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Viewer RatingToday, I want to discuss on a very important topic on inferential statistics area and that is “Hypothesis”. Hypothesis means a conclusion based on some evidence collected from data for a certain time. In statistics , we explain hypothesis in two ways: When we have something already defined, we shall put the assumption under … Read more
Viewer RatingLet us start today’s topic on uniform probability distribution (I will discuss on continuous dist today). Now, the concept comes in two forms: discrete and continuous. If I toss a coin then there are two possible outcomes: Head and Tail. If I roll a die, then it always return a digit (1 or 2or … Read more
Viewer RatingToday, I would like to extend my previous topic on discrete probability distribution with the concept of Binomial Distribution. A binomial distribution is a specific probability distribution. It is used to model the probability of obtaining one of two outcomes, a certain number of times k out of fixed number of trials N of a discrete random … Read more
Viewer RatingIn today’s topic I want to explain how we plot the distribution of a random discrete variable. Key terms: expected mean, probability, variance and standard deviation. Let’s explain it by an example. For rolling a Die, let us assume a random variable X (x=1,2,3,4,5,6). The probability is P(x) =1/6. That is exactly same for … Read more
Viewer RatingToday’s topic is random variable. It is better to start with an example: Suppose I roll a die. What are the probable outcomes? Exactly 1 or exactly 2 or exactly 3 or exactly 4 or exactly 5 or exactly 6. No number in between. Let’s put another example: if I want to know the … Read more
Viewer RatingIn statistics, a sample is a part of a population and a population is a whole; it’s every member of a group. All elements in a sample must also by definition be part of the population as it is defined. The sample should be representative of the population from which it is drawn. In … Read more