12/06/2022 | By: FDS
Standardization is a statistical process in which a given set of numbers is converted into a new set of numbers that all have the same mean and standard deviation. The newly generated set of numbers is called standardized data. It is often used to compare different sets of data or to put data into a more homogeneous format.
12/06/2022 | By: FDS
A nonparametric test is a statistical test that does not require any assumptions about the distribution of the data. They are particularly useful when you have data that is not normally distributed or when you do not have information about the distribution available. Nonparametric tests tend to be less powerful than parametric tests, but in many cases they can be used to test the same hypotheses.
12/06/2022 | By: FDS
A normal distribution is a continuous probability distribution that can be described as a symmetrical "bell"-shaped curve pattern. It is also referred to as the Gaussian normal distribution or Gaussian distribution. It is the most commonly used distribution in statistics. In a normal distribution, the values are arranged so that the average values are in the middle and the extreme values are at the edge.
12/06/2022 | By: FDS
A confidence interval is an interval that bounds an estimate of an unknown quantity. It gives a probability that the unknown quantity lies within the confidence interval. Confidence intervals are a common tool in statistics for making an estimate of an unknown quantity. They are often used to assess the accuracy of the estimate and to make predictions about a specified population.
12/06/2022 | By: FDS
The chi-square test (also chi-square test or chi-square test) is a statistical test used to test hypotheses about the independence of two characteristics. It is often used to test the significance of an observational or experimental data analysis. The chi-square test is used to find out whether a particular set of observations or measurements is significantly different from the expected value. The test is based on comparing the empirical probabilities of a particular outcome with the theoretical probability of the same outcome.