   

This course introduces concepts in design and analysis of medical studies, with emphasis on randomized controlled clinical trials. Primarily use data arising from biomedical and health sciences literature and analyzed using standard statistical computer packages. 

Design of clinical trials: bias elimination, treatment assignment, randomization and matching, precision, replication, repeated measures design, Prevalence and Incidence, Sensitivity and Specificity, ROC curves, Relative Risk, R x C tables, Cochran-Mantel-Haenszel test, Kappa statistics. Introduction to Survival data: Parametric and nonparametric methods, KaplanMeier survival curve estimator, Cox proportional hazards model. 

Credit Hours - 3

Overview

This course is intended to equip students with concepts of Bayesian Statistical Analysis, with focus on applications; Bayesian and frequentist methods compared; Bayesian model specification, choice of priors, computational methods; hands-on Bayesian data analysis using appropriate software; interpretation and presentation of analysis results. Use of statistical computer packages. Some applications   to data in  the  field of  Pharmacy,  Biology, Economics,  Agriculture, Biology,  Pharmacy, Medicine  and Finance. 

Credit Hours - 3

Overview

This course introduces students to basic concepts of mathematics of life contingencies. Principles of simple life insurance and annuity contracts. Means and variances of payment under these contracts. Determination of expected present value and variances of benefits. Determination of net premiums and policy values. Survival Models and Reliability Models. to stochastic optimal control. 

Credit Hours - 3

Overview

The  course is  aimed at  introducing  students to  basic  concepts of  financial  statistics. Topics to be discussed includes the following: Principles of time value of money. Concepts of compound Interest and Discounting. Interest or Discounting Rates. Compound Interest Functions. Investment Project appraisals. Stochastic Interest Rate Models. Dynamic portfolio management, introductory applications to insurance liabilities. 

Credit Hours - 3

Overview

The  course is  aimed at  introducing  students to  application  of experimental  design  and analysis  in  Biology and  Agriculture.  Topics to be discussed in class includes; Biological Assay, Analysis of Quantile responses. Agricultural and clinical trials. Sampling and Estimation of Biological Populations.  Some applications to hand-on data using R computer package. 

Credit Hours - 6

Overview

The project work is aimed at  developing  students problem  solving  and written  skills. It has one year duration. Students present a project on a relevant and topical issues pertaining to  Statistics  while applying appropriate Statistical techniques and tools  to  problems or  data  emanating from Insurance,  business,  financial and  banking  sector, communication sector, agricultural  sector,  mining sector,  construction  sector etc. 

Credit Hours - 3

Overview

This course is a sequel to STAT 336: Design of Experiments. Topics to be  covered include; Single-factor and multi-factor experiments, Analysis of Variance (ANOVA), Multiple Comparisons, Contrasts, Diagnostics, Fixed, Random and Mixed Effects models, Design with blocking and/or nesting, two level factorials and fractions thereof, Some  Medical  and Agricultural Applications. Use of Statistical Computing Packages. 

Credit Hours - 3

Overview

The course aimed at  building  on  the basic  concepts  of non-parametric  statistics  acquired in  the  course STAT 228. Topics to be covered include; Chi-square tests for Homogeneity, Chi-square tests for Independence, The Median Test, and Mann-Whitney-Wilcoxon Tests all under two-sample tests. Uses of Order Statistics Distribution under alternative Hypotheses. Introduction to nonparametric regression smoothing; basic ideal of smoothing, kernel smoothing, k-nearest neighbour estimates, orthogonal series estimators, spline smoothing. Use of statistical computer packages. 

Credit Hours - 3

Overview

This course  is  aimed at equipping students with solid  linear algebra background with  further Statistical Inference Methods. Topics include: Introduction to theory and methods of Multivariate Data Analysis; Estimation and Tests of Hypotheses, Profile Analysis, Multivariate Structure, Discriminant Analysis. Factor Analysis, Principal  Component Analysis  and  Cluster Analysis .Use of statistical computer packages.  Some applications  to hand-on  data will  be discussed  in  class. 

