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...]

## Difference Between Parametric and Nonparametric Test

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...]

## Difference Between Histogram and Bar Graph

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...]

## Difference Between Area and Perimeter

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...]

## Difference Between Mean and Median

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...]

## Difference Between Statistic and Parameter

In statistics vocabulary, we often deal with the terms parameter and statistic, which play a vital role in the determination of the sample size. Parameter implies a summary description of the characteristics of the target population. On the other extreme, the statistic is a summary value of a small group of population i.e. sample. The parameter is drawn from the measurements of units in the population. As against this, the statistic is drawn from the measurement of the elements of the … [Read more...]

## Difference Between Sample Mean and Population Mean

In statistic, the arithmetic mean is one of the ideal measures of central tendency. For a given set of observations, the arithmetic mean can be calculated by adding all the observations and dividing the value obtained by the number of observations. There are two types of mean, i.e. sample mean and population mean, which is often used in statistics and probability. The sample mean is mainly used to estimate the population mean when population mean is not known as they have the same expected … [Read more...]

## Difference Between Variance and Standard Deviation

Dispersion indicates the extent to which observations deviate from an appropriate measure of central tendency. Measures of dispersion fall into two categories i.e. an absolute measure of dispersion and relative measure of dispersion. Variance and standard deviation are two types of an absolute measure of variability; that describes how the observations are spread out around the mean. Variance is nothing but the average of the squares of the deviations, Unlike, standard deviation is the square … [Read more...]

## Difference Between Permutation and Combination

In mathematics, you might have heard the notions of permutation and combination end number of times, but have you ever imagined that these two are different concepts? The fundamental difference between permutation and combination is the order of objects, in permutation the order of objects is very important, i.e. the arrangement must be in the stipulated order of the number of objects, taken only some or all at a time. As against this, in the case of a combination, the order does not matter … [Read more...]

## Difference Between Sampling and Non-Sampling Error

Sampling error is one which occurs due to unrepresentativeness of the sample selected for observation. Conversely, non-sampling error is an error arise from human error, such as error in problem identification, method or procedure used, etc. An ideal research design seeks to control various types of error, but there are some potential sources which may affect it. In sampling theory, total error can be defined as the variation between the mean value of population parameter and the observed … [Read more...]

- « Previous Page
- 1
- …
- 64
- 65
- 66
- 67
- 68
- …
- 84
- Next Page »