Statistik I at Universität Konstanz | Flashcards & Summaries

Lernmaterialien für Statistik I an der Universität Konstanz

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Inferential statistics

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methods using probability theory to infer from a sample of data to the population of interest

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Statistical Units

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"Entities"

Statistical units or entities are objects or individuals whose

characteristics are of interest


Examples: frims, households, employees,students

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Population

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The collection of all relevant units is called the population and is described by factual, geographic or time criteria.

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forms of populations

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  • finite populations: students enrolled in "Economics" at UKon
  • hypothetical population: potential customers in marketing firm
  • infinite population: number of rolls in rolling dice experiment
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Census

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If data on all units of the population is available (rarely feasible) it's called a census.

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Sample

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"Probe"

A subset may be obtained by drawing a sample from the population. I.e. collecting data from a fraction of the population. Samples should ideally reflect the entire population.

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Sample drawing techniques

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• a simple random sample: each member of the population has the

same probability to end up in the sample


• a stratified random sample: the population is divided into

homogeneous subgroups and simple random samples are drawn from

each group

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qualitative variables

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These take on values that are just labels and divide data into different categories.

Oftentimes categories are coded with numerical values (married = 1, divorced = 2 etc)

Examples: martial status, eye color, study program

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quantitative variables

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These are measured on a numerical scale. They are further divided into discrete and continuous variables.

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discrete variables

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countable number of distinct values 


Example: number of employees, "how happy are you from 1-10?"

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continuous variables

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  • Inifinite numbers in a given interval.
  • may be grouped into classes (discrete)


Example: profit of manufacturing firm

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Descriptive and explorative statistics

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• graphical and numerical methods to describe and summarize data

• methods to detect certain patterns and relations between variables

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Q:

Inferential statistics

A:

methods using probability theory to infer from a sample of data to the population of interest

Q:

Statistical Units

A:

"Entities"

Statistical units or entities are objects or individuals whose

characteristics are of interest


Examples: frims, households, employees,students

Q:

Population

A:

The collection of all relevant units is called the population and is described by factual, geographic or time criteria.

Q:

forms of populations

A:
  • finite populations: students enrolled in "Economics" at UKon
  • hypothetical population: potential customers in marketing firm
  • infinite population: number of rolls in rolling dice experiment
Q:

Census

A:

If data on all units of the population is available (rarely feasible) it's called a census.

Mehr Karteikarten anzeigen
Q:

Sample

A:

"Probe"

A subset may be obtained by drawing a sample from the population. I.e. collecting data from a fraction of the population. Samples should ideally reflect the entire population.

Q:

Sample drawing techniques

A:

• a simple random sample: each member of the population has the

same probability to end up in the sample


• a stratified random sample: the population is divided into

homogeneous subgroups and simple random samples are drawn from

each group

Q:

qualitative variables

A:

These take on values that are just labels and divide data into different categories.

Oftentimes categories are coded with numerical values (married = 1, divorced = 2 etc)

Examples: martial status, eye color, study program

Q:

quantitative variables

A:

These are measured on a numerical scale. They are further divided into discrete and continuous variables.

Q:

discrete variables

A:

countable number of distinct values 


Example: number of employees, "how happy are you from 1-10?"

Q:

continuous variables

A:
  • Inifinite numbers in a given interval.
  • may be grouped into classes (discrete)


Example: profit of manufacturing firm

Q:

Descriptive and explorative statistics

A:

• graphical and numerical methods to describe and summarize data

• methods to detect certain patterns and relations between variables

Statistik I

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