Credit Hours - 3

Overview

This course will expose students to Multi-subject and specialized Socio-Economic surveys household surveys, Types of Surveys: by subject coverage, unit of enquiry, and mode of enquiry.  Longitudinal and cross-sectional Studies. Other topics to be covered include: Single purpose and Integrated surveys, Planning, Design and Organization. Error Control, Problems relating to Concepts, Definitions, Classification and Measurement. 

Credit Hours - 3

Overview 

This course  is  a sequel  to STAT 335: Sample  Survey Methods. It is  aimed exposing  students  to  the theory  of  sampling. Topics to be covered include the  following: Analysis and  comparison of  various  sampling schemes; Sampling experiments, Estimation of population proportions and percentages. Proportion of simple sample estimation. Some  applications to  real-life  data from  the  fields of  Agriculture, Biology, Finance  etc. 

Credit Hours - 3

Overview 

The course  is  aimed at providing students with  the working  knowledge of  Time Series. Topics include: General stationary, nonstationary models, auto-covariance autocorrelation functions; stationary, nonstationary autoregressive integrated moving average models; identification, estimation, forecasting in linear models; financial times series models, use of statistical computer packages.  Some applications  to  financial and   actuarial  data will be  discussed  in class. 

Credit Hours - 3

Overview

The course will introduce students to the use of mathematical and statistical techniques to solve a wide variety of organizational problems. Topics include linear programming, network analysis, decision analysis. Transport problem, dynamic programming, scheduling problem, Markov chains, decision trees, Optimization and inventory control and Introduction to Supply Chain Management. 

Credit Hours - 3

Overview

This course introduces students to the concept of Analysis of  Experimental Design. Topics include: Basic Principles and concepts of experimental Statistics. Analysis of Variance for standard and experimental designs. The estimation of treatment Effects. Use of statistical computing   packages. Some  applications to  data  from the  field  of Agriculture,  Biology,  Pharmacy and  Medicine. 

Credit Hours - 3

Overview

This course is aimed at introducing students  to the  Theory of  Sampling. Topics to be covered include: Basic Sample Survey Procedures and Sample Designs. Estimation of population of parameters. Sampling and Non Sampling Errors. Estimates of population means, totals, proportions, and their variances, Multi-stage and Multi-phase Designs, Ratio and Regression Estimation.   

Credit Hours - 3

Overview

In  this  course students  are  introduced to  the  basic concepts  of  non-parametric  statistics. Topics to be discussed  include: Single Sample problems; the problem of location, the Sign Test, Wilcoxon Sign Rank Test. Introduction to Chi-square tests for Homogeneity, Chi-square tests for Independence, The Median Test, Mann-Whitney-Wilcoxon Tests all under two-sample tests. Some  applications to data   in the  field   of  medicine  and  biological sciences  will  be   discussed  in  class. 

Credit Hours - 3

Overview

The  course  aims to  build  on the  skills  of computing  students   acquired in  the  course STAT 111  and  STAT 112.  Topics to be covers include:  Reviews of some basic concepts in probability and classical statistical inference; triangular distribution, sampling distribution, point estimation, interval estimation, and hypothesis testing. Writing simple codes in R to perform inferences, simulation of random variables from probability distributions; geometric, negative binomial, hyper-geometric, exponential, normal distributions, the visualization of bivariate data. 

Credit Hours - 2

Overview

In  this  course students  are  introduced to  economic,  social and demographic  statistics. Purposes and scope of the course includes, the structure and work of the National Statistical System; Ghana Statistical Service. Organizational, Methods and Practices of Data Collection and Dissemination. Population Census Methods, Health Information Systems. Environmental Statistics and Introduction to Categorical Data Analysis. 

Credit Hours - 2

Overview

The course  is  to provide  the  student with  a basic knowledge of  Regression and  Time Series. Topics include Regression analysis; Simple linear regression: The model and its assumption; Least Square Estimation. Analysis of variance; sums of squares and their interpretation. Coefficient of determination and the correlation coefficient .Examining the Model Assumptions: Graphical Examination of residual. Test of Randomness of residuals, for constancy of variance, for normality.  Use of statistical computing packages in forecasting. 

