
Statistics
Science of collecting, organizing, summarizing, and analyzing information to draw conclusion or answer questions.

Stages of statistics
 1 Collect.
 2 Analize.
 3 Draw a conclusion or answer.

Types of statistics
 1 Descriptive.
 2 Inferential.

Descriptive statistics:
It consist of organizing and summarizing data using table graph or simple calculation

Inferential:
It uses methods that take a result from a sample extend of population and measure the reliability of the results.

Population:
Is the entire group.

Sample:
is a subgroup of from the population.

Parameter:
Numerical value used to describe population.

Statistic:
Numerical value used for a sample.


Qualitative data:
Descriptive data/

Discrete:
Numbers can be counted
Ex: 45 students

Continuous:
Numbers can not be counted:
 Ex:  355 ml coke can.
  10:00 am

Levels of measurement:
 1 Nominal.
 2 Ordinal.
 3 Interval.
 4 Ratio.

Nominal:
Measurements are names, labels, or categorical data.
 As addition: There is no ordering system.
 EX: Quiz, HW, Final. (order doesnt matter, once added, give same result)

Ordinal:
 Names, labels, (similar as ordinal. Difference is: Names have no mathematical difference)
 EX: S (small), M (Medium), L (large).

Interval:
Numbers. difference has a meaning
as addition: Zero is not a natural starting point.
EX: Temperature, elevation.

Observation study:
It measures the value of the response variable without attempting to influence the value of either the response or explanatory values. (Only observes, gathers data)

Experiment study:
A research assigns the individuals in a study to a certain group, Intentionally changes the value of the explanatory value, and then records the value of response. (Do a lab, then records the change)

Random sample:
(chance varies)
The process of using chance to select an individual from a population to ve included in a sample. (pick one by one)

Simple random sample:
(Always same chance, group)
A sample of size "n" from a population size "N" is obtained through simple random sample if every possible sample size "n" has an equal chance of being selected.

Other effective methods of sampling:
 1 convenience sample.
 2 Systematic.
 3 Stratified.
 4 Cluster.

Convenience sample:
Individuals are easily obtained.

Systematic sample:
Select every kth individuals from a population
Ex: HW 1.1 Do 1100 every odd

Stratified sample:
Separate population into nonoverlaping groups then obtain samples from each group.

Cluster sample:
Obtain samples by selecting all samples from a selected group.

Stratified VS Cluster
 1. Divide population into some groups
 2. Pick all groups l 2. pick some groups
 3. Pick some samples l 3. pick all samples

