Discussion
One of the concepts of chapter three that is crystal clear is the application of additional rule on mutually exclusive events. This is because the concept requires one to understand the definition of a mutually exclusive event. Events are mutually exclusive if they cannot occur in the same period. One event must occur first. Thus, the probability of all the events occurring the same time is zero.
The understanding above tells me that the application of the additional rule is straightforward. For example, in a classroom, there are only two pupils a boy and a girl. The probability of the teacher calling a boy or a girl to answer a question is got by adding the probability of calling a boy or a girl. P (b or g) = p(b) +p (g)= 1. This is because the probability of occurrence of each event is 0.5
The concept that is as clear as mud is the conditional probability. This gets complex to me because an event happens then the second one happens. It is surprising how the probability of same successive events falls. The scenario happens even when the two events are similar to each other. For example, in a bag containing five red balls and five green ones the probability of choosing the second red ball is different depending on the first one. I can’t even relate this to any real life application.
The application of expected values is simple only if you know the formulae to use in different scenarios. This means that if you apply the wrong formulae, you get the wrong value. Moreover, you need to know the basic rule. This rule states that money received in the future has got less value than money received today, assuming the nominal values are the same.
It is very simple to understand a continuous variable because you just need to think of a variable that can take any value. For example, a piece of meat can be 4 kg, 1.1kg, 1.2 kg, 1.112 kg, etc. Thus, the variables can form a line. On the other hand, discrete variable takes specific values. They can be taken as specific points plotted on a chart.
