Introductory Business Statistics is designed to meet the scope and sequence requirements of the one-semester statistics course for business, economics, and related majors. Core statistical concepts and skills have been augmented with practical business examples, scenarios, and exercises. The result is a meaningful understanding of the discipline, which will serve students in their business careers and real-world experiences.<\/p>\n
Introduction<\/p>\n
You are probably asking yourself the question, “When and where will I use statistics?” If you read any newspaper, watch television, or use the Internet, you will see statistical information. There are statistics about crime, sports, education, politics, and real estate. Typically, when you read a newspaper article or watch a television news program, you are given sample information. With this information, you may make a decision about the correctness of a statement, claim, or “fact.” Statistical methods can help you make the “best educated guess.”<\/p>\n
Since you will undoubtedly be given statistical information at some point in your life, you need to know some techniques for analyzing the information thoughtfully. Think about buying a house or managing a budget. Think about your chosen profession. The fields of economics, business, psychology, education, biology, law, computer science, police science, and early childhood development require at least one course in statistics.<\/p>\n
Included in this chapter are the basic ideas and words of probability and statistics. You will soon understand that statistics and probability work together. You will also learn how data are gathered and what “good” data can be distinguished from “bad.”<\/p>\n
1.1 | Definitions of Statistics, Probability, and Key Terms<\/p>\n
The science of statistics deals with the collection, analysis, interpretation, and presentation of data. We see and use data in our everyday lives.<\/p>\n
In this course, you will learn how to organize and summarize data. Organizing and summarizing data is called descriptive statistics. Two ways to summarize data are by graphing and by using numbers (for example, finding an average). After you have studied probability and probability distributions, you will use formal methods for drawing conclusions from “good” data. The formal methods are called inferential statistics. Statistical inference uses probability to determine how confident we can be that our conclusions are correct.<\/p>\n
Effective interpretation of data (inference) is based on good procedures for producing data and thoughtful examination of the data. You will encounter what will seem to be too many mathematical formulas for interpreting data. The goal of statistics is not to perform numerous calculations using the formulas, but to gain an understanding of your data. The calculations can be done using a calculator or a computer. The understanding must come from you. If you can thoroughly grasp the basics of statistics, you can be more confident in the decisions you make in life.<\/p>\n
Probability<\/b>\u00a0is the branch of\u00a0mathematics<\/a>\u00a0concerning numerical descriptions of how likely an\u00a0event<\/a>\u00a0is to occur, or how likely it is that a proposition is true. The probability of an event is a number between 0 and 1, where, roughly speaking, 0 indicates impossibility of the event and 1 indicates certainty. The higher the probability of an event, the more likely it is that the event will occur. A simple example is the tossing of a fair (unbiased) coin. Since the coin is fair, the two outcomes (“heads” and “tails”) are both equally probable; the probability of “heads” equals the probability of “tails”; and since no other outcomes are possible, the probability of either “heads” or “tails” is 1\/2 (which could also be written as 0.5 or 50%).<\/p>\n These concepts have been given an\u00a0axiomatic<\/a>\u00a0mathematical formalization in\u00a0probability theory<\/a>, which is used widely in\u00a0areas of study<\/a> such as statistics<\/a>,\u00a0mathematics<\/a>,\u00a0science<\/a>,\u00a0finance<\/a>,\u00a0gambling<\/a>,\u00a0artificial intelligence<\/a>,\u00a0machine learning<\/a>,\u00a0computer science<\/a>,\u00a0game theory<\/a>, and\u00a0philosophy<\/a>\u00a0to, for example, draw inferences about the expected frequency of events. Probability theory is also used to describe the underlying mechanics and regularities of\u00a0complex systems<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"