Answer:
A characteristic , usually unknown of the population.
Characteristic of the population , such as its mean ,variance and standard deviations are population <u>Parameters .</u>
An observed characteristic of a sample are known as statistics
Estimate the use of a sample characteristic (statistic) to guess or approximate a population characteristic (parameter)
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Step-by-step explanation:
<u>Introduction</u>:-
The outcome of a statistical experiment may be recorded either as a numerical value or as a descriptive representation.
Example:-1
When a pair of dice are tossed and the sum of the numbers on the faces is the outcome of interest, we record a numerical value.
Example :-2
If the students of a certain school are given blood tests and the type of blood is of interest, then a descriptive representation.
<u>Population:-</u>
Population is consists of the total observation's with which we are concerned
The number of observations in the population is defined to be the size of the population
<u>Sample</u>:- A sample is a subset of population.
Samples are classified in two ways
Large sample : if the size of the sample n≥ 30 is called the large sample.
small sample: if the size of the sample n<30 is called the small sample.
Statistics uses different names and symbols to distinguish characteristics
of the population from those of a sample.
<u>Parameters </u>:-
A characteristic , usually unknown of the population.
Characteristic of the population , such as its mean ,variance and standard deviations are population <u>Parameters .</u>
In symbolically mean of the population parameter is denoted by<u> μ </u>
In symbolically variance of the population parameter is denoted by<u> σ²</u>
In symbolically standard deviation of the population parameter is denoted by <u> σ</u>
<u>Statistic :-</u>
An observed characteristic of a sample are known as statistics
Estimate the use of a sample characteristic (statistic) to guess or approximate a population characteristic (parameter)
In symbolically mean of the sample statistic is denoted by<u> x⁻</u>
In symbolically variance of the sample statistic is denoted by<u> S²</u>
In symbolically standard deviation of the statistic is denoted by <u> S</u>
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