**Statistics** being the scientific and systematic methods dealing with numerical facts is broadly categorized into two types depending on how data is handled.

The two main categories of statistics are **descriptive and inferential statistics.**

**Descriptive statistics**

this deals with recording, summarizing, analyzing and presentation of numerical facts that have been actually collected.

Descriptive statistics is the term given to the analysis of **data** that helps describe, show or summarize data in a meaningful way such that, for example, patterns might emerge from the data.

Descriptive statistics do not, however, allow us to make conclusions beyond the data we have analyzed or reach conclusions regarding any hypotheses we might have made.

They are simply a way to describe our data. Descriptive statistics are very important because if we simply presented our raw data it would be hard to visualize what the data was showing, especially if there was a lot of it.

Descriptive statistics, therefore, enables us to present the data in a more meaningful way, which allows a simpler interpretation of the data.

For example, if we had the results of 100 pieces of students’ coursework, we may be interested in the overall performance of those students.

We would also be interested in the distribution or spread of the marks. Descriptive statistics allow us to do this.

Typically, there are two general types of statistics that are used to describe data they are a **measure of central tendency** and** measure of spread**

**Inferential statistics**

this makes inferences about populations using data drawn from the **population**.

Instead of using the entire population to gather the data, the statistician will collect a **sample** or samples from the millions of residents and make inferences about the entire population using the sample.

With inferential statistics, you are trying to reach conclusions that extend beyond the immediate data alone.

For instance, we use inferential statistics to try to infer from the sample data what the population might think.

Or, we use inferential statistics to make judgments of the probability that an observed difference between groups is a dependable one or one that might have happened by chance in this study.

Thus, we use inferential statistics to make inferences from our data to more general conditions; we use descriptive statistics simply to describe what’s going on in our data.

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