What is statistics subject | What is statistics in research.

What is statistics subject

This article explain " What is statistics subject " and what is statistics in research. 

What Is Statistics Subject

Statistics is a scientific field that deals with the collection and analysis of such data as numerical figures, trends, statistics, data, numerical expressions, etc. The fundamental goal of this discipline is to interpret data and draw conclusions from it so that it can be used in further studies. There are many different ways of doing statistical analyses, but most often they come down to one of these two categories: descriptive and inferential, which means using either the mean or median (the middle value) or mode as the ‘best’ value to compare; or comparative and prescriptive, where you want to make predictions based on known values in order to draw them conclusions.

Descriptive – studying the underlying properties or characteristics of something.

Interpretive – drawing conclusions about other situations based on patterns in the data.

Inferential – drawing generalizations about new populations based on previous results

As far as how much does statistics involve in each branch of the study, these kinds of studies are usually concerned with making comparisons and drawing important inferences about groups and populations. For example, with surveys, we can estimate the distribution of people according to age and gender in order to understand people’s preferences and tendencies. By studying historical data, we usually find out who had the highest percentage of voting at the midterm elections, who was very popular among their friends and family members, who became an athlete in college, etc. But what about measuring things like how many times someone came to university? How many friends he has? Or, how many children he has? To answer all of those questions we need to have statisticians with us and make comparisons. And then we can get better information about the population – this is also called statistics in research. From all these observations we can make statements, predictions, conclusions, etc. As for this example, according to statistics in research, if I want to measure how many hours someone spends in class per week, I would have to take into account a lot of factors. First, who has a student, I would talk to the person, get his number of classes in a year, and tell me the approximate number of hours per student. This way, I can understand how much time my friend or colleague has spent on studying for exams per week and what methods they use. Then, since this is my sample, I can make a comparison, and tell me the result – according to our rules and requirements, this person will spend between 15-20 hours a week studying, and they will receive around 50% marks in the exam. A student can also spend extra time studying without the knowledge of our professor, so by taking those extra ten minutes I can actually help him by getting good grades, which is a great method that is used in many colleges around the world and works pretty well. Thus, I can obtain some information about my friend without telling about myself, and we can analyze it together.

So far we have learned about how much time a person spends on studying, how many people studied a certain subject, etc. And how do researchers work on the basis of these findings? We can formulate a hypothesis based on this information and start a survey. However, it may not be enough. It is necessary to collect more information. Since statistics in research consists in comparing groups or samples (which are in fact collections of individuals), it is important to identify different groups of people, collect detailed information about them, and compare. This step is called sampling.

If we have gathered enough information, we can conduct the actual test. Suppose we talk to 100 students about their preference of musical instruments. Now, we gather several kinds of musical instruments, for example, drums, bass, guitars, piano, violins, clarinet, etc. And we are quite sure that the majority of young people prefer drumsticks for playing. Let’s say we give them lots of books with basic information about the instrument, and then we ask them to play various types of percussion. So, at first, we see only the overall feeling about guitars and violins. We don't even know why people like pianos better (it's just that everyone prefers them). So, we ask them to count the number of times they played either guitar or violin each day, so we get information about how many times a person likes each kind of instrument and what kind of music they like. Let's assume we got information from this test: 10 of the people answered positively about guitars and violins, we could draw conclusions about how people prefer different types of musicians and which ones they prefer in terms of instrumentation.

Now we have another question: do we know a particular kind of instrument or musical instrument that everyone likes and they would prefer? Maybe we think that we know them and everyone loves trumpet and people tend to show preferences for it. Maybe they like soprano or maybe they prefer a full soprano – so it turns out that their preference is related to vocal range, so let's ask them again: what kind of trumpets they use – do they use flutes, trombones, high brass? These are examples of possible forms of instruments, so let's try it. Obviously, we don't know anything about them, so it is hard to say anything about them. So, we don't use any of the information about them in our own study – it's just an overview without any real data or information. What should we do now?

We can draw conclusions based on this information about the respondents, about their preferences, etc. So, instead of collecting random samples from the people, we can come up with a list of musical instruments they like and ask them about their preferences. That's when we can draw a conclusion about the kind of music they prefer to listen.