 Hi everyone, it's MJ and welcome to this introductory video on confidence intervals. Now we know the whole big picture of statistics is that we have some data, we want to work out some information on it so we can answer questions and optimize processes. Now the information we want are the parameters and distribution of the random variable that generated the data in the first place. Now in the previous course called point estimation, we had to go at working out the parameters so if the parameter was given by this our estimator has got the little hat. However what we realize is that this estimator itself has got its own set of parameters and its own distribution and that is because this thing over here is its own random variable which means that its value is not stable. So we might be coming up with a single value but that single value is going to be maybe greater or less than the true value. So what we do is we construct something known as a confidence interval and essentially this is a range. We have a lower bound and we have an upper bound. And in the course we look at various things. We look at what is the width of this range and we are also going to be looking at the confidence side of this interval. What do we mean by confidence? What do we mean when we say something is 95% significant? So these are all big concepts that we're going to be introducing in this course but it's a step up from the previous one where in point estimation we were looking at a single value. We're now understanding that well these single values are random variables in their own right and it might be better for us to look at a range. And once we start looking at this range it's going to help us when we come to hypothesis testing which is the following course. But as always if you have any questions please feel free to ask. This is just how confidence intervals fit in the whole big picture of statistics. Keep well. Cheers.