Applied Statistics

Course Title: Applied Statistics

Course No: CSIT.221

Nature of the Course: Theory + Lab

Semester: 4

Full Marks: 60 + 20 + 20

Pass Marks: 24 + 10 + 10

Credit Hours: 3

Course Description

This course covers applied statistics for computer and information technology, which makes students able to understand the scope of applied statistics including non-parametric tests, correlation and regression models, sample survey, survey techniques, design of experiment and inferential statistics.

Course Objectives

To know the scope and concepts of applied statistics; to know basic concepts of non-parametric tests, correlation and regression models, sampling survey, survey techniques, design of experiment and inferential statistics, and their applications; to apply statistical tools and techniques in rational ways; to interpret statistical inferences meaningfully.

Course Contents

1. Unit I: Concepts of Applied Statistics

1 hrs

1.1. Scope, importance and limitations of applied statistics

1.2. Relations of applied statistics with information technology and e-methods

2. Unit II: Sample Survey and Sampling Techniques

7 hrs

2.1. Concept of population and sample, need of sampling, censuses and sample survey, questionnaire design, sample selection and determination of sample size, sampling and non-sampling errors

2.2. Types of sampling: SRS with/without replacement, stratified, systematic, cluster, multistage and PPS sampling; ratio and regression estimation under simple and stratified sampling; estimation of mean, population total and variance (proof not required)

3. Unit III: Correlation and Regression Models

8 hrs

3.1. Concept of simple correlation, Karl Pearson's correlation, Spearman rank correlation, Kendal Tau correlation, partial and multiple correlations

3.2. OLS principles, multiple linear regression, assumptions, coefficient estimation, fitting degree equations and exponential curves, residuals, Fisher decomposition of TSS, coefficient of determination, test of significance and ANOVA (up to 3 variables)

3.3. Concepts of Cobb-Douglas production function, growth model, logistic regression model, Autoregressive model of order one; fitting of Cobb-Douglas production function, and introduction of heteroscedasticity, multicolinearity and autocorrelation

4. Unit IV: Non-Parametric Tests

7 hrs

4.1. Needs of applying non-parametric tests, Run test, Sign test, Wilcoxon signed rank test, Kolmogorov-Smirnov test

4.2. Kolmogorov-Smirnov two sample test, Median test, Mann-Whitney U test, and Kruskal-Wallis one way ANOVA test

4.3. Measures of association: Kendall's tau coefficient, Spearman's coefficient, contingency coefficient, coefficient of concordance, Friedman's two way analysis of variance by ranks

4.4. Chi-square test for independence of attributes and test for goodness of fit (only numerical problems)

5. Unit V: Design of Experiments

7 hrs

5.1. Need and concepts of design of experiments, Analysis of variance, F-statistics and its applications, linear model in ANOVA; analysis of one and two ANOVA with 1 and m observations per cell in fixed effect model

5.2. Fundamental principles of design, Completely Randomized Design (CRD), Randomized Block Design (RBD), Latin Square Design (LSD), and their analysis, Missing lot techniques for RBD and LSD (one observation missing only)

5.3. Concepts of factorial design, 2^2 and 2^3, and compute main and interaction effects of factorial design

6. Unit VI: Statistical Quality Control

7 hrs

6.1. Concepts of statistical quality control, its use, importance and purposes, and control charts and control limits

6.2. Control chart for variables, x-bar and R charts, construction of x-bar and R charts, detecting lack of control in x-bar and R charts, limits, uses and interpretations

6.3. Control chart for attributes, p-chart, its limit, use and interpretation

6.4. Control chart for number of defects per unit (c-chart), its limit, use and interpretation

6.5. Acceptance quality level, and consumers and producers risks

7. Unit VII: Inferential Statistics

8 hrs

7.1. Concepts of Point and interval estimation, confidence interval for mean and proportion, relationship of sample size with desired level of error

7.2. Estimation of parameters, likelihood function and its properties, maximum likelihood estimation of parameters of binomial, Poisson and normal distribution, properties of maximum likelihood estimate, method of moments and method of least squares techniques

7.3. Interval estimation, confidence interval and confidence coefficient, method for obtaining confidence limits, confidence interval of mean, proportion, variance and difference between means

7.4. Hypothesis Testing: null/alternative hypotheses, type I/II errors, significance level, critical value and region, p-value, one/two tail tests; one sample mean/proportion tests, two means/proportions, paired t-test, two independent sample variance tests

Laboratory Works

Students will use Excel and SPSS software for data analysis. Lab work covers correlation, regression, sampling techniques, non-parametric tests, design of experiments, statistical quality control, and inferential statistics through hands-on numerical problems.

