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Intermediate Statistics is a course which impacts students with the knowledge to be familiar with statistical tools used to analyse data in multiple disciplines. This area of study also goes forth to offer experience in reading and interpreting of data and leads to the full understanding of techniques used in data analysis. Students undertaking Intermediate Statistics course ought to understand the underlying concepts rather than relying on mathematical formulas. Among the software’s used in data analysis while doing this course is SPSS where students should be conversant with reading data and interpreting the data into a meaningful form.
Among the key topics, students undertaking Intermediate Statistics should learn are logistic regression, multiple regressions, repeated measure ANOVA and Factorial, Bayes’ theorem, Basic Statistics: Mean, Median, Mode, Standard Deviation, Minimum, Maximum, Quartiles, Computer data processing using existing packages, Convergence of random variables, Confidence Intervals for the Mean and Variance, Data mining and statistics based Natural Language Processing, Exploratory Factor Analysis and Principal Components, Graphical Methods: Time Series Plots, Histograms, Discrete: Uniform, Binomial, Poisson, Data Coding and Exploratory Analysis, Gauss Markov theorem, Gage R&R (Measurement System Analysis), Logistic Regression and Discriminant Analysis, Markov Chain Monte Carlo, Multivariate Analysis of Variance and Canonical Correlation, Random and mixed effects, Selecting and Interpreting Inferential Statistics, Univariate and multivariate distributions, Vapnik-Chervonenkis Theory.
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