Key Differences

The binomial distribution is one, whose possible number of outcomes are two, i.e. success or failure. On the other hand, there is no limit of possible outcomes in Poisson distribution The theoretical probability distribution is defined as a function which assigns a probability to each possible outcomes of the statistical experiment. The probability distribution can be discrete or continuous, where, in the discrete random variable, the total probability is allocated to different mass points … [Read more...]

In today's fast-paced world, statistics is playing a major role in the field of research; that helps in the collection, analysis and presentation of data in a measurable form. It is quite hard to identify, whether the research relies on descriptive statistics or inferential statistics, as people usually, lacks knowledge about these two branches of statistics. As the name suggests, descriptive statistics is one which describes the population. On the other end, Inferential statistics is used to … [Read more...]

In geometry, there are many types of a quadrilateral i.e. parallelogram, rhombus, square, rectangle, trapezium, and kite, which share common characteristics, due to which people face trouble in understanding these figures. A rhombus can be referred as a slanting square, whose adjacent sides are equal. On the contrary, a parallelogram is a slanting rectangle with two sets of parallel opposite sides. The basic difference between rhombus and parallelogram lies in their properties, i.e. all the … [Read more...]

Ratio and proportion are two mathematical concepts which have end number of practical applications in different spheres of life. The ratio is used to compare the quantities of two different categories like the ratio of men to women in the city. Here, men and women are the two different categories. On the contrary, Proportion is used to find out the quantity of one category over the total, like the proportion of men out of total people living in the city. Ratio defines the quantitative … [Read more...]

Correlation and Regression are the two analysis based on multivariate distribution. A multivariate distribution is described as a distribution of multiple variables. Correlation is described as the analysis which lets us know the association or the absence of the relationship between two variables 'x' and 'y'. On the other end, Regression analysis, predicts the value of the dependent variable based on the known value of the independent variable, assuming that average mathematical relationship … [Read more...]

To make the generalisation about the population from the sample, statistical tests are used. A statistical test is a formal technique that relies on the probability distribution, for reaching the conclusion concerning the reasonableness of the hypothesis. These hypothetical testing related to differences are classified as parametric and nonparametric tests.The parametric test is one which has information about the population parameter. On the other hand, the nonparametric test is one where … [Read more...]

The fundamental difference between histogram and bar graph will help you to identify the two easily is that there are gaps between bars in a bar graph but in the histogram, the bars are adjacent to each other. After the collection and verification of data, it needs to be compiled and displayed in such a way that it highlights the essential features clearly to the users. The statistical analysis can only be performed if it is properly presented. There are three modes of presentation of data … [Read more...]

Area and perimeter are two vital fundamental concepts of mathematics, which are often understood together. These two concepts are used to measure the physical space of an object and forms a foundation for advanced mathematics. The perimeter is often understood as the length of the path that covers a closed figure while the area refers to the space covered by the closed figure. Both the concepts have practical application and are used in our day to day life. While the area is nothing but the … [Read more...]

Central tendency implies the tendency of the data points to cluster around its central or middle-most value. The two most commonly used measures of central tendency are mean and median. Mean is defined as the 'central' value of the given set of data whereas median is the 'middle-most' value in the given set of data. An ideal measure of central tendency is one which is clearly defined, easily understood, simply calculable. It should be based on all observations and least affected by extreme … [Read more...]