In current times and in the foreseeable future, data collection, collation, analysis and putting it in understandable and enabling form for further effective use shall continue to dominate various businesses across the globe. Banks, e-commerce and logistics businesses are already investing in a big way in building skills in this area. Institutes across discipline have quickly caught on with the computing industry need and have introduced data courses as integral part of the study/electives and using industry experts to impart niche learning. The students too have become aware of the opportunities these coursed them in making them better employable. This is also a mandatory requirement specified by various accreditation agencies, namely National Board of Accreditation and NAAC.
Cresscenza is a learning center constituent of Search Online Communication OPC Pvt. Ltd a part of City Innovates enterprise. We have on board, some of the leading experts in the field, both in terms of their qualification and experience. Faculty from IIT and IIM background and with experience in top companies of the world deliver our courses to corporate and higher education institutes and have earned an excellent feedback and testimonials. The profile of the leading faculty is attached.
This course introduces you to the discipline of statistics as a science of understanding and analyzing data. You will learn how to effectively make use of data in the face of uncertainty: how to collect data, how to analyze data, and how to use data to make inferences and conclusions about real world phenomena.
The learning outcomes of this course are as follows:
- Recognize the importance of data collection, identify limitations in data collection methods, and determine how they affect the scope of inference.
- Have a conceptual understanding of the unified nature of statistical inference.
- Apply estimation and testing methods (confidence intervals and hypothesis tests) to analyze single variables and the relationship between two variables in order to understand natural phenomena and make data-based decisions.
- Model and investigate relationships between two or more variables within a regression framework.
- Interpret results correctly, effectively, and in context without relying on statistical jargon.
- Critique data-based claims and evaluate data-based decisions.
- Complete a research project that employs simple statistical inference and modeling techniques.
- Introduction to Analytics
- What is Analytics?
- Applications of Analytics
- Analytics Technology
- Analytics Terminology
- Introduction to data
- Types of Data
- Exploratory data analysis
- Frequency Distributions and Visualizing data
- Descriptive Statistics
- Central Tendencyand Variability
- Defining probability
- Probability and Normal Distributions
- Standardized Scores (Z-scores)
- Sampling Distribution
- Inferential Statistics
- Variability in estimates and the Central Limit Theorem
- Confidence intervals
- Hypothesis tests
- Decision errors, significance, and confidence
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