1.3 The Branches of Statistics
You can use parameters and statistics either to describe your variables or to reach conclusions about your data. These two uses define the two branches of statistics: descriptive statistics and inferential statistics.
CONCEPT The branch of statistics that focuses on collecting, summarizing, and presenting a set of data.
EXAMPLES The mean age of citizens who live in a certain geographical area, the mean length of all books about statistics, the variation in the weight of 100 boxes of cereal selected from a factory’s production line.
INTERPRETATION You are most likely to be familiar with this branch of statistics because many examples arise in everyday life. Descriptive statistics serves as the basis for analysis and discussion in fields as diverse as securities trading, the social sciences, government, the health sciences, and professional sports. Descriptive methods can seem deceptively easy to apply because they are often easily accessible in calculating and computing devices. However, this easiness does not mean that descriptive methods are without their pitfalls, as Chapter 2, “Presenting Data in Charts and Tables,” and Chapter 3, “Descriptive Statistics,” explain.
CONCEPT The branch of statistics that analyzes sample data to reach conclusions about a population.
EXAMPLE A survey that sampled 1,264 women found that 45% of those polled considered friends or family as their most trusted shopping advisers and only 7% considered advertising as their most trusted shopping adviser. By using methods discussed in Section 6.4, you can use these statistics to draw conclusions about the population of all women.
INTERPRETATION When you use inferential statistics, you start with a hypothesis and look to see whether the data are consistent with that hypothesis. This deeper level of analysis means that inferential statistical methods can be easily misapplied or misconstrued, and that many inferential methods require a calculating or computing device. (Chapters 6 through 9 discuss some of the inferential methods that you will most commonly encounter.)