Probability and statistical thinking

This is a tentative schedule that may be changed based on the needs of the students, the needs of the instructor, or any apocalyptic events that may occur during the semester.

1:

Mon/Tues

Class preparation

  • n/a

Agenda: Introductions

  1. make seating chart
  2. introductions and discuss Day 1 handout
  3. Q&A

Extra practice

Wed/Thurs

Class preparation

Agenda: How do experiments lead to probability?

  1. teams need: online dice roller or 2d6 in different colors, d4, d8; Roller derby board
  2. notation for probability
    P(event) = (# event)/(total # outcomes)
  3. Law of large numbers: As number of trials increase, the closer the experimental probability reflects the actual (theoretical) probability (Excel)

Extra practice

2:

Mon/Tues

Class preparation

Agenda: How can we determine probability without experiments?

  1. compare Monte Carlo simulation using Excel
  2. represent sample space for 2d6 using: list, grid, tree diagram; then compute theoretical probabilities
  3. compute theoretical probabilities for 2d4 using a sample space (hint: P(5) = 1/4)
  4. group work: CA 16F, CA 16G

Extra practice

  • try next problem on WeBWorK homework
  • 16.1 problems: 1 (3/8, 4/8, 6/8), 2 (various, 5/12, various)
  • Read Chapter 16.2
  • Supplemental Instructor's extra practice

Wed/Thurs

Class preparation

Agenda: How can tree diagrams be used in different contexts?

  1. formative quiz (~10 mins)
  2. discuss: CA 16G.2
  3. introduce weighted tree diagrams for compound probabilities

Reminder: Next class online using Zoom

Extra practice

  • try next problem on WeBWorK homework
  • Chapter 16.2 practice exercises: 1, 2
  • 16.2 practice exercises: 4
  • 16.3 problems: 5 (9/16), 6 (1/64)
  • Supplemental Instructor's extra practice

3:

Mon/Tues

Class preparation

discuss expectations for online classes

Agenda: How can two-way tables be used to compute probabilities?

  1. two-way frequency tables with experimental data
  2. two-way frequency tables with theoretical data

Extra practice

Wed/Thurs

Class preparation

Agenda: How do values influence probability situations?

  1. formative quiz (~10 mins)
  2. expected value = value1 * probability1 + value2 * probability2 + …
  3. use expected value to analyze fair games

Extra practice

4:

Mon/Tues

Class preparation

Agenda: How do values influence probability situations? (continued)

  1. finish fair games
  2. CA 16K (expected earnings: ~29 prizes, $92-$93)
  3. if time, challenge problems on fair games

Discuss online version of graded quiz & virtual review sessions with SI

Extra practice

Wed/Thurs

Class preparation

  • if needed, email instructor to request online version of graded quiz (strict time limit, available before class, due before end of class)
  • try spinners

Agenda: What are examples of probability misconceptions?

  1. groups: CA 16B (probability misconceptions), CA 16J (more probability misconceptions)
  2. graded quiz (last 20 mins)

Extra practice

5:

Mon/Tues

Class preparation

  • read Chapter 9.5
  • (optional) answer the "off topic" question in this week's discussion board

Discuss graded quiz

Agenda: How can story problems be modeled different ways?

  1. CA 9U (strip diagrams and algebra)

Note: Last Zoom class

Extra practice

Wed/Thurs

Class preparation

  • try next problem on CA 9U

Agenda: How can story problems be modeled different ways? (continued)

  1. formative quiz (~10 mins)
  2. continue CA 9U (strip diagrams and algebra)

Extra practice

6:

Mon/Tues

Class preparation

Agenda: How can (polynomial) formulas be developed from tables?

  1. create functions from tables (tutorial)

Extra practice

Wed/Thurs

Class preparation

  • if needed, email instructor to request online version of graded quiz (strict time limit, available before class, due before end of class)
  • try next problem on functions from tables

Agenda: How can linear equations be identified?

