Analyze Data Using Essential Statistics for Analytics
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What you'll learn
Explain core statistical concepts, data types, and measurement scales used in analytics.
Create and interpret charts, histograms, scatter plots, and box plots for data analysis.
Apply appropriate sampling techniques to support accurate, data-driven decision-making.
Skills you'll gain
- Box Plots
- Histogram
- Exploratory Data Analysis
- Probability & Statistics
- Data Literacy
- Statistics
- Data Analysis Software
- Data Analysis
- Analytics
- Statistical Methods
- Quantitative Research
- Business Analytics
- Data Visualization Software
- Statistical Analysis
- Statistical Visualization
- Sampling (Statistics)
- Statistical Programming
- Descriptive Statistics
Tools you'll learn
Details to know
February 2026
12 assignments
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There are 3 modules in this course
By the end of this course, learners will be able to analyze datasets using fundamental statistical concepts, interpret different types of data, create meaningful visualizations, and apply appropriate sampling techniques for data-driven decision-making.
Statistics Essentials for Analytics β Beginners is designed to build a strong statistical foundation for aspiring analysts, data professionals, and business learners with no prior background in statistics. The course progresses from core statistical concepts and data types to practical visualization techniques and sampling methodologies used in real-world analytics. Learners will explore variables, measurement scales, and graphical representations, followed by hands-on exposure to charts, histograms, scatter plots, and box plots using industry-relevant tools such as Excel and R. What makes this course unique is its balanced focus on conceptual clarity and practical application, reinforced through structured lessons, quizzes, and graded assessments. Each module is carefully aligned to analytics workflows, ensuring learners not only understand statistical theory but can also apply it confidently to real datasets. Upon completion, learners will gain the statistical literacy required to interpret data accurately, communicate insights effectively, and build a strong foundation for advanced analytics and data science learning paths.
This module introduces the fundamental concepts of statistics, including the role of data in decision-making, types of variables, measurement scales, and basic graphical techniques used to summarize and interpret data for analytical purposes.
What's included
7 videos4 assignments
7 videosβ’Total 33 minutes
- Introduction to Elements of Statisticsβ’7 minutes
- Random Numbers in Excelβ’5 minutes
- Variables and Types of Variablesβ’2 minutes
- Quantitative and Qualitativeβ’7 minutes
- Understanding Ordinal Scaleβ’5 minutes
- Different Graphical Techniquesβ’3 minutes
- Examples on Graphical Representationβ’4 minutes
4 assignmentsβ’Total 60 minutes
- Getting Started with Statisticsβ’10 minutes
- Understanding Variables and Measurement Scalesβ’10 minutes
- Introduction to Graphical Representationβ’10 minutes
- Foundations of Statistics and Data Typesβ’30 minutes
This module focuses on data visualization techniques, emphasizing the use of charts and plots to explore data distribution, relationships, and patterns using statistical tools and R software.
What's included
7 videos4 assignments
7 videosβ’Total 37 minutes
- Bar Chart using R Softwareβ’6 minutes
- Pie Chart using R Softwareβ’2 minutes
- Entering Values to Variablesβ’3 minutes
- Illustration on Using Box Plotβ’9 minutes
- Histogram Bar Graphβ’6 minutes
- Examples on Histogram using Rβ’5 minutes
- Plotting the Scatter Plotβ’6 minutes
4 assignmentsβ’Total 60 minutes
- Creating Charts Using Rβ’10 minutes
- Exploring Data Distributionβ’10 minutes
- Advanced Visual Analysisβ’10 minutes
- Visualizing Data Using Charts and Plotsβ’30 minutes
This module explains statistical sampling methods, highlighting probability and non-probability techniques and their application in drawing representative samples for reliable data-driven conclusions.
What's included
6 videos4 assignments
6 videosβ’Total 31 minutes
- Different types of Sampling Techniquesβ’3 minutes
- Drawing Sample in Rβ’5 minutes
- Different Types of Sampling Techniqueβ’3 minutes
- Different Types of Sampling Technique Continueβ’9 minutes
- Probability Samplingβ’6 minutes
- Non-Probability Samplingβ’6 minutes
4 assignmentsβ’Total 60 minutes
- Basics of Samplingβ’10 minutes
- Sampling Methods in Detailβ’10 minutes
- Probability vs Non-Probability Samplingβ’10 minutes
- Sampling Techniques and Data Collectionβ’30 minutes
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