Vital Statistics: an introduction to health science statistics draws on real world, health-related and local examples, with a broad appeal to the Health Sciences student , it demonstrates how an understanding of statistics is useful both in the real world, and in statistics exams.

Written in recognition of Health Sciences courses which require knowledge of statistical literacy, this book guides the reader to an understanding of why, as well as how and when to use statistics.

It explores:

• How data relates to information, and how information relates to knowledge
• How to use statistics to distinguish information from disinformation
• The importance of probability, in statistics and in life
• That inferential statistics allow us to infer from samples to populations, and how useful such inferences can be
• How to appropriately apply and interpret statistical measures of difference and association
• How qualitative and quantitative methods differ, and when it's appropriate to use each
• The special statistical needs of the health sciences, and some especially health science relevant statistics
• The vital importance of computers in the statistical analysis of data, and gives an overview of the most commonly used analyses

Vital Statistics: an introduction to health science statistics draws on real world, health-related and local examples, with a broad appeal to the Health Sciences student , it demonstrates how an understanding of statistics is useful both in the real world, and in statistics exams.

Written in recognition of Health Sciences courses which require knowledge of statistical literacy, this book guides the reader to an understanding of why, as well as how and when to use statistics.

It explores:

• How data relates to information, and how information relates to knowledge
• How to use statistics to distinguish information from disinformation
• The importance of probability, in statistics and in life
• That inferential statistics allow us to infer from samples to populations, and how useful such inferences can be
• How to appropriately apply and interpret statistical measures of difference and association
• How qualitative and quantitative methods differ, and when it's appropriate to use each
• The special statistical needs of the health sciences, and some especially health science relevant statistics
• The vital importance of computers in the statistical analysis of data, and gives an overview of the most commonly used analyses