A prerequisite for the Data Science Certificate Program and an elective course in the Data Analytics for Business Certificate Program.
Practical Math and Statistics are the foundation of the fields of Data Science and Predictive Analytics. Statistics are used in every part of business, science, and institutional data processing. This course covers fundamental statistical skills needed for Data Science and Predictive Analytics. This is an application-oriented course and the approach is practical. Students will take a look at several statistical techniques and discuss situations in which one would use each technique, the assumptions made by each method, how to set up the analysis, as well as how to interpret the results.
This course starts with an introduction to data analysis. Next the course covers the fundamental concepts of descriptive statistics, probability, and inferential statistics, which include the central limit theorem, and hypothesis testing. From there the course will focus on various statistical tests, including the Chi-Square test of independence, t-tests, correlation, ANOVA, linear regression, time series, and applying previously learned techniques in new situations.
NOTE: This course uses the software SPSS. Students have the option to access the software through UCI's Virtual Machine. Access to the Virtual Machine requires a UCInetID. This course may use live sessions via Zoom. While students are highly encouraged to attend, all sessions are optional and will be recorded. A device with audio and visual will be needed to participate. The following student guide provides additional resources/information on how to use and access your courses Zoom sessions.
Jesus Salcedo has a Ph.D. in Psychometrics from Fordham University. He is an independent statistical and data-mining consultant that has been using SPSS products for over 20 years. He is a former SPSS Curriculum Team Lead and Senior Education Specialist who has written numerous SPSS training courses and trained thousands of users.
Textbooks for your course may be purchased from any vendor or bookseller of your choice.
No textbook information is available for this course.
|Event||Date||Day||Start Time||End Time||Location||Room
|START||01/10/2022||Monday||---||---||Online (Access Begins)||---
|END||03/06/2022||Sunday||---||---||Online (Access Ends)||---