BUSINESS STATISTICS | BBA | UNIT-5 FULL EXPLANATION SEM-2 OSMANIA UNIVERSITY | ‎⁨@shivanipallela⁩

[00:00:00]Students, welcome back to our channel.

[00:00:02]So, here in this video, we are going to discuss the unit number five complete explanation of business statistics of BBA semester two.

[00:00:12]In previous videos, problematic explanation and remaining units explanation, everything were available in our channel. So, here in this video, you'll get a clarity regarding the unit number five. Absolutely, you can score 16 to 20 marks weightage questions you'll get it here. Why? Because every year, basically, unit five is a theory unit. So, 12 marks for theory.

[00:00:34]Sometimes, four marks two questions they'll ask. That means each answer carries four marks. So, 4 + 4 eight marks. So, maximum, they'll give two questions for short, but minimum to one question they'll give for short in part A. And part B, 12 marks long question. So, 16 or 20 marks weightage you can score from this unit number five. Basically, unit number five is a theoretical unit. Okay?

[00:00:59]So, whatever the questions I'm discussing in this video, however I'm explaining, everything that will be more than enough for the examination. Like how I'm showing, that that only you need to write the answers in the examination, so that you can score full marks. Clear?

[00:01:17]So, let's get into the video. First question what I have given, explain the additional and multiplicational theorems of probability with suitable examples.

[00:01:26]Okay? So, this is the question I have given in the gunshot questions. So, what is the answer? If they're asking about the addition and multiplication theory in the question from unit number five, this is the answer you need to write it.

[00:01:39]Clear? So, what is mean by probability?

[00:01:41]First, you need to write the introduction. Probability is a branch of statistics that measures the chance of occurrence of an event. So, probably, this may happen. Like that we will send we will frame a sentence. No? Same like that only.

[00:01:57]An event, how many uh it is having a chance to appear? That is nothing about a probability.

[00:02:04]Probability is a branch, it is a one part of the statistics only. Okay? The addition and multiplication theorems are important rules used to calculate probabilities in different situations.

[00:02:16]This addition theories and multiplication theories, whatever you're having, it will be useful to calculate the probability in different situations, it seems. So, this is introduction you need to write it compulsory. Three to four lines is. Then you need to write the meaning of the probability. Probability is nothing about a likelihood or a chance of an event occurring. Okay? It is nothing about a likelihood or a chance of event occurring. It is always lies between the zero to one. So, the probability will become always in zero to one. In that range only the probability should be there. It should be there. So, this is the meaning of the probability.

[00:02:53]Then you need to write the definition of the probability and formula. What is the definition? Probability is defined as the ratio of the number of favorable outcomes to the number of possible outcomes. So, here we are writing about the probability is nothing about the favorable outcomes divided by possible outcomes. Okay? So, what is the formula for this probability? P of E is equal to number of favorable items divided by total number of possible outcomes.

[00:03:23]Okay? Favorable outcomes divided by possible outcomes. So, this is the definition as well as the formula.

[00:03:30]Clear, ma? Understood? So, any question related to the unit number five related to the probability or additional multiplication theorem, definitely 200% you need to write the introduction. You need to write the meaning. You need to write the definition. You need to write the formula also. Okay? Now, coming back to the additional theorem. First, we will discuss about the additional theorem. We all know by seeing the name only we can able to identify it is a addition. Okay, the addition theorem is used to find the probability either one event or another event. Occurrence of the one event or another event that is considered as a additional event additional theorem. Okay, so what will be the formula see here.

[00:04:14]P P of A union B this is symbol U is symbol of your union.

[00:04:21]A union B is equal to P of A plus P of B minus P of A intersection. This is the formula. This reverse U is nothing about intersection.

[00:04:34]Union intersection. Clear? You need to identify that. So compulsory you need to remember the formula ma. It is very important to remember the formula. So remember it. Okay.

[00:04:45]After doing this what is the side points you can use it for this additional theorem. Okay, this is the side points you can write it over here. First one is used for union of events. What is this used for union of events? This additional theorem is used for the probability of event A and event B. How many times it is occurring event A? How many times B event is occurring like that for that case this union event is useful. That means side points of the additional theorem. Second one what it will do means sorry for the extremely disturbance for the background. Just wait a minute.

[00:05:17]Okay.

[00:05:19]Second one what it will do means it will avoid the double counting. With the help of this additional theorem what it will happen means it will avoid the double counting of the events. Okay, third one is the applicable to overlapping the events. So this theorem additional theorem is mainly used when two events are having the common outcome. For example A is having the outcome of five, B is having also five.

[00:05:43]That time this theorem will be useful for the overlapping of the events. Okay.

[00:05:50]So, these are the common points, ma'am.

[00:05:52]Like for example, in the examination, you can write like this a flowchart.

[00:05:56]This is a word counting, double counting, overlapping, and like that.

[00:06:00]Okay. Diagrammatical representation of your answers is also very, very, very important. Okay. What is the example?

[00:06:07]See here the example. For example, if P of A is equal to 0.5, P of B is equal to 0.4, A intersection B is 0.2, then A union B what it will happen?

