Parameters and statistics are two important aspects of data. Parameters are the specific values that define a set of data, while statistics are the measures or calculations that are taken from the data. In this blog post, we will explore the difference between these two concepts, and provide some examples to help illustrate their differences.

## What is Parameter?

- Parameter refers to a characteristic that can be measured or numbered. It is used in statistics and research design, and varies depending on the field of study. For example, in social sciences, parameters may include age, gender, race, and education level. In medicine, parameters may include blood pressure, weight, and height.
- In physics, parameters may include temperature, speed, and mass. By measuring and recording these variables, researchers can better understand the phenomenon they are studying.
- Parameters provide a way to quantify information and make it easier to compare and contrast data. Without parameters, it would be difficult to determine if two groups are different from each other or if a change is due to chance.

## What is Statistic?

- Statistic is a tool of measuring any given process. It is a mathematical science concerned with the collection, analysis, interpretation, presentation, and organization of data. In applying statistics to, for example, a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied.
- Populations can be diverse topics such as “all persons living in a country” or “every atom composing a crystal”. Statistic tool helps us to understand the data better and make sound decisions.
- It also allows us to study the data in more depth and come up with new hypotheses. Statistic tool is very important in any field where we need to collect and analyze data.

## Difference between Parameter and Statistic

Parameter and Statistic, both are the important tool of measuring any given process. Parameter is used to measure the stability of a process while statistic is used to estimate the performance of a process.

- Parameter is a numerical value that remains constant while statistic is a variable value that changes with each observation. Parameter can be calculated before conducting any experiment while statistic can be calculated only after conducting an experiment.
- Parameter is used to describe a population while statistic is used to describe a sample. Parameter is instantaneous value while statistic is average value over time.
- Parameter includes complete data set of a population while statistics includes only subset of data from the entire population. Parameter can be used for entire population inference while statistics can be used for individual inference.
- Examples of parameter are mean, median, mode etc.,while examples of statistics are range, standard deviation etc., In short, parameter is an overall or exact measure while statistic is an approximate or sampled measure. It should also be noted that all statistical measures are parameters but all parameters are not statistical measures.

For example- ‘population mean’ is a parameter but it’s also a statistical measure; on the other hand, ‘height of Mt Everest’ represents a parameter which cannot be considered as a statistical measure.

## Conclusion

Statisticians are responsible for analyzing data and turning it into information that is useful to businesses, governments, and other organizations. They work with parameters to understand the relationships between variables in a population. Parameters help statisticians make better predictions about future events. If you want to be a statistician, you need to have strong math skills and be able to think critically.