Credit Hours - 1

Overview

Topics to cover the first foundations of actuarial practice module, role of the actuary etc. what an actuary is and does, external forces that influence actuarial work, and framework and processes actuaries use to perform actuarial work using Microsoft excel. One hour a week seminar by Members of Actuarial Society of Ghana. Students would be divided  into working groups and  each group  would  be assessed   at  the end  of  the Lecture  series. 

Credit Hours - 1

Overview

The course  is  to provide  the  student with  a basic knowledge of Time Series. Topics include Forecasting; Time Series methods, Moving  average, exponential  smoothing, Decomposition of  Time  series and Multiplicative Model, Additive Model, Forecasting.  Some financial/actuarial application of time series. Use of statistical computing packages in forecasting. 

Credit Hours - 3

Overview

This course is aimed at developing students programming and computational skills  in  the R  package. Topics to be considered include: Simulation of random variables from probability distributions, the visualization of multivariate data, Monte Carlo integration and variance reduction methods, Monte Carlo methods in inference, bootstrap and jack-knife, permutation tests, Markov chain Monte Carlo (MCMC) methods, and density estimation. Selection of examples that illustrate the application of numerical methods using R functions.       

Credit Hours - 3

Overview

This course introduces students to techniques of statistical quality control. Topics to be discussed include: Development of control charts, acceptance sampling and process capability indices, reliability modelling, regression models for reliability data. Single and  double  acceptance sampling  plans  for attributes  and  variables. Some   applications to  real-life  data will  be  discussed in  class.

Credit Hours - 3

Overview 

This course is aimed at building on   the knowledge acquired by students in STAT 457. Topics to be discussed include:  review of statistical analysis of topics and problems in microeconomics, macroeconomics, business, finance, forecasting, data quality, and policy evaluation.  Introduction to the System of National Accounts (SNA). The system, its Accounts and their corresponding economic activities. Input-Output Tables. Social Accounting.

Credit Hours - 3

Overview

The course is designed to broaden and deepen student knowledge of  the Applied  Statistics   that concerns   the collection, processing, compilation, dissemination, and analysis of   social and  economic data.  Topics to be covered include: Statistics on Economic and Social Activities and Trends and their uses. Methods and sources of data collection. Indices and indicators of Economic Activity. Indicators of Social Development and Living Standard.

Credit Hours - 3

Overview  

The course aims to build on introductory regression knowledge gained in previous years. Advanced Regression analysis focuses on applications of basic statistical techniques; model formulation, checking/diagnostics, selection; interpretation and presentation of analysis results; simple and multiple linear regressions; logistic regression; ANOVA; hands-on data analysis with R computer software. Some  applications  to data  from  the field  of  Agriculture, Biology,  Economics, Finance etc.

Credit Hours - 3

Overview

The   course is  designed to broaden  and  deepen students  understanding  of  Demography  and  Population issues. Topics to be studied include; Demographic Concepts and Measures. Collection and analysis of Demographic data. The Dynamics of population change. Mortality; Measures of Mortality, Measures of Fertility.  Rates of incidence and rates of change. Crude and Specific rates.  Life expectancy. 

Credit Hours - 3

Overview

This course is to introduce students to stochastic models in the fields  of  natural and social sciences. Topics to be covered include: Some discrete and continuous time processes; Markov  Chains, Random  Walks, Birth  and  Death Process, Random Trees; Galton-Watson Processes, Introduction to  Brownian Process, Basic Theory and Applications in  Demography/Population study, Insurance, Finance  and  Risk Management.    

Credit Hours - 3

Overview

This course is  designed  to introduce  students to the  application of in statistics business. Topics to be discussed include: Customer analytics, operation analytics, people analytic,  accounting  analytic and bus  analytic  capstone. Descriptive  analytics; use  to understand past  and  present data , predictive  analytic;  past performance, prescriptive analytic; uses  of optimization  techniques. Some applications  to real-life   data  from the field of   business.    

