Agricultural and Biological Statistics

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Agricultural and Biological Statistics
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Introduction to Statistics

• Chapter 1

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What is Statistics?

• Statistics provides the basis for investigations
  in many fields of knowledge, such as social,
  physical and biological sciences, engineering,
  education, business, medicine and law.
• Information is acquired in the form of numbers,
  data.

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What is Statistics?

• An analysis of this data is made to obtain a
  better understanding of the phenomenon of
  interest, and some conclusions may be drawn.

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What is Statistics?

• Definition of Statistics making sense of
  figures (numbers). It is the methodology which
  scientists and mathematicians have developed for
  interpreting and drawing conclusions from data.

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What is Statistics?

• Statistical Inference refers to a process of
  making informed decisions.
• In statistical inference it is common to collect
  observations on a few items (a sample), analyze
  them using a well known procedure, and then infer
  that since the findings obtain (are the case) for
  the sample, they must obtain for all the items
  (the universe) or population.

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Examples of This Process

• Determining who won an election even before the
  polls close.
• Determining the average life of light bulbs even
  before they are produced.
• Determining the quality of an equestrian safety
  helmet that wont be tested.
• Determining the quantity of corn flakes in a 64
  oz. box.
• These things involve inductive logic.

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Common Misuses of Statistics
In our everyday life we are bombarded with
presentations supported by statistics

• Bias quoting statistics to prove the
  superiority of a product, competitors seem to be
  using other statistics to prove the opposite.
• Data could be biased.
• Poor questionaires
• Leading questions

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Common Misuses of Statistics

• Faulty Generalizations - when one tries to say
  using statistics that the data has a certain
  meaning.
• Sample size too small types of fish in lake
  taken from a sample of five.
• Samples that are non typical respondents not
  typical or random from population.

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Common Misuses of Statistics

• Faulty Deduction What is true for the whole is
  not true for the individual.
• 60 of the trees in the US are Oak
• This wouldnt be true for the south would it?

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Common Misuses of Statistics

• Noncomparable Data Comparisons made between
  items that arent really alike.
• Cost of an auto before airbags and other safety
  features and those produced today.
• This creates a problem with price indexes because
  the technology to produce autos is constantly
  changing.

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Common Misuses of Statistics

• Errors in Semantics Slanted or colored words
  being used to influence the respondent.
• You dont really like this product, do you?
• Questions that suggest an answer.

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Common Misuses of Statistics

• Assuming Causation from Correlation
• If one thing precedes another in time then it is
  assumed that it (the first) causes the other (the
  second)
• Get wet Catch cold
• Wintertime Stay indoors Catch cold
• A and B fluctuate together (A and B are
  correlated)
• It may be that A causes B or B A or that C causes
  both A and B or that the correlations are due to
  chance.

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Assuming Causation from Correlation

• Statistics cannot be used to infer causation from
  correlation. All statistics can say is that the
  factors move together in some fashion.

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Common Misuses of Statistics

• Oversimplification
• Sales have increased 125
• What is missing?
• Time Frame
• Advertisers use this technique

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Common Misuses of Statistics

• Spurious Accuracy
• Answers generated with a large number of trailing
  decimals.
• If data is accurate to the nearest 100, an
  average should be presented to the nearest 100.

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Statistical Analysis
This is the whole process of organizing,
processing, summarizing, and drawing
conclusions from the data. In statistical
analysis, methods of description and methods of
analysis combine.
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Statistical Analysis Flow Diagram
For a Sample
For a Population