Lecture 03

Hinzugefügt: 2026-05-06

[00:00:22]Good day dear learners. I welcome you to this course of advanced statistics in education. So today's topic is importance and use of statistics in research. So I'll be the resource person for this particular topic and um I am Anju Mahhmed from department of education. So let's begin the overview.

[00:00:43]First I'll be giving you the overview what we're going to see in this next 30 minutes. So I'll be first explaining the core meaning definition and types of statistics. Then I'll be switching to understanding what are the different function of statistics and ultimately towards the end you will be able to comprehend how statistic is useful in other discipline and especially with special reference to research. So let's get started.

[00:01:11]So to begin with um when I'm talking about statistics so if you have to look at the ethmological origin where did this word originate from? So it originated from a Latin word status statista in Italian word also and even in German word we call as stat uh statistic with a different spelling but you pronounce it almost the same uh which means a political state. So you see way back even in 18th century um the first German scholar at that time the echen wall he described the whole systematic collection and analysis of data about the state particularly you know the concerning the population economy what was the military strength and resources and so on. So from there on we started using this word statistics. So originally statistic was um not meant for the mathematical data analysis but more of a descriptive type of the political state. Now statistic is also used as a singular word and it also has a plural sense also though the spelling is the same but there is a difference in it. If you're using statistic as a plural form uh so you have to understand that the data it is used in the data sense that means it is basically referring to the numerical data. So for example if a teacher is collecting data from uh 50 students according their marks like you know some might some might be having 25 some might be 60 70 80 or 99 whatever is it this these mark scores when we talking about numerical data we're talking about statistic but in a singular function statistic has a different view viewpoint. So basically when we're talking in into the singular term we mean in the form of a discipline.

[00:02:55]So basically it's a branch of study which is deal which is dealing with what collection of data organization of data how you're presenting the analysis and the interpretation of the numerical data. So this is how the the essence of statistic can be reflected both in the singular and the plural sense. Okay. Now let's move forward.

[00:03:20]Now in the singular sense when we're talking that stat statistic is highly interdisciplinary field. So it is not only limited to mathematical uh field alone. Basically if you see nowadays it is a toolkit for every scientific field.

[00:03:37]That means if you want the answers you want to analyze data you want to take some certain decisions. The scientists in all these particular field they face problems like how can such large amount of data can we make can we make it meaningful enough to understand and this is where they they resolve and they resort to using statistical methods.

[00:04:00]Moreover, now we have to understand that the statistic uh the field of statistics also has two fundamental ideas. The idea of uncertaintity and the idea of variation. Now what does uncertaintity mean? So uncert uncertaintity means uh it refers to the fact that we cannot always predict the outcomes.

[00:04:24]Just let me take out the uh pen. Yes, we cannot always predict outcomes and that too with absolute certaintity we cannot do so right because the future is sometimes so unknown to us like how are we going to manage it then? Um plus we also know that the certaintity can also be divided into two for uh two types that is future uncertaintity that means not yet determined that means if you want to know um if it's going to rain tomorrow or not right it's a future that is um uncertain to us. So we find that um that type of uncertaintity is future uncertaintity and something is knowledge uncertaintity that means it is present there but it is no longer uh this is unknown to us at this time. For example, you gave an exam but the result is not out and it's a knowledge uncertainty.

[00:05:20]You still want to know what you scored in that particular test. Right? But the evaluator has already furnished the mark mark list and has published the result has not published the result at the public platform but they have made the list. So you see this is knowledge uncertaintity.

[00:05:35]Then moving forward variation. Now under variation we know that it refers that the outcomes are not always the same.

[00:05:44]They differ from one individual to individuals. And this is where we find that we have to understand the variation in order to study the patterns and make certain predictions as well. So data can never be constant. It always varies.

[00:06:02]Now coming to the definitions of statistics, we have different definitions. I have I tried to encompass um at least five definitions here. Now if you look closely I'll also be bringing about the common features of all these and trying to summarize these definition. So we have and of course all these definitions are given by famous statisticians. So we have lovit who talks about statistic as the branch of st um science which basically deals with collection classification and tabulations and so on. Then we have uh croxton and cton which also talks about the same thing. They're also talking about collection, analysis, interpretation of numerical data. Then we have kings which talks about science of statistic as the method of judging um and collecting natural or social science phenomena from the result obtained from the analysis. Then we have bodings which though he has given a very crisp definition that statistic is the science of estimates and probability.

