In Inferential statistics, we make an inference from a sample about the population. The main aim of inferential statistics is to draw some conclusions from the sample and generalise them for the population data. Inferential Statistics in quantitative research works in addition to Descriptive Statistics. Where descriptive statistics helps to summarise the characteristics of a sample population, inferential statistics focuses on using that summarised data and predicting the characteristics for the larger population.
What is Inferential Statistics?
Given a sample of data, an inference is made to discover unknown information related to the larger population. There are various inferential statistics in research, business and economics, like hypothesis testing, sampling, and probability. In hypothesis testing, data is collected and then a null hypothesis and an alternate hypothesis are made. For example, if a researcher wants to find out the percentage of people who consume a particular food item in their country, then the researcher will have to collect data about the number of people who consume that particular food item. The researcher will then hypothesise that, the percentage of people who consume that food item is more in that country compared to other countries.
What is Hypothesis Testing in Inferential Statistics?
Hypothesis testing is the process, where a researcher collects data from a sample from a population and then makes a null and alternate hypothesis about the population based on the sample data. The null hypothesis is, “there is no significant difference between the sampled population and the population”. Whereas, the alternate hypothesis is, “there is a significant difference between the sampled population and the population”. Let’s consider an example to understand hypothesis testing in inferential statistics better. Suppose, a researcher visits a random shopping mall and collects data about the number of people who shop at different stores in the mall. The researcher will hypothesise that the number of people who shop at a particular store in the mall is more than the number of people who shop at other stores in the mall. The researcher can then make conclusions about the mall, that all the other stores, who don’t collect such a high number of customers, have to improve their service and make their products, which are liked by the customers, more popular in the mall.
Various Statistical Tests in Inferential Statistics
There are various statistical tests available in inferential statistics. These statistical tests are used to make a conclusion about the population based on the sample data. Different statistical tests in inferential statistics are explained below. – Hypothesis Test – Null and Alternative Hypothesis – Chi-Square Test – Correlation Coefficient – Regression Line – Probability in Bayes’ Theorem – Uniform Random Sampling – External Validation Methodology – Considerations – Conclusion
Difference Between Descriptive and Inferential Statistics?
Let’s understand the difference between descriptive and inferential statistics. Firstly, descriptive statistics helps to discover unknown information related to a particular sample. It simply describes the characteristics of the sample. On the other hand, inferential statistics makes an inference about the population based on the sample data. Let’s consider an example to understand the difference between descriptive and inferential statistics. Suppose, a researcher visits a town and calls a random sample of 100 people and asks them, “What is your profession?” and “How old are you?”. The researcher simply describes the characteristics of the sample. Now, if a researcher wants to make a conclusion about the town, then inference is made from the sample data. The conclusion can be as below. “People in this town are older than average people and their profession is more than average people”. Hence, the difference between descriptive and inferential statistics is very clear in this example.
Conclusion
In short, inferential statistics uses the data collected from a sample to make conclusions about the population. It is entirely distinct from descriptive statistics, where the characteristics of the sample are described. Inferential statistics is widely used in business, economics, and other quantitative fields, whereas descriptive statistics is used in qualitative research.
