# A레벨_Mathematics(AS)_Statistics 1 > A레벨

## 과정소개

교재 : edexcel / 수강기간 : 30일

Chapter 1 Mathematical Modelling

You will be introduced to mathematical modelling and the processes used when creating and testing a mathematical model.

Chapter 2 Measures of Location and Spread

In this chapter you will learn how to identify different types of data, and multiple ways of processing data. In particular how to find the measures of central tendency, such as mean and median for all types of data, as well as other measures of location such as quartiles and percentiles. You will also be introduced to the concept of coding data.

Chapter 3 Representations of Data

In this chapter you will be introduced to various methods of presenting data, such as using histograms, box plots and stem and leaf diagrams. In addition, you will learn how to identify outliers and analyse the skewness of data.

Chapter 4 Probability

This chapter covers a range of probability topics. To begin with there will be a focus on the language used when talking about probability. Following on from that, different methods of presenting information are explored such as Venn diagrams and tree diagrams. In addition various probability formula are covered for various situations, for example, mutually exclusive events, independent events and conditional probability.

Chapter 5 Correlation and Regression

In this chapter you will learn how to plot data on a scatter diagram, and then identify the correlation of the data. To further explore the correlation, how to calculate the least squares regression line will be covered, in addition to the product moment correlation coefficient.

Chapter 6 Discrete Random Variables

Throughout the chapter you will learn about discrete random variable distributions and how to use this information find expected value and variance and how to apply these to problems.

Chapter 7 The Normal Distribution

This chapter will introduce the normal distribution and then the standard normal distribution. You will learn how to use the tables with regard to normal distribution problems.

## 강의목록

• 38 강의
• 07:50:43
• 1. 1.1 Mathematical Models 00:06:31
• 2. 1.2 Designing a Model 00:05:06
• 3. 2.1 Types of Data 00:18:19
• 4. 2.2 Measures of Central Tendency 00:24:25
• 5. 2.3 Other Measures of Location 00:27:37
• 6. 2.4 Measures of Spread 00:09:40
• 7. 2.5 Variance and Standard Deviation 00:18:58
• 8. 2.6 Coding 00:10:31
• 9. 3.1 Histograms 00:18:41
• 10. 3.2 Outliers 00:13:39
• 11. 3.3 Box Plots 00:09:08
• 12. 3.4 Stem and Leaf Diagrams 00:11:46
• 13. 3.5 Skewness 00:19:18
• 14. 3.6 Comparing Data 00:09:29
• 15. 4.1 Understanding the Vocabulary Used in Probability 00:11:17
• 16. 4.2 Venn Diagrams 00:14:16
• 17. 4.3 Mutually Exclusive and Independent Events 00:12:25
• 18. 4.4 Set Notation 00:08:54
• 19. 4.5 Conditional Probability 00:11:59
• 20. 4.6 Conditional Probability in Venn Diagrams 00:04:35
• 21. 4.7 Probability Formulae 00:08:55
• 22. 4.8 Tree Diagrams 00:10:02
• 23. 5.1 Scatter Diagrams 00:13:52
• 24. 5.2 Linear Regression 00:14:39
• 25. 5.3 Calculation Least Squares Linear Regression 00:16:48
• 26. 5.4 The Product Moment Correlation Coefficient 00:08:55
• 27. 6.1 Discrete Random Variables 00:15:35
• 28. 6.2 Finding the Cumulative Distribution for a Discrete Random Variable 00:13:39
• 29. 6.3 Expected Value of a Discrete Random Variable 00:07:15
• 30. 6.4 Variance of a Discrete Random Variable 00:06:57
• 31. 6.5 Expected Value and Variance of a Function of X 00:11:54
• 32. 6.6 Solving Problems Involving Discrete Random Variables 00:05:36
• 33. 6.7 Using Discrete Uniform Distribution as a Model for the Probability Distribution of the Outcomes of Certain Experiments 00:06:11
• 34. 7.1 The Normal Distribution 00:17:40
• 35. 7.2 Using the Tables to Find the Standard Normal Distribution Z 00:15:13
• 36. 7.3 Using the Tables to Find a Value of z Given a Probability 00:08:13
• 37. 7.4 The Standard Normal Distribution 00:11:56
• 38. 7.5 Finding mean and standard deviation 00:10:49

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