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Local Bindings

Sept 25 th , 2019. Local Bindings. Agenda. Preliminaries (8:30-8:35) Exam 1 Cover Sheets (8:35-8:45) Quiz Topics (8:45-8:50) Readings Discussion (8:50-9:05) Lab Time (9:05-9:45) Wrap-up (9:45-9:50). Preliminaries (8:30-8:35). Peer Support Events:

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Local Bindings

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  1. Sept 25th, 2019 Local Bindings

  2. Agenda • Preliminaries (8:30-8:35) • Exam 1 Cover Sheets (8:35-8:45) • Quiz Topics (8:45-8:50) • Readings Discussion (8:50-9:05) • Lab Time (9:05-9:45) • Wrap-up (9:45-9:50)

  3. Preliminaries (8:30-8:35) • Peer Support Events: • Choir concert Saturday 7:30pm Sebring Hall • Upcoming Work: • Monday’s lab due tonight at 10:30pm • Read for Friday • Today’s lab due Friday at 10:30pm • Assignment 4 due Tuesday at 10:30pm • Exam epilogue tonight at 10:30pm

  4. Exam 1 Cover Sheets (8:35-8:45) • Take a blank piece of paper • Write your name and secret ID on the paper • Write these two academic honesty statements: • I have neither received nor given inappropriate assistance on this exam • I am not aware of any other students who have given or received inappropriate assistance on this exam • For each statement: • If the statement is true, sign your name below the statement and write today’s date • If you can’t sign, please schedule an appointment to talk to me ASAP • Bring your cover sheet to the front of the class

  5. Quiz Topics (8:45-8:50) • Boolean Values • #t and #f • Writing and Using Predicate Procedures • and or not positive? even? conjoin disjoin exact? negative? • Filtering Lists • Output of assoc • Show the output of a list filter expression • Write scheme code to filter a list with a complex predicate

  6. How to be a good programming partner • Don’t work on the assignment without your partner • If you two are struggling to make progress, make an appointment with me • Make sure your partner understands what you have typed • If your partner says they understand, believe them

  7. Readings Discussion (8:50-9:05) • Think-pair-share: • What is data science? • Science of manipulating and interpreting data • Similar to statistics, take in data and interpret it • Try to find the golden nugget, lots of data out there, find what is actually valuable • Ethical manner important • What are the major steps in doing data science? • Ethical considerations, collecting, Wrangling, merging, cleaning, filtering, processing, analyzing, visualizing

  8. Readings Discussion (8:50-9:05) • Think-pair-share: what do the following expressions result in? • (let ([x 1] [y 2]) (+ x y)) • 3 • (let ([x 1]) • (let ([x 2] [y (* 2 x)]) • (+ x y))) • 4 • (let ([x 1]) (let* ([x 2] [y (* 2 x)]) (+ x y))) • 6

  9. Lab Time (9:05-9:45) • Person closest to the back starts as driver

  10. Wrap-up (9:45-9:50) • Lab writeup: Exercise 2 both parts • Upcoming Work reminders: • Monday’s lab due tonight at 10:30pm • Read for Friday • Today’s lab due Friday at 10:30pm • Assignment 4 due Tuesday at 10:30pm

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