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Basic Statistics for Data Analytics

Batch Price From £360 (approx. $464 USD) View Dates & Prices
Custom Price From £240 (approx. $309 USD) Price Calculator & Booking
Short course on Statistics for Data Analytics
Total Duration: 12-Hour
Course level: Beginner
Delivery Method: Instructor-led Virtual Classes
Certification: Certificate of Completion will be provided after completing the course

Course Overview

This course comprehensively introduces the key statistical concepts and techniques essential for data analytics using Excel. It is designed for individuals looking to build a statistics foundation, focusing on practical applications in data-driven decision-making. Throughout the course, students will learn to apply statistical methods to real-world data, interpret the results, and use these insights to inform business decisions.

Requirements

  • Basic arithmetic skills (e.g., addition, subtraction, multiplication, division)
  • Basic understanding of Microsoft Excel
  • No statistics background is required

You may also complete the following course(s) before attending the Basic Statistics for Data Analytics course but they are not mandatory:

Course Dates, Prices & Enrolment

All Training Physical Classes Virtual Classes
Time Zone:
There is no date for this course at this moment. Please complete the BOOKING REQUEST FORM below or come back to this page again later.

Course Content

  1. Introduction to Statistics and Data Analytics
    • Definition and importance of statistics in data analytics
    • Types of data: qualitative vs. quantitative
    • Types of statistics: descriptive vs. inferential
  2. Descriptive Statistics
    • Measures of central tendency: mean, median, mode
    • Measures of variability: range, variance, standard deviation
    • Data visualisation: histograms, bar charts, box plots, scatterplots
  3. Probability Basics
    • Definition and basic concepts of probability
    • Probability rules: addition and multiplication rules
    • Independent and dependent events
    • Conditional probability
  4. Probability Distributions
    • Discrete vs. continuous probability distributions
    • Binomial distribution
    • Normal distribution and its properties
    • Standard normal distribution and z-scores
  5. Inferential Statistics
    • Sampling methods and sample size
    • Central Limit Theorem
    • Confidence intervals
  6. Hypothesis Testing
    • Null hypothesis
    • T-tests
    • Chi-squire test of association
  7. Correlation and Regression
    • Scatterplots and correlation
    • Pearson correlation coefficient
    • Simple linear regression: interpretation of slope and intercept
    • Introduction to multiple regression

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