2. Why we use statistics in agriculture?
Transcript
Welcome to the next lecture on statistics for agriculturist. In this lecture we are predominantly focused on why we use statistics in agriculture.
Continuing the previous lecture where in which I talked about graphical representation this is the area representation. In area representation you can see at different spots what is the yield happening. The red zones are zones where the yield is not as expected, the green zones are places where the yield is more than the expected. Now you can see there are patches, from these patches you can extract information and find out why is this patch giving a better yield as compared to that of the red zones. So, this will give you information and knowledge to remove these red zones and make it into green zones. While doing data there is always a variability which comes into existence. In statistics we call this also as error. The error can be based on human, it can be based on instrument.
Instrument it directly depends on resolution. When we talk about the magnitude we always talk about resolution. For example, resolution of a LCD screen, or a smart phone screen, is pixel. The minimum value which you can measure is called as resolution. If you try to use a instrument which does not have lot of graduations in between two main scales then, the resolution is little weaker, and in some times we also use binary data discretion. So there also you have the term called as error. So, we have to focus in reducing the error and trying to get the original data, so the statistics helps us to find out these variabilities in the measurement. This variability makes the use of statistics necessary. Statistics, therefore, helps us to quantify and assess those error also. When we talk about these errors there are two important things one is called as naturally happening error, the second one is accidentally happening error. Naturally happening error means over a period of time what happens the person undergoes fatigue the data, which is measured has a small deviation henceforth, so that is natural. Accidental means while trying to represent the data 20.2 the person makes an error by one decimal, he writes it as 2.02 so, this is an accidental error. So, by using statistics we will be able to find out the naturally occurring variables and accidentally occurring variables statistics helps us in understanding the current facilities and tells us what improvements are to be made such that you can improve the yield.
When we try to follow strictly, statistics in the field we try to do two important things, one is we ensure replication, we ensure randomization. Replication means trying to repeat the same set of experiments and trying to measure the given output. Just by one single data point giving interpretation will be always misleading. So, statistics helps us to repeat the experiments and validate your data. For example, repeat experiments in this season go to the next season do the same set of experiments go to the next season, do the same set of experiments now measure the yield so, that is replication. Randomization is try to use you have a large area, you try to divide that large area into several small patches. This can be form or field, so you try to divide them and try to do your experiments in this patch, this patch, this patch and then try to see what is that you get as an output. So, here we randomize the experiments to talk about the productivity in the field. So, replication and randomization are most important steps while doing experiments. By doing all these things what are we trying to do? We are always trying to keep a point of enhancing productivity with minimum input, trying to get maximum output. Organization like NASA tries to get a satellite image and try to give interpretations to the farmers and suggest them what all things they have to do such that their productivity enhances. This helps the farmer increase their yield and income on a least usage of resources.
The data which is acquired also gives us the most important thing is prediction, based upon the data what you have, the experiments what you have convened you try to predict the future. In agriculture prediction is very very important. How will my yield be at the end of this season provided the other conditions like, humidity, the insect which is trying to hit, the temperature, the rainfall are moving up or down. So, and its influence on the output is very important for the farmer to know. Based upon the production the farmer tries to do several primitive measures such that his productivity mark is reached.
In this lecture, we studied two important things – the need for statistics, randomization, repetition using for enhancing productivity, and prediction for the future.
Thank you.
