Inferential Statistics

Inferential Statistics

1. What is? & How to choose it?

   • Most of the times it is impossible to make a quantitative research of the whole population so in order to make it easier you have to select a small part of that population called sample
   • Everyone from the population has the same probability to be part of the sample
     • We must identify the following in the hypothesis Analysis unit Logic element Variables

2. Random Smapling

   • Sample random sampling a number is assigned to an element of the population, all the numbers are collected in a run and are selected consecutively until the number required

3. Stratified random samplig:

   • This divides the population into different subgroups according to their characteristics. The election of the sample items has to consider the elements of the stratum of the population in proportional number.

4. Formula = K=N/n

   • K is determined by dividing the number of elements of te population (N) over the number f elements requieres

5. Random Cluster Sampling

   • The population is divided into some groups called conglomerates where some elements from those groups are selected randomly

6. Hypothesis: statement of a parameter, can be true or false

7. Hypothesis testing: Determine if its true or false

8. Statical hypothesis: Distribution os the random variable.

9. Important things from the hypothesis: Analysis Unit, Logic element and Variables