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Statistics
Science of collecting, organizing, summarizing, and analyzing information to draw conclusion or answer questions.
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Stages of statistics
- 1 Collect.
- 2 Analize.
- 3 Draw a conclusion or answer.
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Types of statistics
- 1 Descriptive.
- 2 Inferential.
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Descriptive statistics:
It consist of organizing and summarizing data using table graph or simple calculation
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Inferential:
It uses methods that take a result from a sample extend of population and measure the reliability of the results.
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Population:
Is the entire group.
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Sample:
is a subgroup of from the population.
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Parameter:
Numerical value used to describe population.
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Statistic:
Numerical value used for a sample.
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Qualitative data:
Descriptive data/
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Discrete:
Numbers can be counted
Ex: 45 students
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Continuous:
Numbers can not be counted:
- Ex: - 355 ml coke can.
- - 10:00 am
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Levels of measurement:
- 1 Nominal.
- 2 Ordinal.
- 3 Interval.
- 4 Ratio.
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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)
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Ordinal:
- Names, labels, (similar as ordinal. Difference is: Names have no mathematical difference)
- EX: S (small), M (Medium), L (large).
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Interval:
Numbers. difference has a meaning
as addition: Zero is not a natural starting point.
EX: Temperature, elevation.
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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)
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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)
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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)
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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.
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Other effective methods of sampling:
- 1 convenience sample.
- 2 Systematic.
- 3 Stratified.
- 4 Cluster.
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Convenience sample:
Individuals are easily obtained.
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Systematic sample:
Select every kth individuals from a population
Ex: HW 1.1- Do 1-100 every odd
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Stratified sample:
Separate population into non-overlaping groups then obtain samples from each group.
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Cluster sample:
Obtain samples by selecting all samples from a selected group.
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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
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