The elements of a list can be added or removed after it has been created.
To add new elements at the end of a list, Py
Python uses class for object-oriented programming. A class represents the general behavior or information that the programmer or data analyst focuses on. When a class is created, particular objects belonging to this class can be created. This process is called instantiation. Class contains attributes, methods, or functions for general purpose. Attributes for instances can be modified by directly assigning new values, or by using methods defined in a class.
Normal distribution is describing random variables with bell-shaped probability density functions. Normal distribution is widely used in data science because large sample random variates have a mean value which follows approximate normal distribution if variates are independently drawn from any distributions. The probability density function for normal distribution is determined by two parameters: mean(miu) and standard deviation(sigma).
List is the simplest type of data structure in Python programming. A list is used to store a collection of elements of same type (numeric, string, etc.). In Python, a pair of brackets [] indicates the data object is a list type. For example, the following two statements create two lists, in which one is numeric and the other is of string type.
Python is among the most popular programming language for data science nowadays, and getting started with Python is quite easy. You can just install e.g. a free platform like Anaconda, then you can get direct access to Python as well as most of its preinstalled modules (Numpy, pandas, matplotlib, etc.), its IDE (Spyder, etc) and its easygoing package management tools.
When we perform data analysis using Python, it is often useful to pass a list in calling the function as we want each element of the list to be accessed by the function.
A function in Python is a group of code statements wrapped together to perform specific tasks. After a function is defined, then it can be called by passing real values to its arguments and get the returning results. A while loop in Python is a group of conditional statements bundled in a statement beginning with keyword ‘while’, and the codes will run forever until the condition returns false. By including a user-defined function inside a while loop in Python, many iterative tasks can be fulfilled.
Poisson distribution is a discrete distribution. It is frequently used to model the counts of event occurrence during a specified time interval, such as telephone calls coming in to a call center in a given day. There is one parameter in the Poisson probability function, λ, which denotes the constant occurring rate in a Poisson process.
In hypothesis testing, the possibility of the other side than the conclusion usually exists, and the analysis commits so-called Type I and Type II errors, with respect to the truth and the decision made upon the random sample and hypotheses. In particular, a Type I error measures the probability that a true Null hypothesis (H0) is incorrectly rejected, and a Type II error says the probability that a false H0 not being rejected, respectively.