1.Correlation Coefficients
2.Multiple Linear Regression and Model Fitting
3.Cobb-Douglas Production Function and Advanced Regression Models
4.Sampling Techniques and Survey
5.Non-Parametric Tests
6.ANOVA and Experimental Designs
7.Factorial Design
8.Statistical Quality Control Charts
9.Point and Interval Estimation
10.Hypothesis Testing

Text Books

1.Draper, N and H. Smith. Applied Regression Analysis, 2nd edition, New York, John Wiley & Sons, 1981.
2.Hogg & Tanis, Probability & Statistical Inference, 6th edition, First Indian reprint, 2002.
3.Gujarati, D. Basic Econometrics, International Edition, 1995.
4.Gibbons, J.D. Nonparametric Statistical Inference. International Student edition.
5.Siegel, S. Non-parametric Statistics for the Behavioural Sciences. McGraw-Hill, New York.
6.Hollander & Wolf. Non-parametric Statistical Methods. Johns Wiley & Sons, New York.
7.Mukhopadhyay P. Theory and Methods of Survey Sampling, Prentice Hall of India, New Delhi, 1998.
8.Montgomery Douglas C. Design and Analysis of Experiments, 5th edition, John Wiley & Sons Inc., 2001.
9.Cochran W.G. Sampling Techniques, 3rd edition, John Wiley and Sons Inc. New York, 1977.
10.Kempthorne, O. Design and Analysis of Experiments, Wiley Eastern, New York.
11.Desraj, Pramod Chandhok, Sample Survey Theory, Narosa Publishing House, 1998.

Reference Books

1.Aryal, T.R. Fundamental Statistics- Concepts and Practices, Viddharthee Publication, Pvt. Ltd., 2010.
2.Martin, A. Research Methods, Statistics, IT and e-Methods. Icon Publication Pvt. Ltd, 2004.
3.Aryal, T.R. Biostatistics-For Biology, Medical and Health Sciences, Pinnacle Publication, Pvt. Ltd., 2011.
4.Harry Frank & Steven C. Althoen. Statistics Concepts and Applications. Cambridge University Press (Low price edition), 1995.
5.Murray R. Spiegel & Larry J. Stephens. Statistics (Schaum's outlines), Tata McGraw-Hill Publishing Company Ltd, New Delhi, India, 2000.
6.Kapoor J. N. and H.C. Saxena. Mathematical Statistics, S. Chand & Company Ltd., New Delhi, India, 2001.
7.Gupta S. C. and Kapoor V. K. Fundamentals of Mathematical Statistics, Sultan Chand and Sons, 2007.
8.Rohatgi V. K. and Ehsanes Saleh, A. K. MD. An Introduction to Probability and Statistics, John Wiley & Sons, 2005.
9.Miller and Fruend. Modern Elementary Statistics, Pearson Publication, 2007.
10.Feller, W. An Introduction to Probability Theory and its Applications, Vol. 1, Third edition, John Wiley and Sons, Singapore, 2000.
11.Mayer, P. L. Introductory Probability and Statistical Applications, second edition, Oxford and IBH Publishing Co. Pvt Ltd, New Delhi, 1970.
12.Spiegel, M.R. Theory and Problems of Statistics, McGraw Hill Book Company, Singapore, 1992.

Notes:

This syllabus follows the official CSIT curriculum of Far Western University. In case of any doubt or revision, the university's published syllabus shall be considered authoritative.

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Applied Statistics

Course Description

Course Objectives

Course Contents

Laboratory Works

Text Books

Reference Books

Notes: