Even You Can Learn Statistics and Analytics

: 6 Months
: Self Paced, AI Tutor
: Beginner
: Available Immediately

R6200,00R7300,00

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Learn the basic concepts of statistics and analysis with the Even You Can Learn Statistics and Analytics course and lab. This will provide you with the knowledge to apply statistics and analytics in your life and you will have the opportunity to learn and practice the most commonly used statistical methods while using Microsoft Excel. Every concept is explained in plain English, without the use of higher mathematics or mathematical symbols. The course uses a Concept-Interpretation approach to help you learn statistics and analytics. This course will provide you a complete package with hands-on experience in applying statistics and analytics.

Lessons

19+ Lessons | 189+ Exercises | 233+ Quizzes | 143+ Flashcards | 143+ Glossary of terms

TestPrep

39+ Pre Assessment Questions | 2+ Full Length Tests | 39+ Post Assessment Questions | 78+ Practice Test Questions

Hand on lab

20+ LiveLab | 13+ Video tutorials | 16+ Minutes

Lessons 1: Introduction

  • Mathematics Is Always Optional!
  • Learning with the Concept-Interpretation Approach

Lessons 2: Fundamentals of Statistics

  • The First Three Words of Statistics
  • The Fourth and Fifth Words
  • The Branches of Statistics
  • Sources of Data
  • Sampling Concepts
  • Sample Selection Methods
  • One-Minute Summary
  • References

Lessons 3: Presenting Data in Tables and Charts

  • Presenting Categorical Variables
  • Presenting Numerical Variables
  • “Bad” Charts
  • One-Minute Summary
  • References

Lessons 4: Descriptive Statistics

  • Measures of Central Tendency
  • Measures of Position
  • Measures of Variation
  • Shape of Distributions
  • Important Equations
  • One-Minute Summary
  • References

Lessons 5: Probability

  • Events
  • More Definitions
  • Some Rules of Probability
  • Assigning Probabilities
  • One-Minute Summary
  • References

Lessons 6: Probability Distributions

  • Probability Distributions for Discrete Variables
  • The Binomial and Poisson Probability Distributions
  • Continuous Probability Distributions and the Normal Distribution
  • The Normal Probability Plot
  • Important Equations
  • One-Minute Summary
  • References

Lessons 7: Sampling Distributions and Confidence Intervals

  • Foundational Concepts
  • Sampling Error and Confidence Intervals
  • Confidence Interval Estimate for the Mean Using the t Distribution (σ Unknown)
  • Confidence Interval Estimation for Categorical Variables
  • Confidence Interval Estimation When Normality Cannot Be Assumed
  • Important Equations
  • One-Minute Summary
  • References

Lessons 8: Fundamentals of Hypothesis Testing

  • The Null and Alternative Hypotheses
  • Hypothesis Testing Issues
  • Decision-Making Risks
  • Performing Hypothesis Testing
  • Types of Hypothesis Tests
  • One-Minute Summary
  • References

Lessons 9: Hypothesis Testing: Z and t Tests

  • Test for the Difference Between Two Proportions
  • Test for the Difference Between the Means of Two Independent Groups
  • The Paired t Test
  • Important Equations
  • One-Minute Summary
  • References

Lessons 10: Hypothesis Testing: Chi-Square Tests and the One-Way Analysis of Variance (ANOVA)

  • Chi-Square Test for Two-Way Tables
  • One-Way Analysis of Variance (ANOVA): Testing fo…ferences Among the Means of More Than Two Groups
  • Important Equations
  • One-Minute Summary
  • References

Lessons 11: Simple Linear Regression

  • Basics of Regression Analysis
  • Developing a Simple Linear Regression Model
  • Measures of Variation
  • Inferences About the Slope
  • Common Mistakes When Using Regression Analysis
  • Important Equations
  • One-Minute Summary
  • References

Lessons 12: Multiple Regression

  • The Multiple Regression Model
  • Coefficient of Multiple Determination
  • The Overall F Test
  • Residual Analysis for the Multiple Regression Model
  • Inferences Concerning the Population Regression Coefficients
  • One-Minute Summary
  • References

Lessons 13: Introduction to Analytics

  • Basic Concepts
  • Descriptive Analytics
  • Typical Descriptive Analytics Visualizations
  • One-Minute Summary
  • References

Lessons 14: Predictive Analytics

  • Predictive Analytics Methods
  • More About Predictive Models
  • Tree Induction
  • Clustering
  • Association Analysis
  • One-Minute Summary
  • References

Appendix A: Microsoft Excel Operation and Configuration

  • Conventions for Keystroke and Mouse Operations
  • Microsoft Excel Technical Configuration

Appendix B: Review of Arithmetic and Algebra

  • Symbols

Appendix C: Statistical Tables

Appendix D: Spreadsheet Tips

  • Chart Tips
  • Function Tips

Appendix E: Advanced Techniques

  • Advanced How-To Tips
  • Analysis ToolPak Tips

Hands-on LAB Activities

Presenting Data in Tables and Charts

  • Creating a Bar Chart
  • Creating a Pie Chart
  • Creating a Pivot Table
  • Modifying and Refreshing the Pivot Table
  • Creating a Bar Chart
  • Creating a Line Chart
  • Creating a Scatter Plot

Descriptive Statistics

  • Calculating Mean
  • Calculating Median and Mode
  • Calculating First Quartile

Probability

  • Working with Probability

Probability Distributions

  • Calculating the Value of a Normal Random Variable
  • Using the Poisson Distribution
  • Computing Binomial Probabilities

Sampling Distributions and Confidence Intervals

  • Calculating the Confidence Interval

Hypothesis Testing: Z and t Tests

  • Analyzing the Hypothesis Test for the Pooled-Variance t-Test

Hypothesis Testing: Chi-Square Tests and the One-Way Analysis of Variance (ANOVA)

  • Analyzing the Hypothesis Test for the Chi-Square Test

Simple Linear Regression

  • Creating a Histogram

Multiple Regression

  • Using Multiple Regression

Introduction to Analytics

  • Creating a Sparkline
Training Method

Self paced, AI Tutor

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