Data Science Thoughts

  1. What is Hypothesis Testing and when do we use it? Hypothesis testing is a part of statistical analysis, where we test the assumptions made regarding a population parameter. It is generally used when we were to compare: a single group with an external standard two or more groups with each other A  Parameter  is a number that describes the data from the  population  whereas, a  Statistic  is a number that describes the data from a  sample . 2. Terminology used Null Hypothesis:  Null hypothesis is a statistical theory that suggests there is no statistical significance exists between the populations. Alternative Hypothesis:  An Alternative hypothesis suggests there is a significant difference between the population parameters. It could be greater or smaller. Basically, it is the contrast of the Null Hypothesis. Note: H 0  must always contain equality(=). H a  always contains difference( ≠,  >, <). For example, if we...

 -> We are going to have a deep discussion on the Z score. But right before that, we need to understand what a normal distribution and a standard normal distribution are. What is a distribution? A distribution in statistics is a function that shows the possible values for a variable and how often they occur. it may occur with various different values like age, height, the weight of people. What is a Normal distribution? The normal distribution is a distribution that is symmetric about the mean(mean is nothing but average of all the observations). Most of the observations in the normal distribution are surrounded by the mean. What is a standard normal distribution? The standard normal distribution is a normal distribution whose mean and standard deviation are scaled at 0 and 1 respectively. Z score can only be calculated for the observations which follow a normal distribution. What is a Z score? A Z-score is a numerical measurement that describes a value’s relationship to the mea...