[00:07:02]Uh and then RA Fischer he's the one who also known as the uh one known as the father of modern statistics. You should know um Araf Fisher. And of course in in India we have PC that is Prasanta um Chantra uh Mahana Mahala Nobis who also the Indian of who's known as father of Indian statistics.

[00:07:26]So what do we find now? We find that in this definition all the definition deals with numbers. It deals with quantitative facts and numerical data and how are we collecting it, how are we classifying it, tabulating and analyzing it. Further it's the all these definition also stressing on describing explaining comparing judging and so on in the different field using data and especially if you look at Bing's definition he talks about it's a sign of estimates and probability he's acknowledging the inferential aspect of statistic now this is where um I'll be explaining in the later part of my uh slides what inferial actually means here okay So till now let's put a pause at this particular definition. So these are the five definition given by the famous statisticians. Now let's move forward to linking statistic with social science.

[00:08:24]So how statistic and social science are closely linked together. Why? Because statistic provide is providing all the tools to study the human behavior. And social science on the other hand it is dealing with such complex issues we have in the society like poverty education equality public opinion and we want to make all this meaningful uh not only to quantify it but also to interpret it you to infer the data from the statistical um the data that we collect right so if you look at um in social sciences how we collecting data we're also testing theories verifying the hypothes thesis and we are uncovering these patterns in the society and now even uh here I would like to site an example like in education suppose a researcher wants to study whether an online teaching is improving a student's performance compared to a traditional teaching so here he can use a statistic method and he can compare the groups based on gender if there two groups he can use t test if it's more than two group they can he can use ANOVA and so on so this makes the conclusion more reliable rather than just an opinion.

[00:09:36]Now how it is helping the and guiding the policy makers also for example if a government wants to know if there is a new welfare scheme to reduce poverty in rural areas. Now what can they do? They can do a survey in the different households. They can collect data from different household before and after the scheme. And of course they have different statistical tools like mean income, poverty ratio, regression analysis and so on. And all that can be apply applied um to gather the information and then the policy makers can decide whether to expand or modify the scheme as well. So you see how pertinent it is that statistic is being used in the social science field. So in this way we find that the entire descriptive nature of social science is becoming analytical. It is becoming predictive and it is becoming practically by the use of statistic.

[00:10:31]Now what are the different types of statistics? Now if you want to categorize statistics into two type we have the descriptive type and of course we have the inferial statistics.

[00:10:41]Remember Bing's definition. Now I'm going to clarify what inferial statistic is. So in descriptive statistic basically we are summarizing um organizing and presenting data. We are collecting data and we are presenting it. So teacher is collecting data from 50 students and she's calculating the mean the the high score the low score the standard deviation and of course and she's plotting a bar graph and she can you know like illustrate the performance of that class. Whereas in inferial statistic what are we doing? we are drawing conclusion making prediction on the descriptive data. So whatever bar graph that the teacher has displayed now we are inferencing the information from it. So to summarize descriptive data what does the data is showcasing what it is showing you and what can we conclude or predict beyond this data that is where the inferial statistic comes into play. Now let's move forward and we'll be looking into the different functions of statistics.

[00:11:43]So, so far I hope you're all on the same page. We know what statistic is and we know the different types of statistic.

[00:11:49]Now, how does statistic function? So, first it functions to present facts in a definite form. We don't want a vague statement like there's a lot of unemployment in in India. But if we have a statement like for example the XYZ report in 2022 reported that 7.6% 6% of the unemployment rate is in a particular rural um district or or rural area then it makes sense. It validates it's just not an opinion. It is based on some facts. It's more convincing. It is more clear. Secondly, precision to the facts like we want to be very precise what we are going to talk about. So here even if I say that um uh saying that the individual prices are less informative than a general price index it's kind of you know still very vague. We have to be explicit in that. So if I talk about consumer price index CPI, how the inflation grows to up to 7% in March in 2025, then it's more precise precise and meaningful in its stating that it is the goods are becoming costlier.

[00:12:56]Then coming to the comparison how even statistic functions in comparing things.

[00:13:02]So if I say that India's uh literacy rate is 77 77.7%.

[00:13:08]So statistic comparison would be that India's literacy rate is 77.7%.

[00:13:14]Of course with the help of some report I'll be defending it and it is lower than for example China and I'll be stat I'll be quoting the percentage it could be six 96.8% and it could be higher than for example Afghanistan which could be 62.3%. So the comparison by statistics it helps in comparing things for better understanding and for policym as well.

