Why statistics are important
It is beneficial to know and use statistics. Statistics are everywhere. Think about the news stories you have heard or read today. How many of them referenced statistical results? Did you understand the meaning or context of that statistic? It is easy to accept the statistics that you hear in the news. You might become more skeptical of a statistic, however, if you need it to make a decision that impacts you or your family's welfare. For example, imagine you are faced with a decision about whether or not to take a drug based on the statistical results of a clinical trial. Would you feel comfortable making a decision without asking questions about the statistical results? What questions would you ask? One of the themes of this course is that you need to become a shrewd consumer of statistics—and know which questions you need to ask before you act on a statistic.
This course focuses on how to use statistics and how to apply them to real-world situations. It is important to understand the various concepts in statistics and to know how they are used in business, as well as in personal situations. Upon finishing this course, you may find that your outlook on the real world has changed. Instead of accepting what you see, you may start to ask questions and look for solutions to various situations in your world. For example, understanding a stock's behavior in the past can help predict its future behavior. Or suppose a human resources manager at a large manufacturer decides to test applicants for a job but then interviews only applicants who score in the top 10%. How should the manager determine the cut-off score?
Do you have to be a math wiz to take this course? It is worth drawing an important distinction between this course and other typical introductory statistics courses. This course focuses on the interpretation of statistical results. In order to evaluate statistical results, it is necessary to have an understanding of the underlying calculations. Thus, this course will require some calculations; however, they will be in the context of statistical reasoning.
The median is a term used to summarize a set of data. For example, you have likely heard median house prices or median salaries discussed in the news. Think for a moment about the benefits of providing a summary instead of the full data set. If you did not have a summary, what conclusions could you draw from the full data set? How difficult would it be? If you were given two lengthy data sets, how would you compare them?
Here are some other terms and concepts you will apply in this assessment:
Measures of central tendency—Like the median or average, measures of central tendency are used to facilitate data analysis and to allow a common understanding of the data.
Measures of variation—Measures of variation include range, variance, and standard deviation. In conjunction with the measures of central tendency, this provides a full description of data.