Module 3

Module 3

1. 3.1- Population and sampling

   • Descriptive statistic: to describe the basic features of the data in a study. Inferential statistic: to reach conclusions that extend beyond the immediate data alone.
   • Types of sampling
     • Probability
       • Simple random sampling
         • A number is assigned to each element of the population.
       • Systematic random sampling
         • A constant "K" is determined by dividing the number of elements of the population (N) over the number of elements required (n). K = N/n
       • Stratified random sampling
         • Divides the population into different subgroups according to their characteristics.
       • Cluster random sampling
         • The population is grouped by proximity to existing subgroups, which will be called conglomerates.
     • Nonprobability
       • Quota sampling
         • Made up of people who are easy to reach.
       • Convinience sampling
         • In the assembled sample has the same proportions of individuals as the entire population with respect to know characteristics, traits, etc.

2. 3.2- Hypothesis tests

   • Null hypothesis
     • Is a type of hypothesis used in statistics that proposes that no statistical significance exists in a set of given observations.
     • Elements of null hypothesis
       • Unit of analysis, logical element and variable.

3. 3.3- One-tailed and two-tailed tests

   • Significance level
     • Is the criterion used for rejecting the null hypothesis, it s commonly used in hypothesis testing.
   • Acceptance region
     • It's the interval within the sampling distribution of the tet statistic that is consistent with the H0.
   • Rejection region
     • Is the set of values for the test statistic that lead to rejection of H0.
   • Two-tailed test
     • Statistical test which the critical area of distribution is two-sided and tests which sample is greater.
   • One-tailed test
     • Statistical test with one-sided distribution, greater or less than a certain value but not both.
   • Steps for Hypothesis testing
     • 1.- State null hypothesis and alternative
     • 2.- Determine significance level to be used
     • 3.- Select the test statistic
     • 4.- Determine critical value for test statistic
     • 5.- Calculate the value of the test
     • 6.- Conclude

4. 3.4- Z-test

   • Formula

5. 3.5- t-test

   • Formula

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