Chapter 6 Wrap Up
This chapter introduced statistics and how it is taught in the elementary classroom. It also addressed the importance of being able to read and analyze data, including asking critical questions as to not be misled by data that are presented with bias. Different ways to represent data were explored as well as measures of central tendency and implications thereof. This is just the beginning of the very complex field of statistics but provides a basis of understanding data and how they are presented. In middle school, students expand on these topics as well as study the spread of data and corresponding graphical representations (for example so called “box and whisker plots”). This all provides a foundation to understanding data and how they can provide valuable information (or potentially harmful misinformation). Statistics are used absolutely everywhere in today’s society and are more important than ever for students to understand.
For material on Measuring the Spread of Data see p. 181 – 182, 187 – 196 in Big Ideas in Geometry and Data Analysis (see link in Back Matter – OER Resources)
A value calculated using data from a sample.
A sample is biased if members of the population do not have equal likelihood of being in the sample.
Types of bias include:
Sampling bias: when the sample is not representative of the population
Voluntary response bias: the sampling bias that often occurs when the sample is volunteers
Self-interest bias: bias that can occur when the researchers and/or participants have an interest in the outcome
Response bias: when the responder gives inaccurate responses for any reason
Perceived lack of anonymity: when the responder fears giving an honest answer might negatively affect them
Loaded question bias: when the question wording influences the responses
Non-response bias: when people refusing to participate in the study can influence the validity of the outcome
