STATISTICS

STATISTICS

1. DESCRIPTIVE STATISTICS

   • Presenting, organizing and summarizing data.
     • HYPOTHESIS TESTING
       • A procedure based on evidence of the sample and theory of probabilities of reasonable affirmation.
         • HYPOTHESIS
           • Conjecture about a parameter of one or more populations and which is subject to verification.
         • NULL HYPOTHESIS
           • Any hypothesis that wants to be proved. Its notation is Ho
         • ALTERNATIVE HYPOTHESIS
           • It's the hypothesis that is accepted when the null hypothesis is rejected. Its notation is H1
         • SIGNIFICANCE LEVEL
           • It is the probability of rejecting the null hypothesis when it's true. It's denoted as alpha or a.
         • ERROR TYPES
           • Is this decision trustworthy based on the data of a sample, when we base on simple data it's possible to have two types of errors.
             • ERROR TYPE I
               • It is made when a hypothesis that is correct is rejected.
             • ERROR TYPE II
               • It is made when a hypothesis that is incorrect is accepted.
         • TEST STATISTIC
           • This is the value to make contrast against critical value in an appropiate probability distribution.

2. INFERENTIAL STATISTICS

   • Drawing conclusions about a population based on data observed in a sample.