Official Syllabus — STS-207

1. Basic operations of Data entry, Data import and export, I/O files handling etc.
2. Data Visualization: Pie diagram, Bar diagram, Histogram, Line plot, frequency curves & polygons, Scatter Plot, Gantt Chart, Box Plot.
3. Descriptive Statistics: Measures of Central Tendencies, Dispersions, Relative measures of Dispersions, Moments, Skewness, Kurtosis.
4. Parametric Tests: Testing for Mean(s), Variance(s), Proportion(s), ANOVA for one-way two-way and two way with one and m-observations per cell and with & without interactions.
5. Non–Parametric tests: Sign test, Wilxon Sign Rank test, Mann-Whitney U-test, Run test, Kolmogorov Smirnov test, Chi-square test for goodness of fit and Chi-square test independence.
6. Design & Analysis of Experiments: Analysis of Variances for Completely randomized, randomized block and latin Square Designs and Factorial experiments (2², 2³ F.E. without confounding).
7. Regression Analysis: Analysis of Simple and Multiple Linear Regression models, Selection Best Linear Regression Model (All possible, forward, backward, stepwise and stage wise methods). Binary and multinomial Logistic regression models, Probit analysis.
8. Multivariate Data Analysis: Linear Discriminant Analysis, Principal Component analysis, Factor analysis, multi-dimensional scaling, Cluster analysis.
9. Statistical Quality Control: Construction Control charts for variables and attributes.

Practical Record should contain all practical's with their implementation and is Mandatory and it carries 5 Marks. The Semester end practical exam contains answer any two with their implementation out of four Questions. (Answer any two out of the four)

The course home page maps each prescribed area to the pages that derive it. Only item 1 — the SPSS interface itself — and three parts of item 7 — model selection, logistic regression and probit analysis — are written from scratch on the practical page; the rest is linked, not repeated.