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Data Science Statistics for Absolute Beginners

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Data Science Statistics for Absolute Beginners, available at $74.99, has an average rating of 4.5, with 71 lectures, 9 quizzes, based on 5 reviews, and has 153 subscribers.

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You will learn about Students will be have full knowledge of the core statistics needed for Data Science Students will be able to decide and construct different visualizations and graphical representations used in Statistics Identify and be able to carry out calculations related to calculating Measures of Central Tendency Identify and be able to carry out calculations related to calculating Measures of Dispersion Define the right operations to be performed on a set of data and carry out the mathematics behind those operations This course is ideal for individuals who are Beginners in the field of Data Science and Machine Learning wishing to know the core part of the Statistics behind some data science practices or Experts wishing to revise some foundations of statistics for Data Science and Machine Learning It is particularly useful for Beginners in the field of Data Science and Machine Learning wishing to know the core part of the Statistics behind some data science practices or Experts wishing to revise some foundations of statistics for Data Science and Machine Learning.

Enroll now: Data Science Statistics for Absolute Beginners

Summary

Title: Data Science Statistics for Absolute Beginners

Price: $74.99

Average Rating: 4.5

Number of Lectures: 71

Number of Quizzes: 9

Number of Published Lectures: 71

Number of Published Quizzes: 9

Number of Curriculum Items: 80

Number of Published Curriculum Objects: 80

Number of Practice Tests: 2

Number of Published Practice Tests: 2

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

  • Students will be have full knowledge of the core statistics needed for Data Science
  • Students will be able to decide and construct different visualizations and graphical representations used in Statistics
  • Identify and be able to carry out calculations related to calculating Measures of Central Tendency
  • Identify and be able to carry out calculations related to calculating Measures of Dispersion
  • Define the right operations to be performed on a set of data and carry out the mathematics behind those operations

Who Should Attend

  • Beginners in the field of Data Science and Machine Learning wishing to know the core part of the Statistics behind some data science practices
  • Experts wishing to revise some foundations of statistics for Data Science and Machine Learning

Target Audiences

  • Beginners in the field of Data Science and Machine Learning wishing to know the core part of the Statistics behind some data science practices
  • Experts wishing to revise some foundations of statistics for Data Science and Machine Learning

This course will take you from basics of Statistics to more high level view of Statistical computations. This course is for you if you are just getting started with Data Science or Machine Learning and you need to understand the nitty-gritty of all the statistical calculations being used in these fields.

We will start with the big picture of what Statistics is, graphical representations of Data, the measures of Central Tendency and Measures of Dispersion and lastly the coefficient of variations.

Note that this course will not be talking about descriptive statistics though some use cases of the concepts will be discussed where necessary.

In this course I will be taking you through all the nitty-gritty and foundational concepts of statistics that you will need to establish a career in data science and machine learning. This course will prepare you with statistical calculations, graphical representations of data and how to make meaning of these graphs.

At the end of this course, you will know how to represent data graphically in different forms, how to determine the measures of central tendency and dispersions for a giving set of data and how to know which operation is to be performed when giving some set of data.

This is the right course for you if you are new to data science and you want to understand the principles behind different formulas or calculations you will come across in your data science journey.

Course Curriculum

Chapter 1: Welcome

Lecture 1: Welcome to Statistics for Data Science

Lecture 2: The Subject of Statistics

Chapter 2: Frequency Distribution Table

Lecture 1: Section Introduction

Lecture 2: Ungrouped Frequency Distribution Table

Lecture 3: Grouped Frequency Distribution Class Range, Interval and Width

Lecture 4: Grouped Frequency Distribution Class Limit and Class boundary

Lecture 5: Grouped Frequency Distribution Class mark

Lecture 6: Grouped Frequency Distribution Table

Lecture 7: Unequal Class Intervals

Lecture 8: Cumulative Frequency Distribution 1

Lecture 9: Cumulative Frequency Distribution 2

Chapter 3: Graphical Representations of Data

Lecture 1: Section Introduction

Lecture 2: Pictographs

Lecture 3: Simple Bar Chart

Lecture 4: Compound Bar Chart

Lecture 5: Introduction to pie chart

Lecture 6: Pie Chart Sector Calculations

Lecture 7: Visualizing Pie Chart

Lecture 8: Line Graph

Lecture 9: The concept of Histogram

Lecture 10: Histogram Example 1

Lecture 11: Histogram Example 2

Lecture 12: Frequency Polygon

Lecture 13: The Cumulative Frequency Curve or Ogive

Lecture 14: Graphical Representation of Data Practice Test

Chapter 4: Measures of Central Tendency

Lecture 1: Section Introduction

Lecture 2: Central Tendency

Lecture 3: The concept of Central Tendency

Chapter 5: The Mean

Lecture 1: The Arithmetic Mean

Lecture 2: Mean from Assumed Mean

Lecture 3: An Example on calculating Mean 1

Lecture 4: The Sigma Notation

Lecture 5: An Example on calculating Mean 2

Lecture 6: An Example on calculating Mean 3

Lecture 7: Mean of Grouped Frequency Distribution

Chapter 6: The Median

Lecture 1: The Median

Lecture 2: An Example on calculating Median

Lecture 3: Geometrical Determination of the median

Lecture 4: The Median Class

Lecture 5: Estimating the Median using Histogram and Cumulative Frequency Curve

Lecture 6: Introduction to Quartiles and Percentiles

Lecture 7: Estimating the median using the interpolation formulae

Lecture 8: Median Interpolation formulae example

Chapter 7: The Mode

Lecture 1: Introduction to The Mode

Lecture 2: Finding The Mode

Lecture 3: Estimating the mode using the interpolation formulae

Lecture 4: Mode interpolation formulae example

Chapter 8: Pros and Cons of Mean, Median and Mode

Lecture 1: Advantages and Disadvantages of the Mean

Lecture 2: Advantages and Disadvantages of the Median

Lecture 3: Advantages and Disadvantages of the mode

Lecture 4: Measures of Central Tendency Practice Exercise

Chapter 9: Measures of Dispersion: Basics

Lecture 1: Section Introduction

Lecture 2: Introduction to Measures of Dispersion

Lecture 3: The Concept of Measures of Dispersion

Lecture 4: The Range

Lecture 5: Mean Deviation

Lecture 6: Mean Deviation of Ungrouped Frequency Distribution

Lecture 7: Mean Deviation of Grouped Frequency Distribution

Lecture 8: Interquartile and The Semi Interquartile range

Lecture 9: Interquartile and The Semi Interquartile range Example 1

Lecture 10: Interquartile and The Semi Interquartile range of Grouped Distribution

Lecture 11: Disadvantages of the Range, Mean Deviation and Interquartile Range

Chapter 10: Variance and Standard Deviation

Lecture 1: Variance and Standard Deviation

Lecture 2: Standard Deviation Example Part 1

Lecture 3: Standard Deviation Example Part 2

Lecture 4: Standard Deviation for Grouped Distribution Example 1

Lecture 5: Standard Deviation for Grouped Distribution Example 2

Lecture 6: Coefficient of Variation

Lecture 7: Full Example on Measure of Dispersion

Lecture 8: Measures of Dispersion Practice exercise

Lecture 9: Final Remark

Instructors

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Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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