S1/Statistics 1(AS) > A레벨_AS
과정소개
기본설명 교재 : edexcel / 수강기간 : 30일
1.
Unit Title: AS
Mathematics (Statistic 1)
2.
Unit Code:
WST01/01
3.
Content Overview:
Mathematical models in probability and statistics; representation and summary
of data; probability; correlation and regression; discrete random variables;
discrete distributions; the Normal distribution.
4.
Assessment Overview
Unit |
Percentage |
Mark |
Time |
Availability |
S1: Statistics 1 |
33 1/3% of IAS 16 2/3% of IAL |
75 |
1 hour 30 mins |
January, June and October |
5.
Summary
Statistics 1
introduces us to the common measurements we take in statistical situations,
along with an introduction to probability theory.
Chapter 1 -
Mathematical Modelling
We are
introduced to the basic concept of a mathematical model, and how they are used
to simplify real world problems and used to create predictions. A seven stage
process for creating and refining a model is given.
Chapter 2 - Measures of
Location and Spread
Different
types of data must be treated differently, and the different types are
introduced here. We then look at measures of location, such as the mean, median
and mode, and measure of spread such as the interquartile range and standard
deviation. We learn the various methods of estimating these depending on the
data, and how they can be used to compare and contrast data-sets.
Chapter 3 -
Representations of Data
In this
chapter we take the data and statistics we found in the previous chapter and
look at the different ways we can represent them visually. This includes the
drawing of histograms and box-plots. We also look at identifying outliers, and
determining whether or not a data-set is skewed.
Chapter 4 - Probability
The ideas of
theoretical and experimental probability are first introduced, and we learn the
notation of sets and its applications to probability. We see how to represent
probability spaces via Venn-diagrams and tree diagrams. Definitions of
independence and mutual exclusivity are given, and the concept of a conditional
probability is presented.
Chapter 5 - Correlation
and Regression
To determine
the relationship between two variables, we can draw scatter diagrams and lines
of best fit. Instead of guessing, we can use summary statistics to calculate an
exact least squares linear regression line and the product moment correlation
coefficient to see the strength of correlation. Using simple linear coding we
can simplify our calculations.
Chapter 6 - Discrete
Random Variables
In this
chapter we begin introducing a formal framework for random variables and
probability distributions. We look at the rules governing such distributions,
including finding cumulative distributions, expectations and variances. Again
we see how we can apply simple coding to distributions to aid problem solving.
Chapter 7 - The Normal
Distribution
This final 1.chapter
introduces a ubiquitous distribution whose applications are common all over the
world of science and economics. We look at how to standardise a normal
distribution and use the cumulative distribution tables to find probabilities.
We also see how to use the tables in reverse to find key values and the mean
and standard deviation.
강의목록
- 38 강의
- 08:00:52
- 1. 1.1 Mathematical Modelling 00:06:31
- 2. 1.2 Mathematical Modelling 00:05:06
- 3. 2.1 Measures of Location and Spread 00:18:19
- 4. 2.2 Measures of Location and Spread 00:24:25
- 5. 2.3 Measures of Location and Spread 00:27:37
- 6. 2.4 Measures of Location and Spread 00:09:40
- 7. 2.5 Measures of Location and Spread 00:18:58
- 8. 2.6 Measures of Location and Spread 00:10:31
- 9. 3.1 Representations of Data 00:18:45
- 10. 3.2 Representations of Data 00:13:39
- 11. 3.3 Representations of Data 00:09:08
- 12. 3.4 Representations of Data 00:11:46
- 13. 3.5.1 Representations of Data 00:19:18
- 14. 3.6 Representations of Data 00:09:24
- 15. 4.1 Probability 00:11:17
- 16. 4.2 Probability 00:14:30
- 17. 4.3 Probability 00:12:25
- 18. 4.4 Probability 00:08:54
- 19. 4.5 Probability 00:11:59
- 20. 4.6 Probability 00:04:35
- 21. 4.7 Probability 00:08:55
- 22. 4.8 Probability 00:10:02
- 23. 5.1 Correlation and Regression 00:13:52
- 24. 5.2 Correlation and Regression 00:14:39
- 25. 5.3 Correlation and Regression 00:16:48
- 26. 5.4 Correlation and Regression 00:08:55
- 27. 6.1 Discrete Random Variables 00:15:34
- 28. 6.2 Discrete Random Variables 00:13:39
- 29. 6.3 Discrete Random Variables 00:07:15
- 30. 6.4 Discrete Random Variables 00:06:57
- 31. 6.5 Discrete Random Variables 00:11:54
- 32. 6.6 Discrete Random Variables 00:05:36
- 33. 6.7 Discrete Random Variables 00:06:11
- 34. 7.1 The Normal Distribution 00:17:40
- 35. 7.2 The Normal Distribution 00:15:13
- 36. 7.3 The Normal Distribution 00:18:10
- 37. 7.4 The Normal Distribution 00:11:56
- 38. 7.5 The Normal Distribution 00:10:49