Does the subject statistics fascinate you? Do you aspire to become a statistician?
Then this article is a must-read for you. Go through this article nicely to understand all the important details that you should learn about the subject to become a successful Statistician.
Before going into details about all the different topics related to statistics, it is important to understand what statistics is all about. Statistics deals with data, its collection, correct arrangement, evaluation, interpretation, and proper display in front of the world.
The application of statistics is widespread in each and every field. You can find statistics in scientific researches, industries, financial sector, etc. Statistics is hugely implied in the various surveys and other jobs of the government.
For example, the rate of population growth in a country can be displayed by applying statistics to it. The growth of a country in any sector also demands the application of statistics. When there cannot be the exact data collected about any particular experiment, then various formulas of statistics are implied to display the output of the experiment.
Who is a statistician?
A person who deals with the various aspects of statistics can be called a statistician. He can apply any form of statistics appropriately to carry out the desired job. a statistician deals with both the theories related to statistics and its rightful application.
The job of a statistician is in high demand in every sector of our life. You can find statisticians working in various government fields and also in private companies. There are many other sub-categories in which statisticians work. These categories have different titles like actuary, applied mathematician, data analyst, data scientist, financial analyst, economist, sociologist, epidemiologist, etc.
Various topics related to statistics
Statistics is a vast subject that has a wide application in various fields. Almost all the sectors need an able statistician to handle various types of complex tasks in the organization. Statistics has many sub-branches which together shapes the subject. These sub-branches are some of the very important topics that you should know in details to work in any field as a successful statistician.
The sub-branches or important topics related to statistics are:
Theory of Probability
Probability is one of the most important aspects of statistics. Statisticians have to deal with a huge number of probability calculations in their entire career. Different people have a different perception of this topic. But if a clear idea can be drawn about this sub-branch of statistics then it can come to great help for the statisticians in carrying out their regular job.
The term probability can be defined as the measurement of the chance of an event to take place. Probability of any event can be numbered anything between zero and one. Here zero determines that the chance of occurrence is extremely void or it is an impossible event. And one determines that the event is sure to occur. Any number in between zero and one displays the chance between possibility and impossibility of the occurrence of a particular event.
If the number displaying the probability of an event in higher in value, then it clearly depicts that the chance of occurrence of that event is close to possible. If the digit is low in value then the chances of the possibility of an event can be considered very little.
For example when tosses happen in any sports match then it clearly represents probability. There are fair chances of winning the toss for both of the teams participating in a particular match. A particular coin can bring only two results, that is, heads and tails.
Therefore the chance of any team winning is 50 percent. There can be only two possible outcomes of the toss. It can be a heads or a tails. Here the probability of the event can be written as 1/2.
Probability has an extensive application in various fields related to mathematics, statistics, finance, physics, computer science, gaming, philosophy, gambling, etc. Probability can be implied in solving various complex problems in our day to day life.
Application of mathematics in statistics can be termed as mathematical statistics. This branch of statistics is extremely opposite to the method employed in collecting statistical data for any evaluation. It deals with the interaction between pure mathematics and the real-life events occurring around us.
There are some mathematical techniques that are employed by the statisticians in solving various statistical problems related to this branch. Different kinds of mathematical techniques used are linear algebra, mathematical analysis, differential equation, theory of measurement, and stochastic analysis.
Mathematical statics forms an integral part of the whole subject of statistics. Various procedures related to statistics are developed and redesigned using different formulae of mathematics. Statisticians are also able to raise various mathematical queries related to the research findings of statistics. Statistical mathematics highly depends on probability distribution and the theory of decision making.
As probability distributions have a lot of application in statistical mathematics, therefore it is discussed briefly in this article. In every experiment carried out, a probability is assigned to the subsets of the results that can be measured. This probability that is assigned to the subset is termed as probability distributions. Probability distributions can be related to a single variable or multiple variables.
Sampling is a method in which statistical designs are used that ensures the optimization of the data collected applying the least amount of effort. In this method of statistics, each and every data collected is arranged effectively so that the maximum output can be derived from it. This helps in minimizing the effort that needs to be applied by a statistician.
