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Business Statistics for Data Analysts

DECIPHER THE LANGUAGE OF DATA BY HARNESSING STATISTICAL COMPETENCIES.

Craft beginner level expertise in analyzing and interpreting data for sound business decision making

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Key Highlights

Course Length

4 Weeks

100% Online

With Continuous Learning Community support + Monthly Live Webinars

Effort

4 Hours/ Week

Learning Access

Resource Toolkit & Templates + Unlimited Networking Events

“This course taught me new ideas, techniques that I can apply to real-world scenarios”
Kavitha
TechM
“A very comprehensive course. I am now more confident in applying statistical techniques in my role as a Data Analyst”
Karmarkar
Wintech Solutions

What will you Learn?

  • Gain the ability to apply statistical tools to applications
  • Develop critical thinking and analytic skills
  • Learn data summarization and presentation
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Top skills you will learn

  • Generate hypothesis for a one-way analysis of variance
  • Apply Chi-Square Tests and ANOVA in Business Scenarios
  • Data grouping mechanisms
  • Understand the fundamentals of statistics
  • Perform hypothesis testing
  • Master the foundations of data science, statistics, and machine learning
  • Calculate correlation and covariance
  • Probabilistic approaches
  • Types of Probabilities
  • Determine patterns or motive of the data
  • Uncover anomalies in data

Course Curriculum

  • Introduction
  • Statistical Learning vs Machine Learning
  • Datatypes
  • Why data types are important
  • Data Grouping
  • Data summarization techniques
  • Measures of location, spread, and shape
  • Visual representation of summarized data
  • Summary
  • Additional Learning Resources
  • Chapter Quiz
   Introduction to Probability?
   Probability and Business decisions
   Deterministic and Probabilistic models
   3 types of the probabilistic approach
   Understanding basic terminologies 1
   Measuring outcomes
   Understanding probability through Venn diagrams
   Understanding basic terminologies 2
   Types of probability
   Conditional law
   Laws of probability
   Probability distributions
   Binomial distribution
   Poisson distribution
   Continuous distributions
   Uniform distribution
   Normal distribution
   t – distribution
   Choosing an appropriate distribution
   Summary
   Additional Learning Resources
    Chapter Quiz
   Inferential Statistics
   Key concepts and vocab
   Probability & Non-Probability sampling
   Sampling distribution and CLT theorem
   Estimating population parameters
   Confidence levels and Confidence Intervals
   Hypothesis testing
   Null and Alternate hypothesis
   Significance levels
   2 methods to test significance
   Applying significance levels to decision making
   Chi-square test and their applicability in business scenarios
   One way ANOVA and their applicability in business scenarios
   Summary
   Additional Learning Resources
    Chapter Quiz

Ideal For

  • Individuals seeking a career in Data Science, Business Intelligence, or Business Analysts.
  • Professionals keen to learn Statistics and its applications in the business world.
  • Beginners looking to build a strong grounding in data understanding.
  • Industry professionals desirous of mastery of statistical fundamentals.

Common Scenarios to Enroll

Engineer Data-Driven Decision Making
Engineer Data-Driven Decision MakingYou no longer want to rely on your gut or heuristics to make decisions, instead want to leverage data-driven insights to plot optimal decisions at work.
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Develop Critical Thinking
Develop Critical ThinkingCritical thinking you believe is a surefire aid in understanding and solving business problems, and you know statistical data goes to the heart of providing such an understanding.
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Secure in-demand Professional Future
Secure in-demand Professional FutureMarket studies reveal that demand for people who understand numbers and data and can interpret it to generate insights is growing exponentially and you want to be at the forefront of such industry demand.
Read More
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Statistics provide managers with more confidence in dealing with uncertainty in spite of the flood of available data, enabling managers to more quickly make smarter decisions and provide more stable leadership to staff relying on them.

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