Alright. So now we're gonna have a bit of an abstract discussion on how information can be useful to the users. Alright, let's check it out. So for information to be useful to the users. Well, it's going to have to have two fundamental qualitative characteristics. We call them fundamental qualitative characteristics. And these two are relevance and faithful representation. Alright, let's start here with relevance, relevance. Is that the information is gonna make a difference in the user's decision making? Okay. So it's actually gonna be relevant to their decision. Right, relevance is gonna be relevant to them. So how is it relevant? Well, it's gonna have these two characteristics to be relevant. Okay, The first one is it's having predictive value. Okay, so what do you think predictive value is gonna do? What's gonna enable users to predict future outcomes. Right? So that's pretty relevant If it's information that can help them gauge what's gonna happen in the future. That seems pretty relevant, Right? So, they're predictive value and guess what confirmatory value is gonna do? Well, it's gonna help users confirm their previous predictions. Okay. So they might have made a prediction in the past. And now they're going to use this information to see if that prediction was true or not. Okay, so that's the relevance about faithful representation. Right, faithful representation. Well, this is that the information is true, right? The information has to be true and to go a little deeper. Let's talk about these three characteristics here. So faithful representation. We talk about completeness. Alright. Completeness means that the company is providing all relevant information right? They're not holding anything back there, showing everything that should be shown. They're showing it to the user's next is neutrality. Right? Well, neutrality, that means that the information is unbiased. Right? The company is not taking one side or the other. Are trying to pad things to make it look better. Right there. Unbiased. They're just showing you information and you do what you will with it. Last is freedom from material error. Alright. Material error notice we're not saying that they can be perfect. Material error means a big error. Okay. Means that there are no I'll say large errors in the information. Alright. We know no one's perfect. And if you think about a company like say coca cola or Apple or amazon that their billion dollar companies To say that, you know, if they lost a $5 bill here or there $100 is missing. It's probably not gonna be a huge impact on the users of the information, right? Because there's so much bigger numbers that they're dealing with. That these small errors they can slide by. Okay, So the freedom from material error. We talked about materiality and that's a threshold for how big an error can be. Okay. And that all depends on the size of the company. You can imagine a small company, maybe $100 missing could be a big deal but for a company like coca cola. You know, if that gets by they're gonna just not spend the time uh figuring out where that went. Okay, So let's pause here and then in the next video, we'll follow up with the conceptual framework. This is the way the faz be considers, uh, information to be useful. They use the conceptual framework to kind of put this all together. All right, so let's pause here and then continue in the next video.