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Statistics Essentials for Analytics
4.3( 3 REVIEWS )
127 STUDENTS
Overview Modern businesses depend on statistical analysis and tools to make informed decisions. Statistics Essentials for Analytics course aims to …
Overview
Modern businesses depend on statistical analysis and tools to make informed decisions. Statistics Essentials for Analytics course aims to provide knowledge to delegate about statistical concepts and techniques to help professionals derive meaningful insights from their data. The learners will know how to implement different statistical techniques using dedicated videos and illustrations.
The course will teach you about data types and variables, skewness, measures of central tendency, and modality to understand the basics of statistics. In addition to statistical concepts, the Statistical Essentials for Analytics will help you to apply statistical techniques in the real world using case studies. You will also understand various sampling techniques in addition to Bayesian Theorem and Conditional Probability.
Our Statistical Essentials for Analytics is an ultimate opportunity to comprehend and apply the concepts of statistics and analyse professional businesses to create sustainable strategies. The power to analyse different types of data will surely put you among the top industry professionals.
Why You Should Take This Training at Study365?
Study365 is a leading online provider for several accrediting bodies and provides learners with the opportunity to take this exclusive course awarded by Edureka. At Study365, we give our fullest attention to our learners’ needs and ensure they have the necessary information to proceed with the Course.
Learners who register will be given excellent support, discounts for future purchases and be eligible for a TOTUM Discount card and Student ID card with amazing offers and access to retail stores, the library, cinemas, gym memberships, and their favourite restaurants.
- Access Duration
- Who is This Course For?
- Entry Requirements
- Certification
- Awarding Body
- Method of Assessment
- Career Path & Progression
The course will be directly delivered to you, and you have 12 months of access to the online learning platform from the date you joined the course. The course is self-paced and you can complete it in stages, revisiting the lessons at any time.
This Statistics Essentials for Analytics course is recommended for:
- Data Analysts
- Statistics Trainers
- Analytics Mangers
- Business Analysts
- Entrepreneurs and Decision-Makers
- Masters or PhD Students (for thesis completion)
- Researchers and Professors
- Learners should have the basic know-how of English and ICT.
- A good educational background or professional experience is a plus.
- Learner should be above 16 years.
Upon the successful completion of the course, you will be awarded the 'Certificate for Statistics Essentials for Analytics' by Edureka.
Edureka is the fastest-growing online learning platform with a trusted name in the industry. The platform has the highest course completion rate and turns beliefs into realities by ridiculously committing to their students. Edureka collaborates with Study365 and many other educational bodies to provide guaranteed learning and success to global students & professionals.
In order to complete the Statistics Essentials for Analytics, learners will have to submit an assignment. The assignment will demonstrate your familiarity with the particular subject and test your ability to apply it in a real-world scenario.
The Statistics Essentials for Analytics will go a long way to equip you with the best knowledge to help organisations make better decisions using statistical tools and techniques. You can contribute to the critical success of your organisation and also study advanced statistical tools alongside.
Given below are job titles you can compete for, along with the average UK salary per annum according to https://www.glassdoor.com.
- Data Analyst - £55,000 (Approximately)
- Business Analyst - £67,000 (Approximately)
- Analytics Manager - £79,000 (Approximately)
Course Curriculum
| 1: Understanding the Data | |||
| Introduction to Data Types | |||
| Numerical Parameters to Represent Data | |||
| Statistical Parameters to Represent Data | |||
| 2: Probability and its Uses | |||
| Uses of Probability | |||
| Need of Probability | |||
| Bayesian Inference | |||
| Density Concepts | |||
| Normal Distribution Curve | |||
| 3: Statistical Inference | |||
| Point Estimation | |||
| Confidence Margin | |||
| Hypothesis Testing | |||
| Levels of Hypothesis Testing | |||
| 4: Data Clustering | |||
| Association and Dependence | |||
| Causation and Correlation | |||
| Covariance | |||
| Simpson’s Paradox | |||
| Clustering Techniques | |||
| 5: Testing the Data | |||
| Parametric Test | |||
| Parametric Test Types | |||
| Non- Parametric Test | |||
| Experimental Designing | |||
| A/B Testing | |||
| 6: Regression Modelling | |||
| Logistic and Regression Techniques | |||
| Problem of Collinearity | |||
| WOE and IV | |||
| Residual Analysis | |||
| Heteroscedasticity | |||
| Homoscedasticity | |||
Bennie Doyle
This is an amazing course for beginners who want to learn statistics and earn good money.
Addison Khan
I strive to earn more salary with statistics as additional knowledge.
Jess Thompson
Thank you for the step-by-step instructions.