EDS 8823 Representation and Analysis of Quantitative Data

This course focuses on: (1) describing and summarizing data; (2) creating and interpreting standard scores, and; (3) using inferential statistics to make decisions. Students will be introduced to these quantitative procedures using the SPSS software. The skills developed in this course are a prerequisite to understanding educational research.

Credits

3

Student Learning Outcomes

Upon successful completion of this course, the candidate will be able to:

1. Differentiate between descriptive and inferential statistics to understand appropriate application of data to educational practices
2. Define the four levels of measurement in quantitative data
3. Explain how levels of measurement connects to which hypothesis test we conduct to build aligned research studies for use in applied educational settings
4. Evaluate the appropriate fit between data and statistical analysis approach to learn how to conduct trustworthy analyses and to be able to evaluate when other analyses are trustworthy enough to use in applied practice
5. Describe characteristics of quantitative data using appropriate statistical tools like central tendency and measures of dispersion
6. Perform several hypothesis tests in SPSS and understand the logic differentiating these tests
7. Understand the normal distribution and probability in the context of the normal distribution to make an appropriate differentiation between what we can say about a sample vs. a population (e.g., a classroom vs. a school)
8. Work with quantitative data to understand data patterns and build useful summaries for outside audiences