Quantitative Methods Questions Medium
Descriptive statistics and inferential statistics are two branches of statistics that serve different purposes in analyzing and interpreting data.
Descriptive statistics involves summarizing and describing the main features of a dataset. It focuses on organizing, presenting, and analyzing data in a way that provides a clear understanding of its characteristics. Descriptive statistics include measures such as mean, median, mode, range, standard deviation, and variance. These measures help to describe the central tendency, dispersion, and shape of the data. Descriptive statistics are primarily used to provide a snapshot of the data and to summarize its main features.
On the other hand, inferential statistics involves making inferences and drawing conclusions about a population based on a sample. It uses probability theory and sampling techniques to generalize findings from a sample to a larger population. Inferential statistics allow researchers to make predictions, test hypotheses, and determine the significance of relationships or differences between variables. It involves techniques such as hypothesis testing, confidence intervals, and regression analysis. Inferential statistics are used to make broader statements about a population based on the analysis of a smaller sample.
In summary, the main difference between descriptive and inferential statistics lies in their objectives. Descriptive statistics aim to summarize and describe data, while inferential statistics aim to make inferences and draw conclusions about a population based on a sample. Descriptive statistics provide a detailed overview of the data, while inferential statistics allow for generalizations and predictions beyond the observed sample.