Statistics and Data Analysis Course for Beginners | Interactive Lessons, PDF eBook, Excel Workbook and Python

$55.00

Learn statistics from scratch and use it with confidence. Statistics and Data Analysis: From Basic Concepts to Practical Applications is a complete beginner course. It takes you from your first average to analysing real-looking datasets and writing clear, honest reports. You only need basic maths.

Description

 

What you get

  • Interactive HTML course: 15 modules, 90 quiz questions with instant feedback, 62 exercises with answers, progress tracking, bookmarks and a 158-term glossary. It works offline on desktop and mobile.
  • 9 interactive tools:descriptive statistics calculator
  • probability calculators
  • confidence intervals, plus a simulation of what “95% confidence” really means
  • central limit theorem simulator
  • hypothesis-testing calculator covering 7 tests
  • 8 graded testing exercises
  • chart explorer
  • regression visualiser
  • “Choose the right statistical method” decision tool
  • 157-page PDF eBook: every module with charts, 51 formulas with every symbol explained, step-by-step worked examples, and an answers appendix.
  • Editable Excel workbook: example and blank versions. It covers data cleaning, descriptive statistics, frequency tables, probability, confidence intervals, hypothesis tests, regression, a project template and a dashboard. It uses live formulas and no macros.
  • Python package: 7 tested Jupyter notebooks and scripts using pandas, SciPy and Matplotlib, with their outputs already included.
  • 7 real-world projects: household spending, a customer survey, sales over time, student performance, advertising and sales, an A/B test, and a dashboard. Each one goes from question to final report.
  • 8 printable bonus resources:formula sheet
  • chart selection guide
  • method decision tree
  • data cleaning checklist
  • report template
  • dataset worksheet
  • glossary
  • final project checklist

What you’ll learn

  • Mean, median, standard deviation and quartiles
  • Charts that tell the truth, and how to spot misleading ones
  • Probability, the normal and binomial distributions, and sampling
  • Confidence intervals and p-values, interpreted correctly
  • t-tests, chi-square tests, ANOVA, correlation and regression
  • Data cleaning in Excel and Python

The course also explains:

  • why correlation isn’t causation
  • why “significant” doesn’t always mean important
  • how to report results honestly

Good to know

  • All datasets are simulated for teaching, so every number can be checked.
  • This is an educational course. It is not a professional qualification.
  • Instant digital download.

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