87 lines
2.7 KiB
Markdown
87 lines
2.7 KiB
Markdown
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---
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title: Statistics
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updated: 2022-04-02 15:10:58Z
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created: 2021-05-04 14:58:11Z
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---
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# Statistics
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## Data Types
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- **Categorical**
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- **Nominal Variables**
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Intrinsic order of the labels:
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Country of birth (Argentina, England, Germany)
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Postcode
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Vehicle make (Citroen, Peugeot, ...)
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- **Ordinal Variables**
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Can be meaningfully ordered are called ordinal:
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Student's grade in an exam (A, B, C or Fail)
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Days of the week (Monday = 1 and Sunday = 7)
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- **Numerical**
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- **Discrete**
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how many cards in a game?
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integers
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- **Continuous**
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height of a room
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floating point numbers
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What are proportions?
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Is an aggregation of nominal data to provide a numerical figure. eq a percentage of nominal variables.
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## Mixed Variables
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- Observations show either numbers or categories among their values
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- Number of credit accounts (1-100, U, T, M) U = unknown, T = unverified, M = unmatched)
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- Observations show both numbers and categories in their values
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- Cabin (Titanic) (A15, B18, ...)
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## Distributions
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Selecting something on de x-axis in the middle has an higher probability then rarer on to the edges.
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Bell curve of Normal Distribution
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Bi-mode distribution
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Skewed distribution
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Sample Distribution
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$$
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\overline{X} == variance
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$$
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## Sampling ande Estimation
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eg
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some best number of successes divided by the sampling, gives an estimate 10 / 3 = 3,3333
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$$
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\Theta == estimate with some variance around to make a good guess out of the sample
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$$
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So given an sample we have am 95% confidence out sample estimate is in this interval.
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If less sure of this theta, the larger the confidence interval. eq because the n is much smaller.
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## Hypothesis Testing
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In Hypothesis Testing never:
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- prove anything
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- never accept the null hypothesis
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## P-values
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consider a null Hypothesis:
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Hypothesis Test asses ig our sample is extreme enough to reject the null.
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The p-value then measure how extreme our sample is.
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## P-hacking
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