Page 89 - Handbook Bachelor Degree of Science Academic Session 20212022

Faculty of Science Handbook, Academic Session 2021/2022

SIT2007 FOUNDATIONS OF DATA SCIENCE
References:
1. Crawley, M. (2013). The R Book (2nd ed.). Chichester,
UK: John Wiley & Sons. Introduction to data science; Differences between
2. Crawley, M. (2019). Statistics: An Introduction using R experimental and observational data; Characteristics of big
(2nd ed.). Chichester, UK: John Wiley & Sons. data sets; Sources of biases in data sets; Introduction to
3. Matloff, N. (2011). The Art of R Programming: A Tour industry-level, open source computing tools such as R; Data
management; Graphical visualisation including spatial data;
of Statistical Software Design. San Francisco, CA: No Analysis and interpretation of real data sets with varying
Starch Press.
degrees of complexity using appropriate statistical methods.
SIT1003 ANALYSIS OF DATA AND STATISTICAL Assessment:
REPORT WRITING Continuous Assessment: 50%
Final Examination: 50%
Descriptive statistics. Hypothesis testing, confidence interval
and tests of independence. Regression and Correlation: References:
continuous response data, simple and multiple linear model. 1. Irizarry, R. (2019). Introduction to Data Science: Data
Analysis and Prediction Algorithms with R. Boca Raton,
Statistical tests: Goodness of fit tests, ANOVA, FL: CRC Press.
Nonparametric test. 2. Crawley, M. (2019). Statistics: An Introduction using R
(2nd ed.). Chichester, UK: John Wiley & Sons.
Statistical Report Writing. 3. Matloff, N. (2011). The Art of R Programming: A Tour
of Statistical Software Design. San Francisco, CA: No
Assessment: Starch Press.
Continuous Assessment: 50%
Final Examination: 50%
SIT2008 FURTHER MATHEMATICAL STATISTICS
References:
1. Tibco Spotfire S-PLUS Guide to Statistics Volume 1, The exponential family; sufficient, complete and ancillary
TIBCO Software Inc. statistics; minimum variance unbiased estimators; Bayesian
2. Mann, P. S. (2013). Introductory Statistics, John Wiley estimation; Delta method for asymptotic approximation;
& Sons. distributions of certain quadratic forms-one and two factors
3. Peck, R., Short, T., & Olsen C (2020). Introduction to analysis of variance; probability measure space; law of large
Statistics and Data Analysis 6th ed. Cengage Learning numbers; Borel-Cantelli lemma.
4. Evans, J.R. & Olson, D.L. (2002). Statistics, Data
Analysis and Decision Modeling and Student CD-ROM Assessment:
(2nd Edition). Prentice Hall. Continuous Assessment: 40%
Final Examination: 60%

SIT2001 PROBABILITY AND STATISTICS II References:
1. Hogg, R.V., & Craig, A.T. (2013). Introduction to
Distributions of two and more dimensional random variables. Mathematical Statistics (7th ed.). New York: Wiley.
Correlation coefficient. Conditional distributions. Bivariate 2. Hogg, R., Tanis, E., & Zimmerman, D. (2019).
normal distribution. Transformation of two random variables. Probability and Statistical Inference (10th ed.). USA:
Distributions of order statistics. Pearson Education.
3. Taylor, J.C. (1997). An Introduction to Measure and
Biased and unbiased estimators. Method of moments. Probability Theory. Springer.
Method of maximum likelihood. Confidence interval for: 4. Casella, G., & Berger, R.L. (2002). Statistical Inference
mean, proportion and variance of single population; (2nd ed.). Pacific Grove, CA: Thompson Learning.
difference between two means, difference between two
proportions and ratio of variances.
SIT2009 REGRESSION ANALYSIS
Hypothesis testing for: mean, proportion and variance of
single population; difference between two means, difference Simple linear regression: Estimation, hypothesis testing,
between two proportions and ratio of variances. Chi-square analysis of variance, confidence intervals, correlation,
goodness-of-fit tests and contingency tables. residuals analysis, prediction. Model inadequacies,
diagnostics, heterogeneity of variance, nonlinearity,
Power of a statistical test. Best critical region. Likelihood ratio distributional assumption, outliers, transformation. Selected
test. Chebyshev's inequality. Convergence in probability and topics from matrix theory and multivariate normal
distribution. Asymptotic distribution of maximum likelihood distribution. Multiple linear regressions: Estimated multiple
estimator. Rao-Cramer's inequality. linear regression. Hypothesis testing, ANOVA, Confidence
Interval, Model selection criteria, Diagnostics for influential
Assessment: observations and multicollinearity. Introduction to logistic and
Continuous Assessment: 40% Poisson regression.
Final Examination: 60%
Assessment:
References: Continuous Assessment: 40%
1. Hogg, R.V., & Tanis, E.A. (2015). Probability & Final Examination: 60%
Statistics Inference, 9 ed., Pearson.
th
2. Hogg, R.V., McKean, J.W., & Craig, A.T. (2019). References:
th
Introduction to Mathematical Statistics, 8 ed., 1. Montgomery, D.C., Peck, E. A., & Vining, G.G. (2012).
Pearson. Introduction to Linear Regression Analysis (5th ed.).
3. Wackerly, D., Mendenhall, W., & Scheaffer, R.L. Hoboken, NJ: John Wiley.
(2008). Mathematical and Statistics with Applications, 2. Weisberg, S. (2014). Applied Linear Regression (4th
th
7 ed., Thomson. ed.). John Wiley & Sons, Inc.
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