 # Statistics vs Econometrics: What are the Differences?

In this blog, we are going to share with you the comparison between Statistics vs Econometrics. Both Statistics and Econometrics topics are very important for students. Before going deeper, Let’s start with a short introduction to each of these terms.

## What is Statistics?

From the Latin word “status,” statistics is derived which refers to a collection of statistics used to represent data concerning a human interest. Statistics is an applied mathematics branch that deals with the gathering, analysing, describing, and inferring conclusions from quantitative data. The information gathered is then used to make decisions. Differential and integral calculus, linear algebra, and probability theory are all used substantially in statistics’ mathematical theories.

Statistical methods are used by financial analysts to evaluate, examine, and summarise enormous amounts of data into a mathematical form that can be used. Statistics is used in a variety of fields, including business, social sciences, industry, psychology, and others.

## What Is Econometrics?

Econometrics is a branch of economics that studies economic data using statistical and mathematical approaches. Those who work in the field of econometrics are known as econometricians.

Econometricians use statistical methods or tools including regression analysis, statistical inference, frequency distributions, probability, and more to examine economic theories and hypotheses. Econometricians compare the results with the real data and observations after putting the economic theories to the test, for forecasting future economic trends.

## Types of Statistics

The study of statistics can be divided into two types. Descriptive and inferential statistics are among them.

#### 1. Descriptive statistics

Descriptive statistics define a population’s basic characteristics and how the data is organised. This allows analysts to recognise data features and make sense of it.

There are two basic forms or types of descriptive statistics used by scientists:

• Measures of central tendency

#### 2. Inferential statistics

In inferential statistics, to infer trends regarding a big population, complex mathematical computations are used. It is tough to analyse each member of a huge population one by one while analysing a large population.

Inferential statistics are used by scientists, between variables in a sample population, to discover the relationships and then to make predictions about how the variables relate to the whole population.

The following are the two primary classifications of inferential statistics:

• Confidence interval
• Hypothesis testing

## Types of Econometrics

Theoretical and applied econometrics are the two main types of econometrics.

#### 1. Theoretical econometrics

To estimate any unknowns, this type of econometrics analysis looks at the existing statistical techniques or tests qualities or properties. Theoretical econometricians may come up with new methodologies of statistics to account for economic data anomalies. To demonstrate the viability of new processes, this field of econometrics focuses on numerical data, theoretical statistics, and mathematics.

#### 2. Applied econometrics

To convert qualitative statements into quantitative ones, the second type of econometrics involves the techniques. It is frequently in response to the work of applied econometricians who have discovered unexplained variations in data sets that theoretical econometricians design new statistical approaches. These new tools can then be used by applied econometricians to test their hypotheses.

## Functions of Statistics

These are the some Important functions of statistics that are shown below:

• Statistics simplifies complexity
• Statistics facilities comparison
• To help in formulation of policies
• Forecasting is aided by statistics.
• Statistics is a method of presenting facts in a definite format.
• Statistics aids in the formulating and testing of hypotheses.

## Functions of Econometrics

Econometrics have three functions basically which are interrelated function:

• In the Econometrics first function, it puts economic theories or hypotheses proposed by eminent econometricians to the test.
• In the Econometrics second function, for economic connection variables it produces numerical estimates. To make decisions, these are the important one’s.
• In the Econometrics third function, it is for prediction of economic events.

## Limitations of Statistics

Statistics have some limitations. The following are the main limitations of statistics are:

• With individuals statistics does not deal
• Statistical laws are not exact
• Statistics is liable to be misused
• Statistics does not study qualitative phenomena

## Limitations of Econometrics

Econometrics have some limitations. The following are the main limitations of econometrics are:

• Sometimes econometrics has been criticized for relying too heavily on the interpretation of raw data without connecting it to established economic theory or seeking causal mechanisms.
• It’s critical that the data’s conclusions can be satisfactorily explained by a theory, even if that involves creating your own underlying processes theory.
• Also regression analysis does not prove causation, and an association between two data sets could be spurious.

## Conclusion

So, this was all about our topic, which was Statistics vs Econometrics. We hope that you have liked what you have read about Statistics vs Econometrics. Moreover, if you need any Advance Econometrics Assignment Help, you can contact our experts and get help at a very reasonable price.

## FAQs

### Which is better statistics or economics?

Statistics is the better one for you if numbers fascinate you. Both degrees will need you to work with data, but the statistics one will be more rigorous. Economics is a better choice if you intend to pursue a career in academics or research.

### What is the function of econometrics?

The functions of econometrics that are the important ones are typically taken to be hypothesis testing and forecasting.

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