You have a data-set containing 10K data points where each data point is the house-hold income of a given area for example. But what do you with this data. The most fundamental tools that help in making sense of huge data-sets are "measures of Central Tendency" and "measure of Dispersion". They are also known as … Continue reading Descriptive Statistics: Measures of Central Tendency and Measures of Dispersion
We had discussed about the Random Variables previously with the help of examples "heights of people" (Hperson) and "outcome of a dice-roll"(Odice-roll). In both the cases the kind of values each of the random variables could take were different. The random variable Hperson can take any real-value between 0 feet and 15 feet while Odice-roll can only take one … Continue reading Types of Data or Types of Random Variables
What is Mean? Mean of any given distribution is a measure of central tendency of that distribution. Mean is also known as Arithmetic Mean or Average Value or Expected Value. For a data-set with discrete real values mean can simply be computed as sum of all the values in data-set divided by the number of … Continue reading How to apply Mean and Standard Deviation?
What is a random Variable? Random Variables are a means of assigning numbers to outcomes of random processes or experiments or activities. An example of random variable can be an "outcome of rolling a dice". Let us denote this random variable by symbol "Odice-roll ". The values this random variable can take can be any … Continue reading Random Variables, Distribution function and Distribution Curve: A tutorial
Google the word “experiment”, the answer returned is, “a scientific procedure undertaken to make a discovery, test a hypothesis, or demonstrate a known fact” While “Experiment” is a broader term, a controlled experiment specifically is about testing impact of a single factor /variable while the other variables remain constant. Confused? Don’t worry, read ahead. I … Continue reading Hypothesis Testing with Controlled Experiments: Computing P-value using Z-statistic