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STATISTICA suite is a product of StatSoft that helps to solve business challenges. StatSoft was acquired by Dell in March,2014. Statsoft has been dealing with big data applications for many years. This is a perfect tool that access and process big data and extract information to solve problems and optimize processes.
Data analysis, data mining, clustering , machine learning, data visualization procedures are incorporated into STATISTICA. This is a product for safe big data solution. It can handle large number of servers by supporting parallel processing . Quality issues can be predetermined and anticipated , supplier demands can be met precisely using STATISTICA.
Statistica provides accurate solutions with the help of algorithms for building models wherein multiuser platform allows for an environment to generate the best possible model for predictive analysis.
Descriptive Statistics : variables,measurement and scales,measures of central tendency and variability,probability theory discrete probability distributions and functions, binomial distribution, continuous probability distributions and functions unit normal distribution
Hypothesis Testing and Inferential Statistics : Z-test; t-test; normal approximation non-parametric statistics chi-square distribution Correlation and Regression: point-biserial biserial tetrachoric rank-biserial regression analysis and equation part and partial correlation multiple regression and correlation 4. Analysis of Variance Techniques : one-way between-subjects ANOVA; factorial between subjects ANOVA mixed between-withinsubjects ANOVA design complexity specific comparisons 5. Analysis of Covariance Techniques 6. Multivariate Analysis of Variance and Covariance Techniques Basic Probability Concepts
Sample space and events, probability axioms, elementary rules of probability, conditional probability, Bayes' Theorem. 8. Random Variables and Probability Distributions Random variables, discrete and continuous, probability distributions, distribution function probability density function mean and variance of a probabilty distribution special discrete distributions binomial, geometric,
negative binomial, Poisson, multinomial; 5. Random Samples and Sampling Distributions Random sampling, estimators sampling distributions Linear Regression and Correlation least squares estimation adequacy of the model correlation regression multiple linear regression.