Credit Hours - 3

Overview

This is a sequel to ACTU 445. Topics covered include: Consumption demand, Absolute income, Life Cycle, permanent income and relative income hypothesis. The Keynesian Theory of Investment i.e. marginal efficiency of capital (MEC) and marginal efficiency of investment (MEI). Advanced topics in demand   and supply of money. Modern Theory of Interest (The Hicks-Hansen  analysis  and synthesis). 

Credit Hours - 3

Overview

Building on the core economic principles of ECON 201 and ECON 202, this course is designed to introduce the actuarial student to behaviour of the economy from an aggregate perspective. Core topics include national income calculation, measuring gross domestic product (GDP), unemployment, monetary policy and banking; inflation, interest rates, stagflation and deflation. Fiscal Policy; exchange rate and balance of payment (BOP). Business cycle and exchange rate policy. Interest rate parity. A knowledge of calculus and ECON 201 and ECON 202 is assumed.                             

Credit Hours - 3

Overview

This course is designed to build on Econometrics I. Topics covered include: Test  of  assumptions of  linear  regression model; randomness,  zero  mean, constant  variance  and normality  of  the disturbance  variable. Autocorrelation,  multicollinearity,  errors in  variables,  time as  dummy  variables, grouped  data.  Lagged variables  and  distributed-lag  models, models  of simultaneous  relationships; simultaneous-equation  models, identification, simultaneous-equation methods, the  method of  principal components,  maximum  likelihood methods,  three-stage  least squares, testing the  forecasting power  of  an estimated  model. Simulation models (Monte-Carlo etc.), Generalized linear models (GLM), and Generalized Estimating Equations (GEE). 

Credit Hours - 3

Overview

The course is designed to introduce the student to the definition, scope, and branches of econometrics as they apply to actuarial science. Topics covered include  methodology  of econometrics  research; partial  correlation, limitations  of the  correlation  theory. The simple  linear  regression model;  ordinary  least squares  method (OLS),  estimation of  elasticity’s  from an  estimated  regression line. Statistical  tests  of  the  significance of  the  estimates, properties  of  the OLS  estimates, extension  of the  linear  regression model  to  nonlinear relationships, regression and  analysis of variance. Introduction to Panel-data econometric models.        

Credit Hours - 3

Overview

This  course is a sequel to ACTU 405. Topics include: Basic construction of financial statements and the role and principal features of the financial statements of a company, accounts of a company or a group of companies; interpretation and limitations, structure and content of insurance company accounts, basic principles of personal and corporate taxation.

Credit Hours - 6

Overview

The project work  is  aimed at  developing  students problem  solving  and written  skills. It has one year duration. Students present a project on a relevant and topical issues pertaining to  Actuarial Science  while applying appropriate Statistical/Mathematical  techniques and tools  to problems  or  data emanating  from Insurance,  business, financial  and  banking sector,  communication sector,  agricultural  sector, mining  sector,  construction sector etc.

Credit Hours - 3

Overview

This  course  is designed to introduce the student to steps involved in actuarial modelling process in solving business problems. Topics relate to severity models (Calculation/interpretation of basic distributional quantities, sensitivity analysis and extreme value distributions), frequency models (Sensitivity analysis of discrete distributions and their mixtures thereof, choosing appropriate discrete distributions for available data etc) and aggregate models (collective risk models estimation, compound models for aggregate claims etc). Types and properties of actuarial risk measures (VaR and TVaR and their limitations). Construction of empirical models in actuarial business context. A knowledge of calculus and probability is assumed.

Credit Hours - 3

Overview

This course builds on Financial Economics I. Topics to be covered include  Options (Black-Scholes Formula, Market-Making and Delta-Hedging, Exotic Options), Financial Engineering and Applications (Financial engineering and security design, corporate applications, real options), Advanced Pricing Theory (The lognormal distribution, Monte Carlo Valuation, Brownian Motion and ItÔ’s Lemma, The Black-Scholes-Merton Equation), Risk-Neutral and Martingale Pricing, Volatility, Interest Rate and Bond Derivatives, Value-at-Risk and Credit Risk Modelling.