If anyone wants to study the findings of particular research beyond the access of a laboratory then he needs to apply various techniques of statistics termed as sampling. For example, if you want to find out the number of pets residing in a cultivated area and how they are harming crops then you will have to visit that area of cultivation in person. This is where the theory of sampling can come to rescue for the researchers.
If various techniques of sampling are employed then researchers will find it much easier to carry out their research work. There are various questions that need to be addressed before going out for a particular survey. These questions are where to carry out the survey? How many measurements should be drawn for finding out exact values of a survey? What can be a favorable condition for carrying out a particular survey?
These questions should be addressed nicely before going ahead with a survey to ensure its effective results and high success rate. This will also help in saving time and cost related to that survey. Therefore, you can see that sampling has a huge impact on various research works. It brings out the expected result by minimizing the amount of effort that needs to be applied.
Design of experiments is one of the most underrated sub-branches of Statistics but has the greatest implementation in almost every field. Statisticians widely use experimental designs to evaluate the authenticity of an experiment. Scientists carry out research experiments and they seek help from a statistician to validate all the findings of that particular experiment.
Design of experiment determines the designing process of an experiment that helps in finding out the discrepancies in the results of that experiment. It explains all the major causes that are leading to the discrepancy in data of that task. Experimental design should comply with the basic requirements of reliability, authenticity, and interchangeability.
A statistician implements statistics designs and finds out all the flaws in the result of an experiment. Therefore for a research scientist, a statistician can be the last resort who can help him come out of each and every complex fault in his experiment. A statistician can help him out by preparing designs of that experiment and pointing out the places which need rectification.
If statisticians can design perfectly for an experiment then it can save a huge amount of time and money. This is because the amount of time wasted in finding out each and every fault will be eliminated and also the cost incurred by it.
Various types of regression models are designed for relating variable data with each other in a particular direction. It shows that if a similar kind of data is related to each other then the proportionality increases with the increase in the value of data. These types of models are called regression models and are used by each and every statistician. They use it as a powerful tool in depicting several kinds of experiments.
Several types of methods are used for evaluating these regression models, but the most common method employed by many statisticians is the least-squares method. But there can be such instances where the data cannot be fitted in a linear fashion. Instead a curve is seen to take place after relating the variables in a model. These curves are quite rigid and can be evaluated with the help of quadratic relationships.
There can be also such situations where the variables cannot be related to each other as they are not of similar kind and this gives rise to various complications in the regression model. But there is nothing to worry when these situations arise as modern regression methods have been designed to solve them quite easily.
Classification is a general method that is employed by everyone in their daily lives. But do you know that this is a sub-branch of statistics? Yes, the proper classification of data as per requirement needs the implementation of various theories of statistics.
Classification can be defined as the grouping of various data according to their features. Various kinds of data are divided into their respective groups that help in their evaluation. For example, a school has various types of students. Some are very good in studies, some are mediocre, some are below average, and the rest do not qualify in any exam. Therefore if the school authority can classify all of its students into various groups depending on their grades then it will be easier for them to evaluate their annual performance.
This sub-branch of statistics finds its place in the field of health. Most of the medicine manufacturers use this technique to determine the impact a drug is going to have on the lives of the patients suffering from a particular disease. They take help of statisticians who can analyze each and every data gathered and find out the exact chance of the success of a particular drug.
For example, if a medicine company is working on a new drug that they believe can cure cancer then they will take help of some patients suffering from it. That company will provide them the drug they are working on and then will analyze the impact it has on them. If the drug is successful in giving out the expected output then they will develop it in full measures but if the result comes out negative then they will bring out the necessary changes in it.
A statistician uses all those data collected by that company in evaluating the success rate of the drug given to the patients. It is his analyses that will help the company in deciding the exact impact of the drug.
There are also some other sub-branches of statistics that need to be learned by a student of statistics to become successful in his career. Statistics needs thorough understanding and rigorous practice and that can help any statistician advance in his career.
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