[00:13:42]Then formulating and testing hypothesis how we're basically testing the hypothesis and uh and with the help of statistical techniques we know the um if the hypothesis is supposed to be rejected or if it is failed to be rejected we try to do that. So the same way if we say that um the higher taxes on the tea export reduce the tea consumption abroad. So the we know that the trade data uh the the trade data before and after the tax is imposed and it can be statistically confirmed and we can reject the hypothesis accordingly.

[00:14:17]Then forecasting statistic also helps in forecasting. For example, if I say that the population um on an average is increasing by 2% per year and in 2024 it was for example 1.4 billion and in 2025 we can forecast that it will be 1.42 billions. So with this prediction it can help in so many aspect. The businessmen can be also benefited by this information. They know the future demands. what are goods that they're going to produce and how are they going to you know satisfy the demand of this growing population then it enlarges knowledge also it makes us aware like Whipple has rightly remarked that statistic enable one to enlarge his horizon you know so you're thinking if a youth is reading about unemployment news that it is highest in urban areas so this should spark his interest it should broaden his horizon he should study more about it and understand Why is this taking place?

[00:15:15]Right?

[00:15:17]So I hope till here you're um you have understood the function of statistics.

[00:15:22]So now we'll be moving to the importance of statistic where all are we using the statistics. So of course we're using statistic in different industries where we it is of great importance and the whole demand and supply is taking place based on the statistical data. So of course statistics have great importance in the uh working of an industry. The same with economics. We do know that in in economics we are collecting data. We are studying the import export inflation rate the per capita income and so on.

[00:15:54]And we need to also present the data in a very graphical manner. We have to illustrate through pira by charts um histogram and bar graph. So our objective is that we need to make the data more easily understandable for the general public. In mathematics you know stats and mathematics are complimentary subjects. Basically statistics also use mathematics derivation basic algebra for analysis purposes and of course in mathematics we're using descriptive statistic in the form of central tendency measures dispersion measures and estimation hypothesis testing. So you see statistic is also called what a branch of applied mathematics.

[00:16:37]Now let's look into the administrative field. Even in administrative field we find that when we want to collect data analyze it and also for interpretation of the result different sectors of administrations are using uh statistics in know when they're um implementing a project they want to know through statistic what is the result of their operation. the successful of their operation depends on the statistical data.

[00:17:02]Then in demography uh demography sorry so statistic is considered as the backbone of demography. So you know all the study that is related to uh demography that is the study of population structure the sex ratio health status and so on. So all the statistic methods are used to determine the sample size and the sampling technique based on the objectives. So if you want to study for example the mortality rate of the cancer patient. So we know from where we supposed to get the data and based and in get the information and after the appropriate sampling technique you're based um the values that are based on this we are estimating the mortality rate of the cancer patients.

[00:17:44]Now especially if you look into the importance of statistic in social science of course like I said it is helping in the presentation of facts in a very clear manner. It is making our statement more valid know more weightage if we just introduce numbers. And you you must have seen in even a daily l in uh uh uh language and daily conversation when we're talking to our friends that simple statement we say without numbers and the moment you introduce number there it adds so much weightage to it.

[00:18:15]Then of course is simplification of complex data as well. So social data is often so vast and so complicated that we have to make it meaningful and easier to interpret for the researcher for the poly policy maker even for the lay man when he reads the magazine or when he reads the newspaper everything should be very clear and everything should be meaningful to him.

[00:18:37]Then for social comparison if we want to uh in especially in social science we do make comparison based on gender based on locality in education we make you know choice of stream. So there may demographic variables on which we make the comparison. So statistics does allow it to make a very meaningful comparison.

[00:18:56]Then formulating and testing hypothesis whether if you want to test the unemployment rate in urban and rural. So of course this is the best thing that you can do that using statistic we can test our assumptions and we can and that to objectively we can test our assumptions and of course where we find that where are we supposed to accept the null ho hypothesis or where we have to reject the null hypothesis.

[00:19:22]Then prediction of future trends. This is so important in social sciences because like for example population projection or if you're in the disaster management field any prediction that you want to make that all will depend on the data that we collect right now and how authentic the data is how what statistical treatment we are coming up with that will help the upcoming challenges and making policies more effective.

[00:19:47]So yes policy making and decision making also is a part of future uh prediction of future trend. So you can see that how the government and organization they all are relying on the statistical data.

