Statistics I
This course contains basics of statistics, descriptive statistics, probability, sampling, random variables and mathematical expectations, probability distribution, correlation and regression.
Tribhuvan University
Institute of Science and Technology
Bachelor of Science in Computer Science and Information Technology
Course Title: Statistics I
Course no: STA169
Semester: II
Nature of course: Theory + Lab
Full Marks: 60 + 20 + 20
Pass Marks: 24 + 8 + 8
Credit Hours: 3
Course Description : This course contains basics of statistics, descriptive statistics, probability, sampling, random variables and mathematical expectations, probability distribution, correlation and regression.
Course Objective : The main objective of this course is to impart the knowledge of descriptive statistics, correlation, regression, sampling, theoretical as well as applied knowledge of probability and some probability distributions.
Course Contents:
Laboratory Works:
The laboratory work includes using any statistical software such as Microsoft Excel, SPSS, STATA etc. whichever convenient using Practical problems to be covered in the Computerized Statistics laboratory
Practical problems
| S.No. | Title of the practical problems | No. of practical problems |
| 1 | Computation of measures of central tendency (ungrouped and grouped data) Use of an appropriate measure and interpretation of results and computation of partition Values | 1 |
| 2 | Computation measures of dispersion (ungrouped and grouped data) and computation of coefficient of variation. | 1 |
| 3 | Measures of skewness and kurtosis using method of moments,
Measures of Skewness using Box and whisker plot. |
2 |
| 4 | Scatter diagram, correlation coefficient (ungrouped data) and interpretation. Compute manually and check with computer output. | 1 |
| 5 | Fitting of lines of regression (Results to be verified with computer output) | 1 |
| 6 | Fitting of lines of regression and computation of correlation coefficient, Mean residual sum of squares, residual plot. | 1 |
| 7 | Conditional probability and Bayes theorem | 3 |
| 8 | Obtaining descriptive statistics of probability distributions | 2 |
| 9 | Fitting probability distributions in real data (Binomial, Poisson and Normal) | 3 |
| Total number of practical problems | 15 |
Text Books:
- Michael Baron (2013). Probability and Statistics for Computer Scientists. 2nd Ed., CRC Press, Taylor & Francis Group, A Chapman & Hall Book.
- Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, & Keying Ye (2012). Probability & Statistics for Engineers & Scientists. 9th Ed., Printice Hall
Reference Books:
- Douglas C. Montgomery & George C. Ranger (2003). Applied Statistics and Probability for Engineers. 3rd Ed., John Willey and Sons, Inc.
- Richard A. Johnson (2001). Probability and Statistics for Engineers. 6th Ed., Pearson Education, India