Hypothesis Testing

• Hypothesis Testing

  • is a method applied in making decisions using experimental data.
• Hypothesis Testing

  • is basically testing an assumption that we make about a population.
• Hypothesis

  • is a proposed assumption, explanation, or assertion about a population parameter or about the distribution of a random variable.
• Types of Hypothesis

  1. Null Hypothesis
  2. Alternative Hypothesis
• Null Hypothesis

  • is an initial claim based on previous analyses, which the researcher tries to disprove, nullify, or reject.
• Null Hypothesis

  • It shows no significant difference between the two parameters.
  • denoted by H sub o (H⁰)
• Alternative Hypothesis

  • In contrary to null hypothesis, this hypothesis shows that observations are the result of a real effect.
  • denoted by H sub a (H^a)
• Level of Significance

  • denoted by alpha or a
  • refers to the degree of significance in which we accept or reject the null hypothesis
• Level of Significance

  • the probability of making the wrong decision when the null hypothesis is true.
  • one-tailed = 0.05; two-tailed = 0.025.
• Rejection Region

  • or the critical region
  • is the set of all values of the test statistic that causes us to reject the null hypothesis.
• One-tailed vs Two-tailed

  • less than or greater than = one-tailed
  • equal or not equal to = two-tailed