Elizabeth Ajazi

Elizabeth Ajazi
  • Lecturer in Statistics and Data Science

Contact Information

  • office Address:

    Academic Research Building
    265 South 37th Street
    Philadelphia, PA 19104

Teaching

Current Courses

  • STAT1110 - Introductory Statistics

    Introduction to concepts in probability. Basic statistical inference procedures of estimation, confidence intervals and hypothesis testing directed towards applications in science and medicine. The use of the JMP statistical package. Knowledge of high school algebra is required for this course.

    STAT1110001 ( Syllabus )

    STAT1110002 ( Syllabus )

    STAT1110201 ( Syllabus )

    STAT1110202 ( Syllabus )

    STAT1110203 ( Syllabus )

    STAT1110204 ( Syllabus )

    STAT1110205 ( Syllabus )

    STAT1110206 ( Syllabus )

    STAT1110207 ( Syllabus )

    STAT1110208 ( Syllabus )

Past Courses

  • STAT0002 - Intro To Stat & Data Sci

    Continuation of STAT 0001. In this course, we will learn basic statistical inference procedures of estimation, confidence intervals, and hypothesis testing. We will also cover statistical inference of bivariate data, including correlation and simple linear regression models. Prerequisite: STAT 0001 or equivalent coursework. Basic R knowledge.

  • STAT1020 - Intro Business Stat

    Continuation of STAT 1010 or STAT 1018. A thorough treatment of multiple regression, model selection, analysis of variance, linear logistic regression; introduction to time series. Business applications. This course may be taken concurrently with the prerequisite with instructor permission.

  • STAT1110 - Introductory Statistics

    Introduction to concepts in probability. Basic statistical inference procedures of estimation, confidence intervals and hypothesis testing directed towards applications in science and medicine. The use of the JMP statistical package. Knowledge of high school algebra is required for this course.

  • STAT1120 - Introductory Statistics

    Further development of the material in STAT 1110, in particular the analysis of variance, multiple regression, non-parametric procedures and the analysis of categorical data. Data analysis via statistical packages. This course may be taken concurrently with the prerequisite with instructor permission.

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Five Myths About Generative AI That Leaders Should Know

Experts from Wharton and the “Magnificent Seven” tech companies debunk five misconceptions about gen AI that could stand in the way of implementation.…Read More

Knowledge @ Wharton - 2024/04/30
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