Descriptive statistics are statistics that describe the central tendency of the data, such as mean, median and mode averages. Variance in data, also known as a dispersion of the set of values, is another example of a descriptive statistics. Greater variance occurs when scores are more spread out from the mean. Descriptive statistics summarize data.
There are two main types of statistics: descriptive and inferential. While descriptive statistics summarize the data, inferential statistics make generalizations about a population from a sample. Several calculations are used to generate inferential statistics, including the t-test and Chi-square, which give information about the probability of the results actually representing the population. These are also known as tests of significance and help researchers determine if the data they obtain is a result of mere chance or if there is an actual relationship between the variables involved. Other tests that generate inferential statistics include linear and logistic regression analysis, ANOVA, correlation analysis, survival modeling and structural equation analysis. Both descriptive and inferential statistics are used to describe populations and samples. A population is the entire set of individuals or objects the researcher is studying. A sample is a smaller group within the population that is studied to make inferences about the larger population.