Credit Hours - 3

Overview

This course is designed to introduce students to the theoretical knowledge and application of financial models as they are applied to insurance and financial risk management. Topics to be covered include interest rate models, introduction to derivatives, insurance, hedging and simple strategies (introduction to forwards and options, insurance, collars and other strategies etc), Forwards, Futures and Swaps, Options I (Parity and Other Option Relationships, Binomial Option Pricing: Basic Concepts, Binomial Option Pricing: Selected Topics).

Credit Hours - 3

Overview

The  course  is aimed  at  equipping students  with  some concepts  of  financial accounting. Topics include the following: principles of finance, structure of a joint stock company, and the different methods by which it may be financed, financial instruments used by companies and the way they may be issued,  capital structure and dividend policy,  a company’s cost of capital interacts  with the nature of the investment, major types of financial institutions operating in the financial markets.

Credit Hours - 3

Overview 

The  theory  and practice  of  social security  and  state, occupational  and  personal pension  plan funding. Features  of  the main  employee  benefit schemes,  principles  of financing,  including  asset and  liability  relationships. Legislative frame work on retirement and various benefit schemes. Tax management,  economic and  demographic  factors, accounting  for  pension costs, valuation  data collection,  analysing experience,  valuing  liabilities and  assets,  calculating contribution  rates;  choice and  management.                  

Credit Hours - 3

Overview

This course  is  a sequel to ACTU 453. Topics include: Premium; calculation and principles,  notion  of utility function; linear utility,   exponential  utility, properties  of premium calculation  principles. Introduction  to experience  rating; under  writer A,   B  and C,  bayesian  approach. Introduction  to extreme value theory; limit  behaviour of  maximum.

Credit Hours - 3

Overview

This  course   aim  at  introducing students  to  the concept  of non-life   computations and  analysis. Basic  models  and concepts;  reserve  process, risk process, Cramer-Lundberg model,  homogeneous  poisson process,  compound Poisson model,  Erlang’s  model. Common distributions for number of claims; Binomial  distribution,  negative binomial  distribution, poisson  distribution. Common distributions for claims size; Gamma distribution, lognormal distribution, some extreme  risk distributions. Distribution of  sum  of claims; convolution  theorem, generating  functions, moments  estimates.

Credit Hours - 3

Overview

This course focuses on the core principles of risk management and insurance in actuarial science. Topics covered include types of risk identification and analysis, risk modelling concepts, risk quantification, approaches for managing risks (how business entities makes decisions about risk management techniques). The further sections of the course will delve into the concept of economic capital, risk measures in capital assessment and techniques to allocate cost of risk within business units. Topics also cover life and health insurance, property and liability insurance, value-based enterprise risk management for corporations, pensions and employee benefits and risk aggregation techniques.

Credit Hours - 3

Overview

The emphasis is on the geometric and computational foundations of Linear Algebra with abstraction (and proof) kept to a minimum. We would examine matrices, linear  systems of equations and their solutions. Basic properties of determinants, vectors in  and a simple introduction to the idea of an arbitrary vector space. The pinnacle of the course is to be able to find eigenvalues and their corresponding eigenvectors  for  a  given matrix and indeed for a linear map. We would carefully develop the diagonalization of symmetric matrices. For those who did the MATH 220 there would be applications using Python.

Credit Hours - 3

Overview

The course introduces the main concepts and tools of game theory. The main  aim of  the course   is  to enable students to read original game-theory literature and to prepare them to do research in the field. They will learn how to represent an economic situation as a game and how to analyze it using different equilibrium concepts proposed in the literature, the prominent one being the Nash equilibrium. Concentration will be on strategic interaction under incomplete information and modify the Nash equilibrium concept to include the uncertainty of the players about some of the parameters of the game.

Credit Hours - 3

Overview

This course is a follow up to STAT 333. It is aimed at building on  the concepts of    mathematical statistics  acquired in  STAT 333. Topics to be covered include: General principles and Procedures of Hypotheses Testing. Parametric and Non- Parametric Test. Simple Linear Regression and Correlation Analysis. The Analysis of Frequency Data. Introduction to Categorical Analysis. Statistical modelling with R. Some  applications  to real-life  data in  the fields of actuarial and finance.

