Predictive Modelling Course

What is ANALYTICS?
The purpose of analytics is to take existing data collected from either a single source or multiple sources and use it to arrive at the optimal decision. Essentially, analytics can be best defined as a science of analysis.
Commonly, one of the most frequent uses of analytics is in the field of business. Managers or researchers for an analytics company can use various data mining techniques combined with historical patterns to make predictions about the performance of a particular market or business.

10 most popular analytic tools in business

• Business analytics is a fast growing field and there are many tools available in the market to serve the needs of organizations. The range of analytical software goes from relatively simple statistical tools in spreadsheets (ex-MS Excel) to statistical software packages (ex-SAS, SPSS).

• To sophisticated Business Intelligence suites (ex-SAS, Oracle, SAP, IBM among the big players).

Descriptive Statistics.

• Measure of central tendency

• Measure of Dispersion

Sampling Methods.

• Simple Random Sampling

• Systematic Random sampling

• Stratified Random sampling

• Cluster Random Sampling

• Non Random samplings: Quota, Judgment, Convince and Snow ball sampling

Parametric tests.

• One sample t test

• Independent of two sample tests ( t test & Z tests)

• Paired t test

• One Way ANOVA

• Two ways ANOVA

Non parametric Tests.

• Mann Whitney U test

• Kruskal Wallis Anova, Friedman Anova

• McNemar test

• Median test

Forecasting Technique.

• ARIMA Modeling

• Exponential Smoothing

Predictive Modeling technique.

• Multiple Linear regressions

• Logistic Regression

Multivariate Techniques.

• Principal Component Analysis

• Factor Analysis

• Cluster Analysis

• Canonical correlation

• Discriminate Analysis