When we study statistics, we see the difference between parameters and statistic. Botha terms are helpful in determining the size of the sample. A parameter is a tool to study the characteristics and nature of a sample or population. Statistics is used to study the values of samples or a part of the population.
For determining parameters, we study the values and measurements of the units of the population or groups. To determine the value of a sample or a small group of the population, we study statistics.
When we are studying advanced statistics, we should understand the difference between parameter and statistic. These terms are often misunderstood.
How do you define statistics?
After measuring the value of a sample or a population, a numerical value is determined, and the branch of study is known as statistics. The statistical value of a population is explained in detail. From a large population, a sample is chosen for the study. In statistics, a numeric value is obtained from a sample, and this value is assumed to be identical for all the samples of the population. In this value, the value of the entire population is determined. The main objective of statistics is to determine the statistical value of a parameter.
You can use several samples for studying, but each sample may reveal a different value.
What is a parameter?
A parameter is used to determine the characteristics of a sample. Many samples are studied, and the common characteristics of the samples are determined. The population also means the aggregate of the units that are studied. But they share a common characteristic. It consists of a numeric value that cannot be changed. Every member of the population should know the parameter. After the census is obtained, a true value is indicated.
Study the differences between statistics and parameters
In this parameter, the basic characteristics of the population are studied. In statistics, we obtain numbers to study the characteristics of the sample.
For example. To determine the average income of the United States is a parameter. But when we are choosing samples from a population and then obtaining the numeric value from a sample, it is a statistic. But we study the mean income of the people of the U.S. when we are applying parameters or statistics.
You can easily differentiate statistics from parameters. Both tools are used to determine a group and to describe each group. You should simply focus on the first few letters of the following:
Statistic = Sample
Parameter = population.
When we study an entire group of people, we are studying the population. When you study a portion of the group, you are determining its statistical value.
Parameters and statistics
Both terms are used to describe study groups.
In both cases, we use numeric values to study and summarize the characteristics of a sample or population. You can evaluate some types of attributes in a given sample or population. If you want to measure the length of a portion of an object and if the objects are approved or disapproved by the inspection agency,
If you are using a continuous scale to measure nature and want to determine value, then you can use different values for statistics and parameters. You can calculate different types of values, such as the median, mean, standard deviation, or even study correlation.
If the characteristic or attribute can be classified, then the parameter or statistic is in proportion.
Symbols of parameter and statistic
The parameters and statistics may reveal identical values, but the statisticians represent the values separately. So, to represent parameters, we use Latin letters or Greek letters. To represent statistics, we use lower-case Latin letters.
How do you identify a parameter or statistic?
When you are examining a report, listening to the news, or determining statistical value, can you differentiate if a summary value is a statistic or a parameter?
The population cannot be measured easily as it represents a large group, so you should choose to study statistics by choosing samples. If you want to find the exact parameter value, then you should study the entire population.
Researchers represent a population for studies and then specifically state about a narrow population. Population refers to a specific group, for example, a group of U.S. senators or a sports team of a particular county. So, as these groups are smaller, you can easily determine the value of a population.
The summary value is implied for the entire population or a part of the population. So, you should read the narration carefully and then consider these points:
If you are unable to measure the value of a very large population, then the summary value is statistical.
If you are providing a description of a sample and it represents the summary value, then it has a known statistical value.
If the size of the population is smaller, then the value can be determined easily, and the researchers can easily measure the group as well. So, the summary value represents the parameter.
Providing an illustration
If a researcher wants to determine the average weight of 22-year-old females in India, then they may choose a sample. So, they can obtain the value of 54 kg by choosing a sample or a group of 40, 50, etc. People.
According to the statistical value, the average weight is 54 kg, which is determined for a group of 40 people. The parameter is the mean weight of the females who are 22 or older in India.
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For e.g. A researcher wants to determine the total water consumption of male teenagers in India. So, they may choose 55 teenagers to examine their capacity and may determine the value as 1.5 liters.
The parameter is the average amount of water consumed by the teenagers, and the statistical value determined is 1.5 liters of water in a day by male teenagers. So, on average, teenagers can drink 1.5 liters of water, which is statistically significant. They are obtaining the value by choosing 55 samples.
So, statistics is the method of determining value from a sample and population from an entire group. If the size of the population is smaller, then parameters are determined.
