M.Sc. in Microbiology (MIC 504)
Course Outcomes
M.Sc. in Microbiology (MIC 503)
Course Outcomes
M.Sc. in Microbiology (MIC 502)
Course Outcomes
M.Sc. in Microbiology (MIC 501)
Course Outcomes
B.Sc. in Statistics (STSEC246)
Course Outcomes CO COGNITIVE ABILITIES COURSE OUTCOMES CO1 REMEMBERING Recall the basic concepts and steps in hypothesis testing, correlation, regression, and chi-square tests. CO2 UNDERSTANDING Explain the process and statistical principles underlying hypothesis testing, correlation, regression analysis, and chi-square tests in Jamovi. CO3 APPLYING Use Jamovi to perform hypothesis testing, calculate correlation coefficients, fit regression models, and conduct chi-square tests on real-world datasets. CO4 ANALYSING Analyze Jamovi outputs to evaluate relationships between variables and determine statistical significance in hypothesis testing and chi-square analysis. CO5 EVALUATING Assess the validity of results from statistical tests conducted in Jamovi. CO6 CREATING Execute complete statistical workflow in Jamovi, integrating hypothesis testing, correlation and regression analysis, and chi-square tests for practical applications.
B.Sc. in Statistics (STE244)
Course Outcomes CO COGNITIVE ABILITIES COURSE OUTCOMES CO1 REMEMBERING Recall the principle of counting, describe random and non-random experiment. CO2 UNDERSTANDING Explain basic concepts of probability. Create sample space for some random experiment and identify the events and their types. CO3 APPLYING Apply the theory of probability to various real-life situations to find the probability of different types of events. CO4 ANALYSING Explain definition of independence of events, concept of conditional probability, Bayes’ theorem. CO5 EVALUATING CO6 CREATING
B.Sc. in Statistics (STM243)
Course Outcomes CO COGNITIVE ABILITIES COURSE OUTCOMES CO1 REMEMBERING Remember the basic concepts of discrete and continuous probability distributions, univariate distributions, and bivariate distributions. Recall the basic definitions, formulas, and concepts of correlation, regression, and curve fitting. CO2 UNDERSTANDING Understand the concept of univariate and bivariate probability distributions. Understand the concept of transformation of random variables. Understand the methods of calculating simple, multiple, and partial correlation coefficients and their interpretations. CO3 APPLYING Apply univariate and bivariate probability distributions to solve real-life problems including calculating probabilities and expected values. Apply the principles of curve fitting and regression analysis to model the relationship between variables in real-world datasets. CO4 ANALYSING Analyse and compare different probability distributions to select the appropriate model for specific real-life applications. Analyze the datasets to evaluate the strength and nature of relationships using correlation and regression techniques. CO5 EVALUATING valuate the suitability and performance of probability distribution models in representing data. Evaluate the regression model and validate the assumptions underlying correlation and regression. CO6 CREATING Develop probabilistic models using appropriate probability distributions to address complex problems in a practical context. Create predictive models using simple, multiple, and partial regression techniques to solve complex problems.
B.Sc. in Statistics (STM242)
Course Outcomes CO COGNITIVE ABILITIES COURSE OUTCOMES CO1 REMEMBERING Recall the basic definitions, formulas, and concepts of correlation, regression, and curve fitting. CO2 UNDERSTANDING Understand the methods of calculating simple, multiple, and partial correlation coefficients and their interpretations. CO3 APPLYING Apply the principles of curve fitting and regression analysis to model the relationship between variables in real-world datasets. CO4 ANALYSING Analyze the datasets to evaluate the strength and nature of relationships using correlation and regression techniques. CO5 EVALUATING Evaluate the regression model and validate the assumptions underlying correlation and regression. CO6 CREATING Create predictive models using simple, multiple, and partial regression techniques to solve complex problems.
B.Sc. in Statistics (STM241)
Course Outcomes CO COGNITIVE ABILITIES COURSE OUTCOMES CO1 REMEMBERING Remember the basic concepts of discrete and continuous probability distributions, univariate distributions, and bivariate distributions. CO2 UNDERSTANDING Understand the concept of univariate and bivariate probability distributions. Understand the concept of transformation of random variables. CO3 APPLYING Apply univariate and bivariate probability distributions to solve real-life problems including calculating probabilities and expected values. CO4 ANALYSING Analyse and compare different probability distributions to select the appropriate model for specific real-life applications. CO5 EVALUATING Evaluate the suitability and performance of probability distribution models in representing data. CO6 CREATING Develop probabilistic models using appropriate probability distributions to address complex problems in a practical context.
B.Sc. in Statistics (STSEC236)
Course Outcomes CO COGNITIVE ABILITIES COURSE OUTCOMES CO1 REMEMBERING Remember Jamovi’s user interface, its layout, menus, and basic functions. CO2 UNDERSTANDING Understand the statistical analysis workflow in Jamovi, including importing data, summarizing data, and selecting appropriate summary measures. CO3 APPLYING Apply Jamovi to perform descriptive statistics and data visualization. CO4 ANALYSING Analyze datasets in Jamovi to identify trends, relationships, and patterns using data visualization. CO5 EVALUATING Evaluate the output generated by Jamovi and interpret statistical results. CO6 CREATING Execute complete statistical workflow in Jamovi.
