Data Literacy

Basic Statistics Mini-Course for absolute beginners is designed for learners without a mathematics or statistics background or training. It is especially useful for those looking to gain a solid grasp of the foundations of statistics and data analysis before deciding how deep they would like to dive into the world of statistics. Basic Statistics explains without jargon

Bivariate statistics or two variable statistics is a type of inferential statistics that deals with the relationship between two variables (e.g., price and demand). Bivariate statistics examines how one variable compares with or influences another variable (e.g., how price can drive demand). A correlation coefficient or a regression model can be used to quantify the

The binomial distribution is a representation of the results of repeated experiments which are independent and identical and in which there are two possible outcomes each time. This post constitutes Lesson 6 of the Basic Statistics Mini-Course. You may also be interested in Bivariate statistics or two variable statistics. Key concepts covered in this post: the

Data mining (DM) applies machine learning techniques and statistical models to uncover hidden patterns in large data sets (Big Data analytics) especially in the context of KDD (knowledge discovery in databases). Data mining is the analysis step of the KDD process. You may also be interested in Normal distribution or Gaussian distribution. DM software: IBM

Normal distribution or Gaussian distribution or Gauss distribution or Laplace–Gauss distribution, in probability theory, is a type of continuous probability distribution for a real-valued random variable. This post constitutes Lesson 5 of the Basic Statistics Mini-Course. You may be also interested in Normal approximation to the binomial distribution. Key concepts covered in this post: the normal

Data spread or data variability of a distribution is the extent to which the scores vary around their central tendency. Data spread is a measure of how far the numbers in a data set are away from the mean or median. Common methods to investigate the variability in data sets are the range, the interquartile range,

Measures of central tendency help us locate the centre of the data, which allows us to make predictions about what is likely to happen. The most common measures of central tendency are the mean, the median, and the mode. This post constitutes Lesson 3 of the Basic Statistics Mini-Course. You may be also interested in Analyzing