[00:06:19]A intersection B they have given. We need to calculate A union B. How we will calculate A union B? What is the formula? 0.5 + 0.4 - 0.2. Then you'll get 0.7. This is This is just an example, ma'am. In the examination also you can take your own values and you can write it here. Okay, this is called additional theorem. Next one, ma'am, multiplication of theorem. That means multiplication is theorem is used to find out the probability of both events are occurring together.

[00:06:49]If both are occurring together, we will use this multiplication theorem.

[00:06:54]There are two segments, ma'am, dependent events and independent events. Dependent events formula is this one. Independent events formula is this one. Okay. Only one change you'll have. Here you'll have the A here, now you will not have A.

[00:07:06]That is the only difference. So, in multiplication theorem you'll have the dependent and independent events. Okay.

[00:07:12]What is the side points you can write it over here. First one, ma'am, it is used only for the joint events. For example, if both are occurring at the same time.

[00:07:20]Okay, together. That time this multiplication theorem will be used. And independent events, means for example, if events does not affect each other, like multiplications of the probabilities if we can do the directly, that time this multiplication theories will be there. And dependent events.

[00:07:36]Dependent event is nothing about one will be the affecting on the another.

[00:07:40]Okay. Using the conditional probability, if one event affects the another, so we will use this multiplication theorem.

[00:07:47]Okay, this is the side points you can write it over here.

[00:07:50]So, what is the example you can do it here means, for example, the probability of getting a head is half percent, the probability of getting a thing is a half percent, the probability of getting six on a die is 1/6. So, 1/6 will be the probability. So, how you will do this is the formula.

[00:08:07]Okay, according to the formula, I'm just multiplying it. So, what is the probability of getting the head? 1/2.

[00:08:13]What is the probability of getting the die at six times? 1/6. So, 1/2 divided by into 1/6. Okay, so like that you need to do it. Clear? So, you can take it the own values and you can do it here in the examination. So, what will be the conclusion part you can write it over here. The additional theorem will be helpful to calculate the event occurring, whereas multiplication theory will be helpful to the probability of getting together. That time this will be useful. So, both the theorems are widely used in the business, economics, and the statistics also. Like that you can write it here first answer. So, first answer additional theory and multiplication theory we have done with the answer. In the examination, exactly this answer if you could write it means 12 on 12 marks you can able to get it. Second question is about the conditional probability and base theorem with suitable illustrations. This is also one of the main important thing.

[00:09:04]>> [snorts] >> Conditional probability and base theorem are important concepts in probability.

[00:09:09]They help us to understand the probabilities when additional information is available. Okay, so this conditional probability and base theorem both are the important concepts in the probability. So, when information is available, so this time this will be helpful. Like that you need to write the introduction. Then what is the meaning?

[00:09:24]Meaning is nothing about conditional probability. First you need to explain what is meant by conditional probability. So, conditional probability is nothing about the probability when event occurring when other event is already occurred. Okay, Already one event is occurred and another event is occurring. That time this is called conditional probability. What is the definition? Conditional probability is a probability of event A given that event B already occurred.

[00:09:50]Event B already there, but event A is occurring. That time it is considered as a conditional probability. What is the formula of the conditional probability?

[00:09:59]This is the formula of the conditional probability. Formulas remembering is very, very, very important. So, compulsory you need to remember the formulas. Clear, ma? Clear with the formulas? Next, what is the side headings you can write it for this means?

[00:10:13]>> [snorts] >> It is depending on the another event.

[00:10:15]Basically, this conditional probability will be depending on the another event because already another event will be occurred in the thing, so that's why.

[00:10:23]Basically, it is useful for the decision-making based on the available information and it is useful in the real life also. Like for example, marketing, in the HR team, HR finance, insurance, diagnosis, in all these departments, this will be helpful. Clear? So, for example, here illustration I have taken, example I have taken. For example, in a bag it is containing five red balls and five blue balls in a bag. So, one red ball is already selected. The probability of selecting another red ball changes there because one red ball already removed. So, for example, in a bag five red balls, five blue balls five blue balls is there. One red ball already it is coming out, okay? So, out of five one is already came, okay? In bag how many it is there? Only four. So, because one red ball already removed, so the probability of selecting another will be changing. So, 4 by 10 only will be the probability of the answer like that, okay? Coming back to the base theorem in the second question, what is mean by base theorem? Base theorem is nothing about a probability used to find out the revised data, okay? New information if you want to do it means we will consider this a base theorem.

[00:11:29]So, base theorem base theorem calculate conditional probability using the prior probability.

[00:11:34]So, this is the formula of the Bayes theorem. So, compulsory uh remembering the formulas is very important. That is the only task you are having in unit number five. What is the side headings you can use it in your home? So, it will be used for the prior information. Okay?

[00:11:48]So, basically it updates the probability for the new evidence everything. And it will be helpful for the prediction and it will be helpful for the forecasting of your uh data and the risk analysis. And it is widely applied. Means it is useful for the medical, it is useful for the science, insurance, banking, artificial intelligence. For every department, this is useful. Okay? So, in illustration for this means uh example for this Bayes theorem is So, a medical test is positive. Bayes theorem will be helpful to calculate the actual probability uh he has a disease after continuing the after considering the previous information.

