Descriptive Statistics:
The purpose of a descriptive statistic is to describe the data. Descriptive statistics summarize the data in terms of its central tendency, variability, or spread. A good example would be the average age of an individual in a population.
Inferential Statistics:
An inference is made from the summary of the data. The inference is based on statistical techniques that can apply to make predictions about future observations. For instance, if we know the mean age of individuals in a population, we can predict what percentage of people will be over 65 years old. It is called inferential statistics.
Common tools of descriptive statistics
Mean, median, mode, range, standard deviation, variance, skewness, kurtosis, quartiles, interquartile ranges, frequency distribution, histogram, box plot, normal curve, etc.
Frequency Asked Questions
What are the differences between descriptive and inferential?
Descriptive vs. Inferential Statistics
How do you determine whether your data is normally distributed?
A: This is a good question. You need more information than just looking at the graph to tell if the data are from a normal distribution. The most common way to test for normality is with the Shapiro-Wilk test. If the p-value is greater than 0.05, it is assumed that the data follow a normal distribution.