Everyday we are faced with oceans of facts and figures. It is impossible to consider each fact individually, so we use “statistics” to describe, or summarize numbers, group them according to characteristics and compare with other groups. For an undergraduate dental student, sometimes understanding and interpreting data becomes a tedious job without having the knowledge of biostatistics. This chapter aims to provide an understanding of statistical methods, how to collect, present and summarize data, this is called descriptive statistics. In addition, patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations, and then used to draw inferences about the process or the population being studied; this is called inferential statistics. These inferences may take the form of hypothesis testing (tests of significance), estimation, correlation, regression. Both descriptive and inferential statistics comprise applied statistics. For practical reasons, rather than compiling data about an entire population, one instead usually studies a sample—a chosen subset of the population. If the sample is representative of the population, then inferences and conclusions made from the sample can be extended to the population as a whole.