Course Title: Statistics I

Course no: STAT-108
Full Marks: 60+20+20
Credit hours: 3
Pass Marks: 24+8+8

Nature of course: Theory (3 Hrs.) + Lab (3 Hrs.)

Course Synopsis: Concept of Applied Statistical Techniques and its Applications

Goal: This course makes students able to understand Applied Statistical Techniques and their applications in the allied areas.

Course Contents

Unit 1: Sampling Techniques

10 Hrs.
Types of Sampling; Simple Random Sampling with and without Replacement; Stratified Random Sampling; Ratio and Regression Method of Estimation under Simple and Stratified Random Sampling; Systematic Sampling; Multistage Sampling; Estimation of population total and its Variance.


Unit 2: Non Parametric Test
16 Hrs.
Chi-square test: Test of goodness of fit; Test for independence (Categorical Data). Definition of Order Statistics; Run Test; Sign Test; Wilcoxon Matched Pairs Signed Ranks Test; Mann-Whitney U Test; Median Test; Kolmogorov Smirnov Test (One Sample Case); Cochran Q Test; Kruskl Wallis One way ANOVA Test; Friedman Two way ANOVA Test.


Unit 3: Correlation and Regression Analysis
19 Hrs.

Partial and Multiple Correlations; Multiple Linear Regressions: Assumptions; Coefficient Estimation, and Significance Test; Coefficient of Determination; Cobb-Dauglas Production Function; Growth Model; Logistic Regression; Autoregressive Model of order One, and Appraisal of Linear Models (Heteroscedasticity, Multicolinearity, Autocorrelation).


  • Theory and practice should go side by side.
  • It is recommended 45 hours for lectures and 15 additional hours for tutorial class for   completion of the course in the semester.
  • SPSS Software should be used for data analysis.
  • Home works and assignments covering the lecture materials will be   given   throughout the semester.


Text Books:

  • Draper, N. and H. Smith, Applied Regression Analysis, 2nd edition, New York: John Wiley & Sons, 1981.
  • Hogg & Tanis, Probability & Statistical Inference, 6th edition, First Indian Reprint, 2002.
  • Gujaratii, D. Basic Econometrics, International edition, 1995.
  • Gibbons, J.D. Nonparametric Statistical Inference. International Student Edition.
  • Siegel, S. Nonparametric Statistics for the Behavioural Sciences. McGraw-Hill, New York.



  • Hollander, M. & Wolfe, Nonparametric Statistical Methods. Johns Wiley & Sons, New York.