Stadistics

Dami Alvarez
Mind Map by Dami Alvarez, updated more than 1 year ago
Dami Alvarez
Created by Dami Alvarez over 5 years ago
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Class resume ;)
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Stadistics

Annotations:

  • The science in charge of collecting, describe, analize and interpret data.
1 Basic Concepts
1.1 Statistic
1.1.1 Measure calculated to describe a characteristic of the population
1.2 Parameter
1.2.1 Measure calculated to describe a characteristic of the poblation
1.3 Sample
1.3.1 Piece of the whole population to analize
1.4 Population
1.4.1 All the elements in consideration
1.5 Random Variables

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  • Caracteristics of the data or information recolected
1.5.1 Quantitative

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  • Numerical
1.5.1.1 Discrete
1.5.1.2 Continous

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  • To obtain it you need to measure it?????
1.5.2 Qualitative

Annotations:

  • Non numerical (caracteristics)
2 Measurement Scales
2.1 Nominal
2.1.1 Identity property

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  • X have magnitude Its values are truth X numerical value
2.2 Ordinal
2.2.1 Identity and magnitude properties

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  • Stablish an order X quantifies the distance between the categories
2.3 Interval
2.3.1 Identity, magnitude and equal intervals properties

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  • Allows negative values The 0 doesnt means the absence
2.4 Ratio
2.4.1 Identity, magnitude, equal intervals properties and an absolute cero

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  • Has all the previous characteristics Do operations
3 Sampling Methods
3.1 Probabilisticos
3.1.1 Simple

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  • Asignar un # Usar un medio para elegir la muestra
3.1.2 Estratificado

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  • niveles deacuerdo a la importancia
3.1.3 Multistage
3.1.4 Sistematico
3.2 No probabilisticos
3.2.1 Voluntario
3.2.2 Conveniente
4 Visual Displays of data
4.1 Distribucion de frequencias
4.1.1 F absoluta

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  • # de veces que ocurre algo
4.1.2 F relativa

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  • % de cada dato
4.1.3 Distrubucion
4.1.3.1 Cada dato pertenece (E) a una clase
4.1.3.2 Datos Agrupados

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  • Limite superior Limite inferior Ancho de clase Marca de clase
4.1.4 Graphs
4.1.4.1 Poligonal
4.1.4.2 Circular / Pay
4.1.4.3 Bars

Annotations:

  • barras
4.1.4.4 Steam and leaves
4.1.4.5 Histogram
5 Measures
5.1 Central tendency
5.1.1 Mean
5.1.1.1 Mean is equal to the addition of all values/ the number of data
5.1.2 Mode
5.1.2.1 Most repited informarion

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  • bi modal multimodal
5.1.3 Median

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  • X sensitive to extreme values changes Divides the groups of numbers in 2 parts
5.1.3.1 Steps to find it

Annotations:

  • 1. Organize data fron lower to higher 2. Divide # in to parts by the half 3. Obtain median Par: (promedio de 2 centros)/ Impar: (dato en el centro)
5.1.4 Weighted mean
5.1.4.1 Weigted Mean is equal to de adition of all values * frequency / The adition of all frquencies
5.2 Dispertion

Annotations:

  • How far are the data between 
5.2.1 Coefficient of variation
5.2.1.1 (s/X) x 100%

Annotations:

  • Division de medida por 100 Medicion relativa de la variacion
5.2.2 Range
5.2.2.1 R= Biggest value - Smallest value
5.2.3 Chevyshev´s Theorem
5.2.3.1 (1)-(1/(k*k))

Annotations:

  • % de info en cierto #
5.2.4 Standart deviation

Annotations:

  • 1. Calcular Media 2.Calcular la desviacion media 3. Elevar al cuadrado la desviacion 4. Sumar las desviaciones 5. Dividir (entre n o n-1) 6. Sacar raiz  cuadrada FIN ;)
5.2.4.1 sqrt((la suma de todos los datos - la media) alcuadrado/ (numero de datos [en caso de que sea muestral # de datos -1]))
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