hypothesis

Sociology

(noun)

Used loosely, a tentative conjecture explaining an observation, phenomenon, or scientific problem that can be tested by further observation, investigation, or experimentation.

Related Terms

  • control
  • experiment
  • dependent variable
  • independent variable
Writing

(noun)

Used loosely, a tentative conjecture explaining an observation, phenomenon or scientific problem that can be tested by further observation, investigation and/or experimentation.

Related Terms

  • claim
  • fact
Biology

(noun)

an educated guess that usually is found in an "if...then..." format

Related Terms

  • theory
  • control group
  • scientific method
Economics

(noun)

An assumption taken to be true for the purpose of argument or investigation.

Psychology

(noun)

A tentative conjecture explaining an observation, phenomenon, or scientific problem that can be tested by further observation and/or experimentation.

Related Terms

  • theory
  • natural science
  • causation
  • variable
  • case study
  • scientific method
  • hard science
  • soft science
  • social science

(noun)

A tentative conjecture explaining an observation, phenomenon, or scientific problem that can be tested by further observation, investigation, and/or experimentation.

Related Terms

  • theory
  • natural science
  • causation
  • variable
  • case study
  • scientific method
  • hard science
  • soft science
  • social science

Examples of hypothesis in the following topics:

  • Student Learning Outcomes

    • Conduct and interpret hypothesis tests for two population means, population standard deviations known.
    • Conduct and interpret hypothesis tests for two population means, population standard deviations unknown.
  • The Null and the Alternative

    • The alternative hypothesis and the null hypothesis are the two rival hypotheses that are compared by a statistical hypothesis test.
    • In statistical hypothesis testing, the alternative hypothesis and the null hypothesis are the two rival hypotheses which are compared by a statistical hypothesis test.
    • In the hypothesis testing approach of Jerzy Neyman and Egon Pearson, a null hypothesis is contrasted with an alternative hypothesis, and these are decided between on the basis of data, with certain error rates.
    • The concept of an alternative hypothesis forms a major component in modern statistical hypothesis testing; however, it was not part of Ronald Fisher's formulation of statistical hypothesis testing.
    • Modern statistical hypothesis testing accommodates this type of test, since the alternative hypothesis can be just the negation of the null hypothesis.
  • Does the Difference Prove the Point?

    • Rejecting the null hypothesis does not necessarily prove the alternative hypothesis.
    • The critical region of a hypothesis test is the set of all outcomes which cause the null hypothesis to be rejected in favor of the alternative hypothesis.
    • Alternatively, if the testing procedure forces us to reject the null hypothesis ($H_0$), we can accept the alternative hypothesis ($H_1$) and we conclude that the research hypothesis is supported by the data.
    • Rejection of the null hypothesis is a conclusion.
    • We might accept the alternative hypothesis (and the research hypothesis).
  • Student Learning Outcomes

    • Conduct and interpret hypothesis tests for a single population mean, population standard deviation known.
    • Conduct and interpret hypothesis tests for a single population mean, population standard deviation unknown.
  • Student Learning Outcomes

  • Misconceptions

    • State why the probability value is not the probability the null hypothesis is false
    • Explain why a non-significant outcome does not mean the null hypothesis is probably true
    • Misconception: The probability value is the probability that the null hypothesis is false.
    • It is the probability of the data given the null hypothesis.
    • It is not the probability that the null hypothesis is false.
  • Steps in Hypothesis Testing

    • Be able to state the null hypothesis for both one-tailed and two-tailed tests
    • The first step is to specify the null hypothesis.
    • A typical null hypothesis is μ1 - μ2 = 0 which is equivalent to μ1 = μ2.
    • If the probability value is lower then you reject the null hypothesis.
    • Failure to reject the null hypothesis does not constitute support for the null hypothesis.
  • Formulating the Hypothesis

    • A hypothesis is a potential answer to your research question; the research process helps you determine if your hypothesis is true.
    • This is an example of a causal hypothesis.
    • To test this hypothesis, he compared twenty different regional Italian governments.
    • To test this hypothesis, he compared twenty different regional Italian governments.
    • While there is no single way to develop a hypothesis, a useful hypothesis will use deductive reasoning to make predictions that can be experimentally assessed.
  • Type I and II Errors

    • Explain why the null hypothesis should not be accepted when the effect is not significant
    • Instead, α is the probability of a Type I error given that the null hypothesis is true.
    • If the null hypothesis is false, then it is impossible to make a Type I error.
    • Lack of significance does not support the conclusion that the null hypothesis is true.
    • A Type II error can only occur if the null hypothesis is false.
  • Elements of a Hypothesis Test

    • The null hypothesis was that the Lady had no such ability.
    • Fisher asserted that no alternative hypothesis was (ever) required.
    • Statistical hypothesis tests define a procedure that controls (fixes) the probability of incorrectly deciding that a default position (null hypothesis) is incorrect based on how likely it would be for a set of observations to occur if the null hypothesis were true.
    • The typical line of reasoning in a hypothesis test is as follows:
    • There is an initial research hypothesis of which the truth is unknown.
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