Credit Hours - 3

Overview   

The first part of the two-semester course provides a systematic development of the principles and methods of statistical inference, on a largely intuitive basis with a minimum of mathematical theory. This part deals with the general nature of Statistical Problems, Statistical Models and Problems of Estimation. Introduction to Bayesian Statistics. Introduction to statistical modelling with R. Some applications to data in the field of actuarial science.

Credit Hours - 3

Overview 

This course is aimed at introducing students to multivariate distribution theory. Topics to be covered include:  Introduction to Vector Random Variables; vector of means, dispersion matrix, matrix of co-variances. Distribution Concepts for several random variables; exponential-type distribution, multivariate moment generating function. Transformation of Random Vectors; gamma distribution, beta distribution, chi-square distribution t-distribution, f-distribution. Order Statistics; joint distribution of order statistics. Multivariate Normal Distributions.

Credit Hours - 3

Overview

Introduction to Economic model-building, comparative static and dynamic models. Consumer  Behaviour  and Demand  theory,  law of  diminishing  marginal utility,  ordinary  utility approach, Demand  function,  income elasticity  of demand, short-run cost; fixed, variable,  total ,  average  and  marginal cost,   production function, perfect  competition; the  firm, market,  product homogeneity,  perfect  knowledge, profit  maximization,  free entry,  short-run equilibrium of  firm and  industry, constant  and increasing  cost.

Credit Hours - 3

Overview

The course is designed to introduce actuarial science students to a thorough understanding of the fundamentals of economic analysis of individual, business and industry choices in market economies as it applies to actuarial practice. Topics to be covered include basic economic concepts, nature and function of product markets, price mechanism, supply and demand, optimizing economic behaviour, cost and revenue, market structures, factor markets, income distribution, market failure and government intervention. Introduction to Economic model-building, comparative static and dynamic models. 

Credit Hours - 3

Overview 

This course is aimed at introducing students to Elementary Distribution Theory. Topics to be covered include Generating Functions and Applications; moment generating functions, probability generating function, factorial moment generating function and characteristic function, moments and limiting distributions. Sequences of random variables; modes of convergences, the Central Limit Theorem and its Applications. Concentration inequalities. Introduction to large deviation theory; large  deviation  probabilities,  method of  types.

Credit Hours - 3

Overview  

This course builds on Life contingency I. It is designed to develop theoretical basis for pricing and supporting life-contingency products. Topics includes economics of insurance, general insurances, annuities, premiums (level and non-level benefits and premiums) and expense (incorporating expenses in insurance models) analysis, analysis of reserves, Hattendorf theorem, probability models: Poisson Processes. The course is designed to set the pace towards ensuring the student’s adequate preparation for the MLC/3L exam of the Society of Actuaries or  Canadian Institute of Actuaries respectively.

Credit Hours - 3

Overview

This course provides  basic foundation of knowledge concerning fundamental building blocks of actuarial practice. It is  meant to present  students with a transition from understanding the mathematical underpinnings of actuarial science to putting them into practice. The course focuses on two areas of actuarial practice: investment management and life insurance. All mathematical computations will be computer program assisted. Students will be able to construct and use life tables in simulation studies, portfolio management theory and design basic individual life. Concepts will apply the concepts within an actuarial problem statement. Recommended software include excel, R and MATLAB.

Credit Hours - 3

Overview 

This course introduces students to mathematics of life contingencies. Being probabilistic in nature, the course seeks to develop theoretical basis for modelling future lifetime status with emphasis on insurance. Topics to be covered include brief review of probability theory, international actuarial notations, actuarial survival models, life table format, life statuses, survival distributions, concept of dependence (common shock models, copulas etc), multiple lives and multiple decrement theory and multiple-state models. The course is designed to set the pace towards ensuring the student’s adequate preparation for the MLC/3L exam of the Society of Actuaries or Canadian Institute of Actuaries respectively.

