Exam 01 review

Prof. Maria Tackett

Oct 02, 2023

Announcements

  • HW 02 due TODAY at 11:59pm.
  • All lecture recordings available until Wed, Oct 4 at 9am.
    • Click here for link to videos. You can also find the link in the navigation bar of the course website.
  • No labs this week
  • No office hours Wednesday - Friday
  • Ed Discussion archived (no new posts) Wednesday - Friday

Exam 01

  • 15% of final course grade

  • 50 points total

    • in-class: 40 points
    • take-home: 10 points
  • In-class: 75 minutes during Wed, Oct 4 lecture

  • Take-home:

    • Released: Wed, Oct 4 ~ 3pm
    • Due: Fri, Oct 6 at 11:59pm
    • Similar in format to a lab/ HW
  • If you miss any part of the exam for an excused absence (with academic dean’s note), then Exam 02 score will be counted twice

Content: Weeks 1 - 5

  • Exploratory data analysis

  • Fitting and interpreting simple linear regression models

  • Statistical models and regression equations

  • Simulation-based inference

  • Mathematical models for inference

  • Prediction

  • Model conditions

  • Model evaluation

  • Basics of multiple linear regression

Outline of in-class portion

  • Closed-book, closed-note.

  • 10 questions, some with multiple parts

  • Question types:

    • Multiple choice
    • Short answer (no more than 3 sentences)
    • True/ False.
      • If false, write 1 - 2 sentence justification about why it is false.
    • Evaluate a response.
  • Last page (front and back) will have analysis output.

  • Just need a pencil. No calculator permitted on exam.

Application exercise

📋 sta210-fa23.netlify.app/ae/ae-08-exam-01-review

  • Sit with your lab group.

  • Put your group’s response to your assigned exercise on Ed Discussion.

    • Section 001: edstem.org/us/courses/44523/discussion/3542094

    • Section 002: edstem.org/us/courses/44523/discussion/3542095

🔗 STA 210 - Fall 2023 - Schedule

Exam 01 review Prof. Maria Tackett Oct 02, 2023

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  • Exam 01 review
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  • Exam 01
  • Content: Weeks 1 - 5
  • Outline of in-class portion
  • Application exercise
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