Hypothesis

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Hypothesis Experiments
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Setting of the Problem
Statement of the Problem
Goal
Establishes
Additional information to comprehend fully the
meaning of the problem
hypothesis
scope
definitions
assumptions
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Hypotheses

• Tentative proposition
• formulated for empirical testing
• Means for guiding and directing in
• kinds of data to be collected
• analysis and interpretation
• have nothing to do with proof
• acceptance or rejection is dependant on data

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Rejecting the Hypothesis

• Often researchers set out to disprove an opposite
  hypothesis
• Example We believe that test strategy A uncovers
  more faults than test strategy B. So our
  hypothesis will be that
• Programmers using test strategy A will uncover
  more faults than programmers using test strategy
  B for the same program.

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Rejecting the Hypothesis

• However, we cannot actually prove this
  hypothesis, we instead will try to disprove an
  opposite hypothesis
• There will be no difference in the fault
  detection rate of programmers using test strategy
  and those using A test strategy B for the same
  program.

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Rejecting the Hypothesis

• If there is a significant difference in the fault
  detection rate we can reject the no difference
  and by default, support our research hypothesis
• the no difference - null hypothesis

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Experiments

• Studies involving the intervention by the
  researcher beyond that required for measurement
• usually, manipulate some variable in a setting
  and observe how it affects the subject (cause and
  effect)
• there is at least one independent variable and
  one dependent variable

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Independent Variable

• Variable the researcher manipulates
• For our hypothesis concerning test strategies, we
  took a sample of software engineers and randomly
  assigned each to one of two groups one using
  test strategy A and the other test strategy B.
  Later we compared the fault detection rate in the
  two groups.

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Independent Variable

• We are manipulating the test strategy, thus it is
  the independent variable

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Dependent Variable

• Variable that is potentially influenced by the
  independent variable
• in our last example, the dependent variable is
  fault detection rate
• Presumably the fault detection rate is influence
  by test strategy applied
• there can be more than one dependent variable

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Advantages of Experiments

• Causality can not be proved with certainty but
  probability of one variable being linked to
  another could be established convincingly.
• Can control contamination from extraneous
  variables

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Disadvantages of Experiments

• Artificiality of the laboratory
• study can be generalized for example form college
  students to professionals is open to question.
• If experiment is unsuccessfully disguised,
  volunteers are often most interested in the topic

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Conducting an Experiment

• Seven activities
• select relevant variable
• specify the level(s) of treatment
• control the experimental environment
• choose the experimental design
• select and assign the subjects
• pilot-test, revise, and test
• analyze the data

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Select the Relevant Variables

• Translate our problem into the hypothesis that
  best states the objectives of the research
• how concepts are transformed into variables to
  make them measurable and subject to testing
• research question
• Does a product presentation that describes
  product benefits in the introduction lead to
  improved retention of the product knowledge?

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The Speculation

• Product presentations in which the benefits
  module is placed in the introduction of a 12
  minute message produce better retention of
  product knowledge that those where the benefits
  module is placed in the conclusion.

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Researchers Challenge

• Select variables that are the best operational
  representations of the original concepts.
• Sales presentation, product benefits retention,
  product knowledge, better
• Determine how many variables to test
• constrained by budget, the time allocated, the
  availability of appropriate controls, and the
  number of subjects. ( For statistical reasons,
  there must be more subjects than variables)

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Researchers Challenge

• select or design appropriate measures for them
• thorough review of the available literature and
  instruments.
• Adapted to unique needs of the research situation

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Treatment Level

• Of the independent variable are the distinctions
  the researcher makes between different aspects of
  the treatment level.
• For example if salary is hypothesized to have an
  effect on employees (high, middle, low ranges)
• common sense and simplicity
• Notice several levels of the independent
  variables may be need to test order- of
  presentation effects

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Treatment Level

• Control group - provide a base level for
  comparison
• control group is composed of subjects who are not
  exposed to the independent variable(s) in
  contrast to those who receive the experimental
  treatment

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Controlling the Experimental Environment

• Extraneous variables - potential for distorting
  the effect of the treatment on the dependent
  variable
• for example, instructions would likely be
  videotaped for consistency
• arrangements of the room, experimenters contact
  with subjects, time of administration -all must
  be consistent

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Other Forms of Controlling Experiment

• When the subjects do not know if they are
  receiving the experimental treatment, they are
  said to be blind
• When the experimenters do not know if are giving
  the the treatment to the experimental group or
  the control, they experiment is double blind

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Choosing an Experimental Design

• Experimental designs are unique to the
  experimental method
• statistical plans to designate relationships
  between experimental treatments and the
  experimenters observations
• improve the probability that the observed change
  in the dependent variable was caused by the
  manipulation of the independent variable

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Selecting and Assigning Subjects

• Representative population
• randomization
• matching - quota sampling

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Pilot Testing

• Reveal errors in the design
• allow refinements
• reduction in force

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Analyzing Data

• If planning and pretesting have occurred, the
  experimental data will take on an order and
  structure and the choice of statistical
  techniques has been determined by the levels of
  the treatment condition, pretests and posttests
  and the group structure