Credit Hours - 3

Overview  

The course will introduce students to introductory data mining. Topics to be covered include: data warehousing, data mining process (data preparation/cleansing, task identification), Association rules (mining and different algorithm types), Classification/Prediction, Classification (tree-based approaches, Neural Networks, etc), Clustering (statistical vs neural-net and other approaches), Model evaluation and visualization techniques. The course will help students make better sense of large chunks of data which will be incredibly useful in understanding big data.

Credit Hours - 3

Overview   

This  course   is aimed  at broaden  and deepen  the  knowledge of  students  theory probability. Topics to be considered  include  the following:  Bivariate Distributions,  Bivariate Moment Generating Functions; their properties and uses. Sampling distributions. Distribution associated with samples from a normal population. The Laws of Large Numbers, and the Central Limit Theorem and its Applications. Statistical Inequalities. Some Statistical  Applications of  Probability; likelihood  functions and estimation. Financial and Actuarial Applications  of  Probability.                           

Credit Hours - 3

Overview

This course introduces students to  some  basic concepts  of  statistical methods. Topics to be  covered are Bivariate Data analysis, Elements of Statistical inference. Hypothesis testing – One-sample case (test for mean, proportion, power, sample size, test for variance, Confidence intervals) Hypothesis testing – Two-sample case (two-sample test for paired and unpaired means and proportions, power, sample size, equality of variance test, Confidence intervals). ANOVA (one- and two-way), Simple Linear Regression and Correlation Analysis.

Credit Hours - 3

 Overview

The course builds  on  concepts introduced  in  STAT 112. Topics  to be  considered include: Further  concepts of Probability, Random Events and Random Variables. The Probability Calculus, Univariate Probability Distributions. Univariate Moment Generating Functions; their properties and uses. Introduction to Bivariate Discrete Distributions; conditional discrete distribution, expectation. Some Probability Modelling based on discrete distributions.

Credit Hours - 3

Overview 

This course  is  aim at  building  on the  foundation  of mathematical  finance that  has been laid  in  the course ACTU 203.  Topics to  be  cover include: Introduction to option pricing; definition  and types  of  options. One period  binomial  and  trinomial  models for  option  pricing. Conditional expectation,   utility functions, examples of  stochastic process. Introduction to interest theory; coupon rate, swap rate, forward rate, simple rate, LIBOR rate. Financial market; some complete market models, some incomplete market models, arbitrage opportunities.

Credit Hours - 3

Overview

This course  is  aim  at  introducing students  to  some basic  concepts  of  mathematical finance. Course content includes foundational concepts of financial mathematics, with applications in calculating present and accumulated values for varied streams of cash flows as a basis for future use in actuarial reserving, valuation, pricing, duration calculation, asset/liability management, investment income, capital budgeting and valuation of contingent cash flows. Basic asset pricing theory, Introduction to optimal  portfolio theory; mean–variance approach, markovitz solution for two assets.   Introduction to option pricing; definition and types of options.  One period binomial and trinomial models for option pricing. A basic knowledge of calculus and an introductory knowledge of probability is assumed for students taking this course.

Credit Hours - 3

Overview

This course is aimed at enhancing students understanding of basic principles in Statistics and Probability. Relative frequency function, Introduction to probability distributions, some univariate probability distributions; Bernoulli, Binomial, Poisson, Uniform distributions. Simulation of random variables from probability distributions; Bernoulli, Binomial, Uniform distributions using (R, Minitab and Stata): mean, variance, mode of probability distribution. Writing simple codes  to generate  discrete  random values of  the  Bernoulli, Binomial  and  Poisson distributed  random  variables. One hour Lab session  a  week  will be  organized  for students.                     

Credit Hours - 3

Overview

This course introduces students to basic principles in Statistics and Probability. The definition, reduction and interpretation of data. Introduction to basic concepts of Probability; Random Events and Random Variables, and Bayes Theorem. Students will be given overview of computational statistics and an introduction to the computing environment. The statistical software (R, Minitab and Stata) will be used to execute concepts learned in class. Methods of data description and analysis using R, Minitab and Stata: emphasis on learning statistical methods and concepts through hands-on experience with real data. One hour laboratory session  a  week will  be  organized for students.