Topic I: Introduction

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Topic I Introduction

• Basic Introduction to the Use of Statistical
  Analysis in Business

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Introduction

• What is Statistics?
• Statistics is the science of data. It involves
  collecting, classifying, summarising, organising
  and interpreting numerical information.
  (Traditional Definition)

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Introduction

• The definition of statistics has now evolved and
  can be stated as the understanding, analysis and
  interpretation of data in order to make wise
  decisions in the face of uncertainty

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Sampling

• Population and Sample
• A population is the complete set of all items in
  which an investigator is interested. A
  population is the set of all of the outcomes from
  a system or process that is to be studied. N
  represents population size.

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Examples of Populations

• Names of all registered voters in Jamaica.
• Incomes of all families living in Mona.
• Annual returns of all stocks traded on the
  Trinidad and Tobago Stock Exchange.
• Grade point averages of all the students at
  U.W.I., Mona.

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Sampling

• Population and Sample
• A sample is an observed subset of population
  values with sample size given by n.

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Sampling

• Random Samples
• Random sampling occurs when each possible element
  of the sample has a probability of being sampled.
• Simple random sampling is a procedure in which
  every possible sample of n objects is equally
  likely to be chosen. The resulting sample is
  usually called a random sample.

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Descriptive and Inferential Statistics

• Descriptive Statistics utilises graphical and
  numerical procedures to look for patterns in a
  data set, to summarise the information revealed
  in the data set and to present the information in
  a convenient form.

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Descriptive and Inferential Statistics

• Inferential Statistics utilises sample data to
  make estimates, decisions, predictions, or other
  generalisations about a larger set of data. We
  also use inferential statistics to test
  hypotheses.

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Areas of Impact

• Statistical methods have made an impact on
• General Management
• Research Development
• Finance
• Production
• Sales
• Advertising
• Operations Management
• Auditing

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Areas of Impact Techniques Used

• Manufacturing Production
• Quality Control Charts
• Sales Marketing
• Survey Sampling
• Finance, Accounting Economics
• Regression Analysis
• Public Affairs Policy
• Index numbers (mainly looking at trends)

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Primary Data Sources

• A data source is primary if the data is collected
  by the firm for a specific research project.
• Advantages
• It is tailor-made to the direct need
• More relevant and recent than secondary data
• Persons responsible can ensure that there is no
  research bias
• Ensures that data is free from methodological
  errors
• Disadvantages
• Can be time consuming and costly

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Secondary Data Sources

• Data that have been gathered by another firm or
  organisation for purposes other than addressing
  the issue or problem currently under study.
• Advantages
• Less expensive than collecting data from scratch
• Larger scale studies can be conducted on a
  smaller budget
• The research is unobtrusive
• Does not waste resources collecting readily
  available data
• Disadvantages
• Terms may not be defined properly so there is
  guess work
• The data may not be culturally appropriate
• There may be limited access to the data or a high
  user fee
• The data may not be reliable or valid