Statistical analysis is a constituent of data logic, a science of inference and reasoning. In the context of BI, statistical analysis involves gathering and scrutinizing every data sample in a set of items from which example can be drawn. An example, in statistics, is a representative collection drawn from a total population. Statistician accumulates data via particular experiments propose and appraisal illustration. An experimental study including measurement of the system of the study, manipulating the system, and then taking the additional part of contrast, an analytical statistic does not involve experimental manipulation. To know the types of statistical analysis, get help from dissertation writing services.

**TWO CATEGORIES OF STATISTICAL ANALYSIS**

**Descriptive**: Descriptive analysis helps in summarizing the available data, it also analyse the structure and distribution of either or the entire data.

**Inferential**; inferential analysis is used to deduce some insights from the data that are not apparently visible. It can be used to make judgments and infer insights from the data.

Now we will look at various types of analysis within each of these categories with the help of an example. Let’s say Sana is a math teacher and teaches a class of 40 students. She wants to analyze the test scores of her students. We will see what types of statistical analysis techniques she can use.

** TYPES OF STATISTICAL ANALYSIS**

** Measures of central tendency**: Measures of central tendency are a type of statistical analysis that is used to represent the central cluster and the typical scenario presented by the data

** Median: **Median is another type of statistical analysis that is used to arrange the data points in ascending order and then taking the middle number. The average taken by the two middle numbers.

** MEAN:** Mean represents the average of data points, also calculates by dividing the sum of all the data points by the number of data points.

**MODE**; mode is another type that represents the frequency occurring to data points in the sample of data. For example, Ali finds out four students scored a perfect 100, and this was the most frequently occurring score. In this case, 100 is the mode.

**Measures of dispersion**: This is a most useful type of statistical analysis that is used to explain how far apart the data points are spread. The most commonly used type of statistical analysis is the standard deviation.

**Standard deviation**: It is the most standard type of statistical analysis that is used to measure data in our thesis research. Calculating standard deviation starts by taking the difference of each data point from the mean, squaring them, then adding them. At the last, we may wind a number of data points and then taking the square root. If that became tough to calculate, we may use computer software to calculate the standard deviation. This type is very useful in a normal distribution. With the big data sets, statistics primary analyses have no other choice.