Lesson 1, Topic 1
In Progress

1.1. Investigate life and work related problems using data and probabilities

ryanrori February 3, 2021

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To reason statistically – which is essential to being an informed citizen, employee, and consumer – we need to learn about data analysis and related aspects of probability.

The amount of statistical information available to help make decisions in business, politics, research, and everyday life is staggering: consumer surveys guide the development and marketing of products, experiments evaluate the safety and efficacy of new medical treatments, statistics sway public opinion on issues and represent – or misrepresent – the quality and effectiveness of commercial products. 

Through experiences with the collection and analysis of data, we learn how to interpret such information.

Statistics is a mathematical science pertaining to the collection, analysis, interpretation, and presentation of data. It is applicable to a wide variety of academic disciplines, from the physical and social sciences to the humanities; it is also used for making informed decisions in all areas of business and government.

Statistical methods can be used to summarise or describe a collection of data; this is called descriptive statistics. In addition, patterns in the data may be modelled in a way that accounts for randomness and uncertainty in the observations, to draw inferences about the process or population being studied; this is called inferential statistics. Both descriptive and inferential statistics can be considered part of applied statistics. There is also a discipline of mathematical statistics, which is concerned with the theoretical basis of the subject.

There are various types of statistics.  Some of these are described below:

  • Descriptive Statistics: This branch of statistics is concerned with the systematic collection of information, its presentation and description.  In other words we are dealing here only with information gathered in a statistical format.

Individuals concerned for the risks attached to their own lives may wish to research information about the chances of these (and other) occurrences arising to themselves:

  • Deaths, births and marriages in a certain section of the population.
  • Numbers of persons contracting a serious disease within a given period.
  • Employment categories for individuals of a certain age, gender, race group and with certain qualifications.
  • Retrenchments, terminations and retirements across similar groupings in a given year.
  • Hijackings or armed robberies occurring in a certain area
  • The number of personal risks occurring within insurance claims categories across sectors of the population.
  • The total number of road accidents occurring detailing fatalities, injuries and total cost to the economy in a given year.
  • The performance of the Rand against foreign currencies in a given period.
  • Inflation figures concerning consumer prices, gross national product, budget spending and consumer spending patterns.
  • Costs associated with personal expenditure such as house prices, insurance costs, taxes, building costs, educational costs, entertainment and others.

These sets of information merely represent and measure data, and offer arithmetical statistics.  They are used to determine average results of risks.  They are historical in nature and look back to describe what has happened. 

  • Inferential statistics: Inferential statistics are of more value for risk assessment activities.  They take the historical information, and use it to make inferences (assumptions).  

Some common everyday examples would include a medical doctor taking an individual blood sample, and on the basis of that sample would make an inference about the person’s blood supply.  Or in insurance, where rates are determined for personal accident insurance based on the age, occupation, lifestyle and habits, and the hobbies of an individual.

This type of inferential work is needed to estimate the types and magnitude of risks that face us in own life.

Note: The word statistics is also the plural of statistic (singular), which refers to the result of applying a statistical algorithm to a set of data, as in employment statistics, accident statistics, crime statistics, etc.