[00:12:24]From the consideration of the previous thing. So, how it will be helpful to analyze the disease of a person like that. Okay? So, this is the example of the Bayes theorem. So, overall conclusion, just give me a minute.

[00:12:36]Um Mhm.

[00:12:38]Overall conclusion will be conditional probability will be helpful to calculate the probability. Whereas Bayes theorem will be helpful to calculate the new information because both are available only. So, it both conditional probability and Bayes theorem both are important tools in the business statistics. Okay? Next one, my third and the last question is about the sampling.

[00:12:58]Very very very very very very very important about the sampling. Again, I'm saying sampling is very very very very very important. Okay? You should not skip the sampling questions. Okay? So, coming back to the introduction part.

[00:13:14]In statistics, studying every member of population is difficult. Okay? So, sample is selected to represent the whole population. This is called sampling. For example, in India there point there are 1.3 million people are there. Is it correct that uh the person has went each and every door and he was counted the people? No, definitely no.

[00:13:35]So, that time the sample is selected to represent the whole population. So, whatever the process is called, this will be considered as a sampling. Okay?

[00:13:44]What is the meaning of the sampling?

[00:13:46]Sampling is a process of selecting small group from a large population for statistical study. From this Telangana state, I am just picking one state of the population. I am doing the analysis and I am representing whole state by taking that sample. Okay? So, that is What is the definition? Sampling is a method of selecting a representative part of population to draw conclusions about the entire population. For the entire populations, whatever the conclusions you are doing, that will be considered as a sampling. Okay? What is mean by probability sampling?

[00:14:20]Probability sampling is nothing about every every unit Every event will have the equal chance of getting selected.

[00:14:28]Okay? So, that is called probability sampling. Okay? So, what are the different types of sampling you're having? First one, ma, simple random sampling you're having. That means every member has a equal chance of getting that. It will be very simple and unbiased. Okay? This is the first one that is considered as a simple random sampling. Okay? Second one, ma, systematic sampling. Systematic sampling is nothing about every nth item is selected after choosing a random start point. For example, 1 2 3 4 5 6 6 lines is there.

[00:15:03]So, we are just choosing the this one.

[00:15:06]After completing this one, this one will come. After this, after this, after this. So, like that, we are getting a random starting point. Okay? Next one, ma, stratified sampling. Stratified sampling is also known as a strata.

[00:15:18]Okay? The The population is divided into homogeneous and samples will selected from the each group. Next one more cluster sampling. Cluster sampling is nothing about it is also divided population is divided into clusters and some clusters will be studying the random like it will be selected randomly for the study.

[00:15:38]So next one more non-probability sampling. What is meant by non-probability sampling?

[00:15:42]Non-probability sampling is nothing about every unit will also does not get a equal chance. In probability they will get the equal chance but here you will not get the equal chance. That is called non-probability sampling. What are the different types you are having here in the non-probability sampling means first one you are having convenience sampling. Convenience sampling is it is selected based on the availability. If it is available means it will be selected. If it is not available means again it is need to be waited. Next one more judgmental sampling. Judgmental sampling is nothing about based on the personal knowledge and the experience we are judging the samples.

[00:16:17]Okay. So whether it is correct or not completely we are judging that. So rather than anything.

[00:16:23]Okay, that is called judgment sampling.

[00:16:25]Next one more quota sampling. Quota sampling is nothing about fixed quotas will be there. Every year 10% will be fixed for this part of data. Every year 20 seats were fixed for this data. Like different groups there will be a fixed quotas more. Same like that don't the sampling will also be quota fixed quotas. Second fourth one more snowball sampling. Snowball sampling is nothing about existing participant will identify and they will recruit the new participants. So that kind of thing is called snowball sampling. Means already existing persons will decide and they will recruit the new participants. Okay, that is called snowball sampling.

[00:17:04]So what is the differences between sampling probability and non-probability sampling means probability will get a equal chance.

[00:17:12]Non-probability will get a unequal chance. It is a random selection. It is a non-random selection. It is more accurate, it is less accurate, it is less biased, it is more biased. So, that is the differences between even for they're asking for four marks also, this is the table you can draw it. But, you can elaborate some or the other thing more, okay? Next one now, conclusion.

[00:17:31]What is a conclusion you can give it over here means sampling will be helpful to save your time, cost, and effort while studying a population. Probability sampling will give more reliable results when it's compared to the non-sampling.

[00:17:45]Compared to the non-probability sampling, probability sampling will give you the reliable results, okay? So, sampling is easy and quick when random sample is not possible. Clear now? So, that's it about the unit number five. So, I hope that you have understood very easily. In unit number five, sampling is one of the main concept. Every year they will ask the question, so don't skip the sampling concept into your preparation, okay?

[00:18:14]Again and again I'm saying, still if you're having any further doubts, do let me know in the comment section how you felt about the explanation video. If you could understand the explanation video means comment down yellow color heart, okay? Yellow color heart symbol in the comment section, so that I'll get to know that you have watched the video till the end. That's it. See you all in the next video now.

[00:18:36]All the very best and bye-bye.