Chapter 1. Basic concepts of group theory

Keyword(s):  
2021 ◽  
pp. 1-26
Author(s):  
Andrew L-T Choo

Chapter 1 examines a number of basic concepts and distinctions in the law of evidence. It covers facts in issue and collateral facts; relevance, admissibility, and weight; direct evidence and circumstantial evidence; testimonial evidence and real evidence; the allocation of responsibility; exclusionary rules and exclusionary discretions; free(r) proof; issues in criminal evidence; civil evidence and criminal evidence; the implications of trial by jury; summary trials; law reform; and the implications of the Human Rights Act 1998. This chapter also presents an overview of the subsequent chapters.


Evidence ◽  
2018 ◽  
Author(s):  
Andrew L-T Choo

Chapter 1 examines a number of basic concepts and distinctions in the law of evidence. It covers facts in issue and collateral facts; relevance, admissibility, and weight; direct evidence and circumstantial evidence; testimonial evidence and real evidence; the allocation of responsibility; exclusionary rules and exclusionary discretions; free(r) proof; issues in criminal evidence; civil evidence and criminal evidence; the implications of trial by jury; summary trials; law reform; and the implications of the Human Rights Act 1998. This chapter also presents an overview of the subsequent chapters.


Author(s):  
M. Hassan Murad ◽  
Qian Shi

Chapter 1 reviews basic concepts of biostatistics. Topics include descriptive data, probability and odds, estimation and sampling error, hypothesis testing, and power and sample size calculations. The discussion of descriptive data includes types of data (discrete vs continuous and nominal vs ordinal), central tendency (mean, median, and mode), skewed distributions, and measures of dispersion (range, variance, standard deviation). Probability and odds are broken down into laws of probability, odds, odds ratio, relative risk, and probability distribution. The examination of estimation and sampling error covers concepts such as random error, bias, standard error, point estimation, and interval estimation.


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