Universidad Católica de Valencia
Area of Study
Business, Mathematics, Statistics
Taught In English
Recommended U.S. Semester Credits0
Recommended U.S. Quarter Units0
Hours & Credits
a. Knowing the tools of inferential statistics: point estimate, confidence estimation and hypothesis testing, its usefulness, limitations and interpretation.
b. Knowing the ANOVA method, its rationale, its implementation, its limitations and its interpretation.
c. Generalize linear regression models for dealing with multiple variables, binary variables, nonlinear relationships, interaction, ...
d. Develop students' critical thinking when it comes to making a decision based on a random sample from a population of interest.
e. Accustom the students to use information technology (spreadsheet or statistical software).
f. Being able to formulate hypotheses, collect and critically evaluate information for problem solving using the scientific method
Statistical Inference is a logical continuation to the descriptive statistics coursed in the previous year. In this course we study the problem of trying to draw valid conclusions, with a margin of error small and known, for a population, from a representative sample. With this module, students achieve the homogenization of knowledge in basic science to further promote the transfer of credits between qualifications.
Courses and course hours of instruction are subject to change.
Eligibility for courses may be subject to a placement exam and/or pre-requisites.
ECTS (European Credit Transfer and Accumulation System) credits are converted to semester credits/quarter units differently among U.S. universities. Students should confirm the conversion scale used at their home university when determining credit transfer.