An Introduction
Parameter and statistics terms are known to be very closely related to each other. Because both of them are very important for determining the sample size and the population in the mathematics field. There are so many people who face issues in understanding the exact difference between Parameter and Statistic.
It is considered to be very important to understand exactly how parameters and statistics are being measured. And also how to differentiate them from each other. Because these two are very confusing concepts and are interchangeably used in the day-to-day life of a person. This is why understanding the exact difference between Parameters and Statistics is difficult for people.
Definition of Parameter and Statistics
The parameter is known to be a fixed measure, which is used to describe the entire population that is based on all the elements of a population. The parameter is also considered to be a mass of all the units, which are taken into consideration that share common elements with each other.
On the other hand, statistics is known to be the characteristic of a sample of the whole population. Statistics is a measure of a characteristic that speaks something about the sample of a population that the researchers study. This is the major difference between Parameter and Statistic in the mathematics field.
Basically, a sample in statistics is a part of the whole population. This works with the goal of estimating a certain population’s parameter. Moreover, we can draw various types of different samples from a given population.
The results of these samples may vary from each other because this depends on the sample taken from the population. Therefore, deciding on a particular sample is also considered to be a very important thing. Because we always have to make an educated guess, in order to draw a sample from the population.
An Example
Let us understand, the difference between Parameter and Statistic with an example
If you ask all the employees of a particular company what kind of food they prefer to eat for lunch. Then half of them might give you a similar answer such as Indian food. But now let us say that we have to understand which particular type of lunch the people in the whole of the country want to or prefer to eat. Then it might not be possible to ask each and every single person in the country with a population of billions.
In this particular case, the major usage of understanding the difference between Parameter and Statistic takes place. So, here in this scenario, researchers make an educated guess and draw samples out of the whole population via mailer boxes wholesale.
The difference between Parameters and Statistics
Here are some of the major and top differences between population Parameters and the sample Statistics mentioned below in the article. It will help you in understanding both fields properly.
- The major difference between Parameter and Statistic is that the parameter is the fixed element and a measure, which is used to describe the whole population. Where on the other hand, the statistic is a kind of characteristic of a sample that has been drawn from the whole targetted population.
- A parameter is an unknown value of mathematics, which is fixed. And the statistics is a variable value that depends on the portion or the sample of the population.
- Another difference between Parameter and Statistic is that they both have different kinds of statistical notations.
- Both parameters and statistics are similar only but with different measures. The parameter represents the whole of the targeted population and the statistics represent the portion or the part of it, which is commonly known as a sample.
- Parameter is an explanatory measurement of the whole of the population. And statistics is a comprehensive measurement of the population.
- Parameter gives a fixed value as the result of an analysis. And on the other hand, statistics give the aggregate value as the analysis of the population.
- Letter “N” in the capital is used to denote the parameter of the population. And letter “n” in the small is used to denote the sample of the population.
Symbols and Notations
Here are some of the commonly used symbols and notations in the statistics field mentioned in the article below. These are used to denote some specific names in the field of statistics. Have a look at the same.
- Mean
- It is represented as “X” in sample statistic.
- It is represented as “μ (m u)” in the population parameter.
- Standard deviation
- It is represented as “S” in sample statistic.
- It is represented as “σ (sigma)” in the population parameter.
- Variance
- It is represented as “s2 or S square” in sample statistic.
- It is represented as “σ2 (sigma squared)” in the population parameter.
- Proportion
- It is represented as “P” in sample statistic.
- It is represented as “π (pi) or 22 by 7 or 3.14” in the population parameter.
- Correlation
- It is represented as “R” in sample statistics.
- It is represented as “ρ (rho)” in the population parameter.
- Regression coefficient
- It is represented as “b” in sample statistic.
- It is represented as “β (beta)” in the population parameter.
Statistics include analyzing, collecting, and also representing the experimental data of research. Basically, statistics is a very large and also vast field of study. People keep studying it and they never get bored. Because it includes problems, issues, concepts, and their interesting solutions. Therefore, the statistical field is growing with new and unique ideas.
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Statistics is a mathematical language, which is used to analyze the population and also draw a sample out of it by making an educated guess. Statistics and parameters are closely related to each other. Because of this they are very commonly used interchangeably as well.
The major difference between Parameter and Statistic is that the parameter field studies the whole population and the statistics field studies a sample of it.