[00:19:58]They cannot believe that um a data and um you can a survey is taking place statistic data is um being collected what is the treatment of that data and how can we make it more you know evidence based uh decision can be take based on that particular data. So like census data which is guided has also guided the government in setting up new hospitals, schools and transportation uh facilities. Then reliability and validity of the research. If you want the statistical tool to help check whether the research instrument like a questionnaire is consistent which is known as under the word is reliable or which is accurate that means it is valid. So this ensures this you know validates or ensures that the research findings are trustworthy and useful. Now tell me honestly do you want to read a statistical data which is false falsified fabricated no way you can you want the data to be trustworthy so that you can believe in it. Right? Then understanding relationship between variables. This is another very important thing how social phenomena are often so interrelated especially in social science and statistics is what it is helping in measuring this this relationship scientifically and it is showing the degree and the direction in which that association between the variable is taking place and of course the examples are given for you can read the examples um along with it. Then guidance in sampling how it also is guiding in collecting sample. So it's impossible to collect sample from everyone. So what is statistics doing?

[00:21:37]It is helping in in in basically helping the researcher to narrow down which method they are supposed to use for sampling. So for example, a survey of employment among youth can study 1,000 young people instead of the whole country which is highly impossible and yet present the national trends. then contribution in um to social progress. So you see that even the whole the security you can you the uh the whole social science and you can say the the laws implications and so on all of them are being dependent on statistical data. Once you know the data that the crime rate has increased or decreased that will make the policy maker introduce different laws and safety measure basically to improve the social security.

[00:22:28]Now let's look at the use of statistics in social science. So we have seen the use that statistics can be used in social science when we have to um compile the um the census and the population data. It is uh more if it is also being very effectively and very efficiently being used in education and learning research especially in the form of standardized test tool and of course when we want to compare academic achievement and when we want to see how the academic achievement of the students is being affected by different variables then in even in the economic and employment studies we find that the statistics is helping in the social science field. So we can see the inflation, the labor market, the income distribution and especially the unemployment that is prevailing in the rural and the urban areas and let's not forget the public health and the social welfare. Here also we find if you want to study the mortality, morbidity, birth rate and nutrition level all that can be done through statistical studies right even in sociology and the social problems that are erupting that are evolving all that can be identified that can be studied and then of course we can plan our action in order to provide more social security. Then even psychology and human behavior. You know how human behavior is so complicated but statistic helps us to measure psychological variables like intelligence, attitudes, personality traits, mental health trends and so on. And of course then we try to develop the norms for different groups and even in policy formulation and governance. We do find that it is helping in designing many welfare programs and allocating resources effectively.

[00:24:17]evaluation and development program. So lastly we see that even in the social programs um they are evaluated if you want to evaluate any program it is through statistics to measure their their reach their efficiency and their impact on society.

[00:24:35]Now coming to the last part of my lecture in which we'll be looking into how statistic is being applied in different phases of research. So we find the statistics is helps also in identification of a problem. For example, you want to see the girls participation in higher education whether it is high or low. We try to gather information through statistic through sampling technique. Then of course in data collection also we want to through random sampling or stratified sampling we are making use different sampling techniques, survey design and questionnaire to collect the accurate data from there. Then when it comes to data presentation also here also we are presenting the data. We are illustrating the data in the form of graphs, charts and diagrams. So what are we doing here?

[00:25:21]We making all that complex data into something very meaningful, something very visually clear. And lastly u second last I would say it is the data analysis here where we are summarizing analyzing data through descriptive mean uh median mode and inferial uh test and so on. So this is basically what it is helping in revealing patterns and relationship in the data. Then statistic after that of course comes the interpretation part. We have to take make sure the whatever information is being displayed we are also able to interpret in the correct directions. So which actually tells us and it kind of you know avoids we any kind of a misleading result as well. So we have to make valid conclusion. And lastly would come in the form of a report writing. Even in the report writing what are we doing? We are making use of statistic. We are through very effectively through illustrations, table, figures, statist statistical summaries, we are making our report more convincing, more clear and ready for academic and policy dissemination.

[00:26:28]So to conclude, so we find that statistic is a very vital discipline and and this is something this is like a toolkit especially for a researcher because it helps to analyze, collect, analyze and interpret data and driving scientific progress and making informed decision making. And moreover we find that the ability of statistic to simplify the data is also helping many of in the in the sampling technique in the policy making and it is making our research finding more reliable and useful. So ultimately what can we say that statistic amplifies our knowledge fuels our social progress and is indispensable in every research phase.

[00:27:11]So here are the recommended reading for you to go through for more comprehensive reading on the importance of uh statistic and social sciences and I hope you enjoyed this lecture and I'll be seeing you again in the future lectures as well. So take care of yourself and have a good day. Thank you.