## Topic outline

• Forum
• ### CHAPTER 1: INTRODUCTION TO STATISTICS

1.1 OVERVIEW

1.2 DESCRIPTIVE AND INFERENTIAL STATISTICS

1.3 VARIABLE AND TYPES OF DATA

1.4 DATA COLLECTION AND SAMPLING TECHNIQUES

1.5 OBSERVATIONAL AND EXPERIMENTAL STUDIES

• ### CHAPTER 2 (PART 1): DESCRIPTIVE STATISTICS

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2.1 DATA ORGANIZATION AND FREQUENCY DISTRIBUTION

2.2 TYPES OF GRAPH

• ### CHAPTER 2(PART 2): DESCRIPTIVE STATISTICS

2.3 DATA DESCRIPTION

2.3.1 Measures of Central Tendency

2.3.2 Measures of Variation

2.3,3 Measures of Position

2.4 EXPLORATORY DATA ANALYSIS

• ### CHAPTER 3(PART 1): PROBABILITY

3.1 BASIC IDEA AND CONSIDERATION

3.2 MUTUALLY EXCLUSIVE EVENTS

• ### CHAPTER 3(PART 2): PROBABILITY

3.3 INDEPENDENCE EVENTS

3.4 CONDITIONAL PROBABILITY

3.4.1 Bayes' Theorem

3.5 COUNTING RULES AND PROBABILITY

• ### CHAPTER 4(PART 1):DISCRETE PROBABILITY DISTRIBUTIONS

4.1 DISCRETE RANDOM VARIABLE AND PROBABILITY DISTRIBUTIONS

4,2 MEAN AND VARIANCE

• ### CHAPTER 4(PART 2): DISCRETE PROBABILITY DISTRIBUTIONS

4.3 BINOMIAL DISTRIBUTION

4.4 POISSON DISTRIBUTION

• ### CHAPTER 5(PART 1): CONTINUOUS PROBABILITY DISTRIBUTIONS

5.1 CONTINUOUS RANDOM VARIABLES AND PROBABILITY DENSITY FUNCTION

5.2 MEAN AND VARIANCE

• ### CHAPTER 5(PART 2: CONTINUOUS PROBABILITY DISTRIBUTIONS

5.3 NORMAL DISTRIBUTION

5.4 THE CENTRAL LIMIT THEOREM

5.5 NORMAL APPROXIMATION TO BINOMIAL DISTRIBUTION

5.6 NORMAL APPROXIMATION TO POISSON DISTRIBUTION

• ### CHAPTER 6: CORRELATION AND SIMPLE LINEAR REGRESSION

6.1 INTRODUCTION

6,2 LINEAR CORRELATION

6.3 SIMPLE LINEAR REGRESSION MODEL