Predictive Modelling
Predictive Modeling is a process that is used in the case of predictive analytics for the creation of a statistical model with respect to the behavior in future. The area of data mining that is concerned with the forecasting of trends as well as probabilities is predictive analytics. A number of predictors make up the predictive model. These are the variable factors that have a very likely influence on the behavior or the results in the future. For instance, in the case of marketing, the purchase history, age, and gender of the customer may predict the probability of a sale in future.
In the case of predictive modeling, the collection of the data is done for the relevant predictors, the formulation of the statistical model is done, predictions are made after that, followed by the revision or validation of the model as the availability of the data increases. The application of a simple linear equation or a neural network that is complex may be employed by the model. This is mapped out by software which is sophisticated.
Minitab and its Application to Predictive Modelling Course
The Minitab Descriptive Statistics course regarding “Minitab and its Application to Predictive Modelling” is aimed at providing and enhancing the skills of predictive modeling across a number of business domains as well as sectors. Quantitative methods along with the concepts of predictive modelling will be made use of in an extensive way for an understanding of the current behaviour of the customers, movements of the financial markets and for the purpose of studying the tests as well as the effects in the sectors of pharma and medicine after the administration of the drugs.
For the purpose of predictive analysis, the practical and also the theoretical databases are covered by the course. As the participant goes through the training that this course provides, the observations and interpretations along with the predictions and conclusions are explained then and there and relevant examples are also provided.
This Minitab Descriptive Statistics course will be helpful in working across a number of software packages like Paint, PDF writers, MS Office and Minitab. Apart from this, the distribution of the course has been done through six sub-courses. The details of the six sub-courses have been mentioned below –
The aim of the course is to provide Minitab Descriptive Statistics skills from the basic to the intermediate level for the implementation of the concepts of Predictive Modelling with the help of the Minitab software. Although the development of the concepts of Predictive Modelling is significant, the capability of implementing it by making proper use of the appropriate software packages is of equal significance. The Minitab Descriptive Statistics course attempts to fill in the gap that exists between an understanding of the various concepts and their practical implementation.
T-test, Standard Deviation, Means and Minitab Descriptive Statistics are all explained by this course. The concepts of descriptive statistics that are explained by this course act as the building blocks for the other related courses that follow this Minitab Descriptive Statistics course.
The objective of the Minitab Descriptive Statistics Course
The aim of this course on Predictive Modelling is providing and enhancing the skills of predictive modeling across a number of business sectors and domains.
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Skills you will master
- Minitab
- Predictive Modelling
- Descriptive Statistics
- Means
- Standard Deviation
- Analysis of Variance ANOVA
- Correlation Techniques
- Regression Modeling
- Multiple Regression
- Identity Equation
- P - Value and T – Value
- Scatterplot
- Multicollinearity
- FLux Vs Insolation
- Business Metrics
Jobs you will be eligible for
- Data Analyst
- Minitab Data Scientist
- Data Analyst
- Business Analyst
- Statistician
- Quality Engineer
- Quality Manager
- Consultant
- Team Leader
- Quality Analyst
- Statistical Analyst
- Software Test Engineer
- QA Engineer
- Test Analyst
- Test Lead
- Analytics Consultant
- Analytics Manager
- Solution Architect
- Programmer Analyst
- Technical Architect
