Presentation of key concepts for understanding and judging reports of statistical analyses and for performing and reporting valid statistical analyses using a limited set of measures and tests.
This course will cover descriptive statistics, correlation and simple linear regression, and inferential statistics when comparing two means. We will also be learning and using Microsoft Excel to aid in statistical analysis.
The overarching goal of this course will be to develop students' statistical literacy, reasoning, and thinking: "Statistical literacy involves understanding and using the basic language and tools of statistics: knowing what statistical terms mean, understanding the use of statistical symbols, and recognizing and being able to interpret representations of data. Statistical reasoning is the way people reason with statistical ideas and make sense of statistical information. Statistical reasoning may involve connecting one concept to another (e.g., center and spread) or may combine ideas about data and chance. Reasoning means understanding and being able to explain statistical processes, and being able to fully interpret statistical results. Statistical thinking involves an understanding of why and how statistical investigations are conducted. This includes recognizing and understanding the entire investigative process (from question posing to data collection to choosing analyses to testing assumptions, etc.), understanding how models are used to simulate random phenomena, understanding how data are produced to estimate probabilities, recognizing how, when, and why existing inferential tools can be used, and being able to understand and utilize the context of a problem to plan and evaluate investigations and to draw conclusions."
Student learning goals
Students will be able to calculate common descriptive statistics such as mean, median, and related measures of spread, and interpret the meanings of these numbers in context.
Students will be able to calculate and interpret Pearson correlation coefficients and a simple linear regression models.
Students will understand the reasoning behind inferential statistics and perform a independent samples t-test comparing two means.
Students will be able to read statistical reports and effectively communicate (both written and oraly) results of quantitative data.
Students will know how and when to use Microsoft Excel to calculate statistics for data sets.
General method of instruction
Lecture, hands-on activities, labs, and small group problem solving.
There are no formal prerequisites for this class. However, we move through that statistical content quickly. So, BIS232 or a solid background in college algebra is recommended.
Class assignments and grading
Grading will be based on a combination of homework, exams, labs, and projects.