A Parameter and Statistic respectively are characteristic of which of the following ${\text{?}}$
$\left( {\text{A}} \right)$Population and sample
$\left( {\text{B}} \right)$Sample and population
$\left( {\text{C}} \right)$Sample and sample
$\left( {\text{D}} \right)$Population and population
Answer
615.3k+ views
Hint: Here we have to know what are parameters and statistics and its characteristics.
Then we can easily choose the correct answer.
We will know the definitions of the given terms and then select the most appropriate answer.
Complete step-by-step solution:
Parameter and Statistic are closely related terms that are important for the determination of a sample size.
Sample size is a number of individual samples measured or observations used in a survey or experiment.
For example,
If you test ${\text{100}}$ samples of blood then your sample size is ${\text{100}}$.
Sample size is nothing but the counting of samples.
In statistics, sample size is generally represented by the variable
Now we have to know the definition of parameter and statistic
Parameter is a measure of a characteristic of an entire population based on all the elements within that population.
For examples,
All students in a classroom, all people living in one city.
A statistic is a characteristic of a sample.
For example,
If you ask all employees in a factory what kind of lunch they prefer and half of them say biriyani.
You get a parameter here.
${{50\% }}$ of the employees like biryani for lunch.
On the other hand it is impossible to count how many women in the whole world like biryani for lunch since you can’t ask all of them about their choice.
In that case, you would probably survey just a representative sample of them.
From this example, we clearly observed that parameter is a count of an entire population while statistics is a count of a part of population that is sample.
Thus parameters and statistics are characteristic of population and sample respectively.
Hence the correct option is $\left( {\text{A}} \right)$.
Note: Confidence intervals are a range of values likely to contain the population parameter.
The characteristic of the population of interest is known as parameter and the corresponding parameter estimate or sample statistic.
Parameters and both are similar, yet different measures.
Then we can easily choose the correct answer.
We will know the definitions of the given terms and then select the most appropriate answer.
Complete step-by-step solution:
Parameter and Statistic are closely related terms that are important for the determination of a sample size.
Sample size is a number of individual samples measured or observations used in a survey or experiment.
For example,
If you test ${\text{100}}$ samples of blood then your sample size is ${\text{100}}$.
Sample size is nothing but the counting of samples.
In statistics, sample size is generally represented by the variable
Now we have to know the definition of parameter and statistic
Parameter is a measure of a characteristic of an entire population based on all the elements within that population.
For examples,
All students in a classroom, all people living in one city.
A statistic is a characteristic of a sample.
For example,
If you ask all employees in a factory what kind of lunch they prefer and half of them say biriyani.
You get a parameter here.
${{50\% }}$ of the employees like biryani for lunch.
On the other hand it is impossible to count how many women in the whole world like biryani for lunch since you can’t ask all of them about their choice.
In that case, you would probably survey just a representative sample of them.
From this example, we clearly observed that parameter is a count of an entire population while statistics is a count of a part of population that is sample.
Thus parameters and statistics are characteristic of population and sample respectively.
Hence the correct option is $\left( {\text{A}} \right)$.
Note: Confidence intervals are a range of values likely to contain the population parameter.
The characteristic of the population of interest is known as parameter and the corresponding parameter estimate or sample statistic.
Parameters and both are similar, yet different measures.
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