  1. finish functions from tables (tutorial)
  2. graded quiz (last 20 mins)

Extra practice

7:

Mon/Tues

Class preparation

  • start note sheet for exam (1-sided, handwritten)
  • (optional) answer the "off topic" question in this week's discussion board

Schedule reminders: SI review, drop-in, next week

Agenda: Review

  1. review topics
  2. creating practice problems

Extra practice

Wed/Thurs

Class preparation

  • if needed, email instructor to request online version of Exam I (strict time limit, available during class time)
  • finish note sheet for exam (1-sided, handwritten)
  • check batteries in calculator ;-)

Agenda: Exam I

  1. approved calculators allowed
  2. one pages notes (1-sided, handwritten)
  3. manipulatives

Extra practice

8:

Mon/Tues

Class preparation

  • n/a

Agenda: Exam I make-ups

  1. No class except for make-up exams (sign-up required).

Extra practice

Wed/Thurs

Class preparation

  • n/a

Agenda: Return exam

  1. Exams will be return and discussed

Extra practice

9:

Mon/Tues

Class preparation

  • Read Chapter 15.2: Displaying Data and Interpreting Data Displays
  • (optional) answer the "off topic" question in this week's discussion board

Agenda: How can data be displayed different ways?

  1. revisit first class
  2. types of displays: pictographs, dot plot, bar graph, pie chart, histogram, steam-and-leaf, line graph, scatterplot
  3. CA 15E (data display errors)

Extra practice

Wed/Thurs

Class preparation

  • Read Chapter 15.3: The Center of Data: Mean, Median, and Mode

Agenda: How can we measure the "center" of data?

  1. formative quiz (~10 mins)
    "note sheet" (1 page, 1 sided, handwritten) now allowed on all quizzes!
  2. arithmetic mean with leveling: CA 15K, CA 15L

Extra practice

  • try next problem on WeBWorK homework
  • Supplemental Instructor's extra practice
  • Chapter 15.3 practice exercises: 1, 2, 3
  • Chapter 15.3 problems: 3 (32), 4 ($83,333)

10:

Mon/Tues

Class preparation

Agenda: How can we measure variability of data? (IQR)

  1. formative quiz (~10 mins)
  2. review preparation activities
  3. define quartiles (exclusive), five-number summary, IQR
  4. CA 15T

Extra practice

Wed/Thurs

Class preparation

  • if needed, email instructor to request online version of graded quiz (strict time limit, available before class, due before end of class)
  • finish CA 15T
  • read Chapter 15.4 Summarizing Distributions with Median and Interquartile Range and with Box Plots

Agenda: How can we measure variability of data? (box plots and outliers)

  1. definitions: mode, bimodal, multimodal, outliers, and box plots
  2. CA 15U (box plots)
  3. graded quiz (last 20 mins)

Extra practice

11:

Mon/Tues

Class preparation

  • finish CA 15U
  • Read Chapter 15.4 "Summarizing distributions with mean and MAD"
  • (optional) answer the "off topic" question in this week's discussion board

Agenda: How can we measure variability of data? (MAD)

  1. discuss graded quiz
  2. CA 15W (compute MAD)
  3. stats variability practice (mean, IQR, MAD)

Extra practice

Wed/Thurs

Class preparation

  • n/a

Agenda: How can we measure variability of data? (var, SD)

  1. formative quiz (~10 mins)
  2. stats variability practice (var, SD)
  3. CA 15W (compute variance, standard deviation)

Extra practice

12:

Mon/Tues

Class preparation

  • Read Chapter 15.4 "Normal curves and standardized test results"

Agenda: How can we compare different scores? (normal distribution)

  1. formative quiz (~10 mins)
  2. introduce normal distribution (see student sample)

Extra practice

Wed

Class cancelled for Math Retreat

Thurs

Class preparation

Agenda: How can we compare different scores? (z-scores)

  1. formative quiz (~10 mins)
  2. introduce standard scores (aka. z-scores)
  3. start scatterplots

Extra practice

13:

Mon

Class preparation

Agenda: How can we compare different scores? (z-scores)

  1. formative quiz (~10 mins)
  2. introduce standard scores (aka. z-scores)
  3. start scatterplots

Extra practice

Tues/Wed

Class preparation

  • if needed, email instructor to request online version of graded quiz (strict time limit, available before class, due before end of class)

Agenda: How can we analyze bivariate data?

  1. introduce quartile-quartile lines (with linear review)
  2. graded quiz (last 20 mins)

Extra practice

Thursday

Class cancelled for "wellness" day

14:

Mon/Tues

Class preparation

  • prepare for final exam

Agenda: Review

  1. discuss graded quiz
  2. discuss take-home part of final
  3. sequels practice

Extra practice

Wed/Thurs

Class preparation

  • prepare for final exam

Agenda: Review

  1. formative quiz (~10 mins)
  2. Review topics
  3. Q&A

Extra practice

Final exam