Question

Explain, in detail, the difference between descriptive and inferential statistics utilizing several examples. What purpose do they serve? How are they different? How are they complimentary?

Answer 1

Descriptive statistics helps to describe the characteristics of a population with the help of tables, calculation or graphs whereas, inferential statistics helps us to make inferences about a population. It helps in predicting about a population on the basis of the sample taken from the same population.

So, descriptive statistics helps to describe the sample population using mean, standard deviation, making a bar chart or describing the shape of the normal probability curve. Inferential statistics are used for two purposes: 1) to estimate parameters, i.e. taking a statistics from the sample population and using it to say or make a prediction about the population parameter. 2) To test hypotheses. In order to answer research questions, inferential statistics is important. One can use the sample data to test and answer various research questions using inferential statistics. T-distributions, regression analysis, ANOVA, MANOVA etc are some examples of inferential statistics.

The main difference between inferential statistics and descriptive statistics is that descriptive statistics describes the population using a sample data, whereas, inferential statistics helps in drawing conclusion about a population using a sample data.

The way how descriptive statistics and inferential statistics are complementary is that descriptive statistics helps to present the raw data in an accurate way, while inferential statistics makes inferences from a data sample and helps in generalizing it to a bigger population. Both, inferential and descriptive statistics are very important to research.