# Introduction to Statistics for Data Science

Site: | Pedagogy Trainings - Learning Management System |

Course: | Pedagogy Trainings - Learning Management System |

Book: | Introduction to Statistics for Data Science |

Printed by: | |

Date: | Monday, 13 July 2020, 2:39 PM |

## Table of contents

- 1. An Introduction
- 2. Grouping and Displaying Data to Convey Meaning (Tables and Graphs)
- 3. Measures of Central Tendency | Dispersion in Frequency Distribution
- 4. Probability Part 1: An Introduction
- 5. Probability Part 2: Distributions
- 6. Sampling in Statistics & its Distributions
- 7. Testing of Hypothesis: One Sample tests
- 8. Chi-Square and Analysis of Variance
- 9. Correlation & Regression

## 1. An Introduction

**Learning Objectives:**

- To examine who would need statistics and how it can be used
- To provide a brief history of the use of statistics
- Sub-Divisions within statistics

### 1.1. Why should you take this course and who uses statistics anyhow?

### 1.2. History of Statistics

The word statistik comes from the Italian word statista (meaning 'statesman'). It was first used by Gottfried Achenwall (1719 - 1772), a professor in Marlborough Russia.

Dr. EAW Zimmerman introduced the word statistics into England. Its use was popularized by Sir John Sinclair in his work Statistical Account of Scotland 1791 - 1799. Much before the eighteen century, however people by then had been recording and using data.

## 2. Grouping and Displaying Data to Convey Meaning (Tables and Graphs)

### 2.1. How can we arrage data?

### 2.2. Examples of raw data

### 2.3. Arranging and Constructing a Frequency Distribution

- One can quickly notice the lowest and highest values in the data
- The data can be divided into sections easily
- Values appearing more than once can be identified
- Distance can be measured between the succeeding values in the data

### 2.4. Graphing Frequencies

Graphing Frequencies

### 2.5. Chapter review

Chapter review

### 2.6. Equations used along

Equations used along

### 2.7. Review and Application Exercises

Review and Application Exercises

## 3. Measures of Central Tendency | Dispersion in Frequency Distribution

Measures of Central Tendency | Dispersion in Frequency Distribution

### 3.1. MCT: The Arithmetic Mean

MCT: The Arithmetic Mean

### 3.2. MCT: The Weighted Mean

MCT: The Weighted Mean

### 3.3. MCT: The Median

MCT: The Median

### 3.4. MCT: The Mode

MCT: The Mode

### 3.5. Why Dispersion is important?

Why Dispersion is important?

### 3.6. Measures of Dispersion

Measures of Dispersion

### 3.7. Measures of Average Deviation

Measures of Average Deviation

### 3.8. The Coefficient of Variation: Relative Dispersion

The Coefficient of Variation: Relative Dispersion

### 3.9. Conclusion: Using Flow Charts

Conclusion: Using Flow Charts

## 4. Probability Part 1: An Introduction

Probability Part 1: An Introduction

### 4.1. Probability: The study of odd and even

Probability: The study of odd and even

### 4.2. Basic Terminology & types of Probability

Basic Terminology & types of Probability

### 4.3. Probability Rules

Probability Rules

### 4.4. Probabilities: Conditions of Statistical Independence

Probabilities: Conditions of Statistical Independence

### 4.5. Probabilities: Conditions of Statistical dependence

Probabilities: Conditions of Statistical dependence

### 4.6. Probabilities: Bayes Theorem

Probabilities: Bayes Theorem

## 5. Probability Part 2: Distributions

Probability Part 2: Distributions

### 5.1. What is a Probability Distribution?

What is a Probability Distribution?

### 5.2. Random Variables

Random Variables

### 5.3. Binomial Distribution

Binomial Distribution

### 5.4. Poisson Distribution

Poisson Distribution

### 5.5. Normal Distribution: of a Continuous Random Variable

Normal Distribution: of a Continuous Random Variable

### 5.6. Choosing the correct Probability Distribution

Choosing the correct Probability Distribution

## 6. Sampling in Statistics & its Distributions

Sampling in Statistics & its Distributions### 6.1. An introduction to Sampling

An introduction to sampling

### 6.2. Random & Non-random Sampling

Random & Non-random Sampling

## 7. Testing of Hypothesis: One Sample tests

Testing of Hypothesis: One Sample tests

### 7.1. Basic concepts to Hypothesis testing

Basic concepts to Hypothesis testing

### 7.2. Testing Means when the Population Std. Deviation is known

Testing Means when the Population Std. Deviation is known

### 7.3. Testing Means when the Population Std. Deviation is not known

Testing Means when the Population Std. Deviation is not known

## 8. Chi-Square and Analysis of Variance

Chi-Square and Analysis of Variance

### 8.1. Chi-Square as a test of Independence

Chi-Square as a test of Independence

### 8.2. Analysis of Variance

Analysis of Variance

### 8.3. Inferences about a Population Variance

Inferences about a Population Variance

### 8.4. Inferences about two Population Variance

Inferences about two Population Variance

## 9. Correlation & Regression

Correlation & Regression

### 9.1. Introduction to Regression Analysis

Introduction to Regression Analysis

### 9.2. Estimating using a Regression Line

Estimating using a Regression Line

### 9.3. Correlation Analysis

Correlation Analysis

### 9.4. Making Inferences about Population Parameters

Making Inferences about Population Parameters

### 9.5. Limitations, Errors and caveats to Regression Analysis

Limitations, Errors and caveats to Regression Analysis