statsdept

Program Specific Outcomes: Mathematics,Statistics and Computer Science (M.S.Cs) The programme is designed to provide an advanced knowledge and hands-on experience to students who are interested in gaining expertise in software engineering. It connects academics to industries and allied areas. The main aim of this course is to create access to employment. Students graduating with MSCs degree will be able to apply their knowledge and skills to course projects that match industry trends. Students will have versatility to work effectively in broad range of analytic, scientific, government, financial, health, technical and other positions. The main purpose of this course is to set high standards to promote professional and technical expertise.

Program Outcomes: Program outcomes refer to broad objectives of a degree program, particularly as they pertain to the quality and productivity of the program. The faculty in each academic degree program at St. Pious X Degree and PG College for Women, articulates what they want students in their program to have achieved--in terms of knowledge, skills, and values--when they complete the program referred to as  Program Outcomes . By articulating these as things that students will know or be able to do, the benefits of a program of study can be clearly communicated to prospective students, to employers, and to others in the institution. The program’s content, student experiences, and teaching methodologies are then aligned in an optimal way to help students achieve these learning outcomes. The college employees a continuous improvement process to evaluate and improve the effectiveness of each academic program. Striving towards achieving the mission of the college the efforts are directe

Semester-IV, Paper-IV: Course Title Course Type HPW Credits      Inference (Theory + Practical) DSC-2D 4(Th)+2(Pr) 4+1 Upon successful completion of the course, students will be able to: ü Define null hypothesis, alternative hypothesis, level of significance, test statistic, p value, and statistical significance. ü Identify the four steps of hypothesis testing. ü Apply central limit theorem to describe inferences. ü Perform parameter testing techniques, including single and two sample tests for means, standard deviations and proportions. ü State and define the inference from small samples including differences between two population means, population variances. ü Analyze data including Chi-square test for goodness of fit and independence of attributes. ü Use in practice the parametric and non-parametric statistical methods. ü Use MS-Excel to generate output for the m

Semester-III, Paper-III: Course Title Course Type HPW Credits Statistical Methods (Theory + Practical) DSC-2C 4(Th)+2(Pr) 4+1 Upon successful completion of the course, students will be able to: ü Calculate and interpret the correlation between two variables. ü Calculate the simple linear regression equation for a set of data. ü Employee the principles of linear regression and correlation, including least square method, predicting a particular value of Y for a given value of X and significance of the correlation coefficient. ü Know the association between the attributes. ü Know the construction of point and interval estimators. ü Evaluate the properties of estimators. ü Demonstrate understanding of the theory of maximum likelihood estimation. ü Analyze Statistical data using MS-Excel.

Semester-II, Paper-II: Course Title Course Type HPW Credits Probability Distributions (Theory + Practical) DSC-2B 4(Th)+2(Pr) 4+1           Upon successful completion of this course , students will be able to: ü Use discrete and continuous probability distributions, including requirements, mean and variance, and making decisions. ü Define binomial outcomes and compute probability of getting X successes in N trials. ü Identify the characteristics of different discrete and continuous distributions. ü Identify the type of statistical situation to which different distributions can be applied. ü Use Poisson, exponential distributions to solve statistical problems. . ü Use the normal probability distribution including standard normal curve calculations of appropriate areas. ü Use different distributions to solve simple practical problems. ü Analyze Statistical data us

Semester-I, Paper-I: Course Title Course Type HPW Credits Descriptive Statistics and Probability(Theory + Practical) DSC-2A 4(Th)+2(Pr) 4+1           Upon successful completion of the course , students will be able to: ü Organize, manage and present data. ü Analyze statistical data graphically using frequency distributions and cumulative frequency distributions. ü Analyse statistical data using measures of central tendency , dispersion and location. ü Use the basic probability rules, including additive and multiplicative laws, using the terms, independent and mutually exclusive events. ü Translate real-world problems into probability models. ü Derive the probability density function of transformation of random variables. ü Calculate probabilities, and derive the marginal and conditional distributions of bivariate random variables. ü Analyze Statistical data using MS-Excel.