/Quant-Bio-VT

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README

Kate Langwig

GitHub Documents

This repository contains the course documents for Quantitative Methods in Ecology and Evolution. The files you'll need are given week by week.

Week 1

Tuesday:

lecture: lectures/le1_intro_to_R.pptx

code: le_1_intro_to_R.R

old video:week_1_tues_lecture

Thursday:

lecture: ex1_intro_to_R.pptx

code: ex1_intro_to_R.R

old video: week_2_thus_lecture

Task list for next week:

Week 2

Tuesday:

lecture: le_2_managing_data

code: le2_data_manipulation.R

old video: week_2_tues_lecture

Thursday:

lecture: ex2_data_manipulation.pptx

code: use code from Tuesday for example

Task list for next week:
  • Make sure that data is clean!
  • Complete Week 2 assignment, make sure to turn in code from Week 1 too

Week 3

Tuesday:

lecture: le3_data_visualization

code: le3_data_visualization.R

old video: week_3_tues_lecture

Thursday:

lecture: ex3_data_manipulation.pptx

code: use code from Tuesday for example

old video: week_3_thursday_lecture

Task list for next week:
  • Submit Week 3 assignment
  • Reading and discussion for next Thurs
  • Start thinking about those bad ggplot2s for the end of the semester!

Week 4

Tuesday:

lecture: le4_statistical_philosphy

code: code just to make examples in lecture - none assigned

old video: week_4_tues_lecture

Thursday:

Task List for Next Week
  • Ensure you are caught up on assignments and data is clean!

Week 5

Tuesday:

lecture: le_5_tests.pptx

code: ex5_tests

old video: week_5_tues_lecture

Thursday:

code: ex5_tests

Task List for Next Week
  • Complete Week 5 assignment

Week 6

Tuesday:

lecture: le6_rev_distributions.pptx

code: ex6_rev_distributions.R

handout: Handout_Week6_Distributions

Thursday:

  • Problem set solutions; distribution fitting (no assignment)

  • lecture & solutions : ex6_solutions.pptx

  • code: ex6_rev_distributions.R / ex6_rev_solutions.R

Task List for Next Week:

Week 7

Tuesday:

Thursday: No class

  • Use this time to:

  • (1) Make sure you have read Week6_Distributions_Bolker_chap4A.pdf

  • (2) Take the distributions quiz

  • (3) Catch up on other assigned reading

Task List for Next Week:
  • None! Enjoy Spring Break.

Week 8

Tuesday:

lecture: le_7_linear_models

  • Lecture will be recorded in advance. No in person class.

code: ex7_linear_models

pre-recorded video: week_6_tuesday_lecture

Thursday:

lecture: ex7_assignment

code: use code from Tuesday

Task List for Next Week:
  • Work on part 1 of linear models assignment. Due date is in two weeks.
  • Keep bad ggplot2 in mind here. Lots of potential this week!

Week 9

Tuesday:

lecture: le8_Linear_model_parameters

code: ex8_linear_model_parameters

video: advanced_linear_models

Thursday:

lecture: le8_Linear_model_parameters (last slide has assignment)

code: use code from Tuesday

video: mini_lecture_advanced_models

Task List for Next Week:
  • Hand in linear models (part 1 & 2).
  • Start thinking about final project
  • Any bad ggplots2?

Week 10

Tuesday:

lecture: le10_glms.pptx

code: ex10_glms.R

datasets: bat_data.csv; lizards.csv

old video: week_10_tues_lec_glms

Thursday:

lecture: ex10_glm_assignment.pptx

code: use code from Tuesday

old video: week_10_thurs_lecture

Task List for Next Week:

Week 11

Tuesday:

lecture: le111_model_selection.pptx

code: ex11_model_comparison.R

reading: Week11_Bolker et al ms information theoretic.pdf

old video: week_11_tues_model_comparison

Thursday:

lecture: le11_assignment.pptx

code: Use code from Tuesday

Task List for Next Week:
  • Hand in 10 & 11 assignment.
  • Work on project results section, outline text in all sections
  • Vote on extended projects
  • Any bad ggplots2?

Week 12

Tuesday:

lecture: le12_mixed_models.pptx

code: ex12_mixed_models.R

reading: Week12_Bolker 2008 TREE.pdf

old video: week12_tues_lecture_mixed_models

Thursday:

lecture: assignment at end of Tuesday lecture

code: use same as Tuesday for example

old video: week_12_thurs_lecture_mixed_models

Task List for Next Week:
  • Hand in Week 12 assignment.
  • Final project: Finish graphs and analyses and draft abstract
  • Do you have final project questions for Kate? Share those with her next week!
  • Any bad ggplots2?

Week 13

Extended topics week!

Tues: Extended Topics

lecture:

  • le13_advanced_models_combined.pptx

code:

zero-inflated models

  • ex_zero_inflated_models.R

power analyses

  • ex_power_analyses.R

time-series models

  • ex_time_series_models.R

non-linear models (mainly least squares examples)

  • ex_nls_models

phylogenetic models using gls

  • ex_phylogenetic_gls_models

Thurs

  • Project Assistance
Task List for Next Week:
  • Finalize content for final project for peer review
  • Reach out to Kate for feedback if needed

Week 14

Tues: Extended Topics

lecture:

  • le13_advanced_models_combined.pptx

code:

  • see previous week

Thurs: PEER REVIEW

  • have assignment turned in for peer review!
  • finalize peer review comments by Friday evening
Task List for Next Week:
  • Integrate comments from peer review
  • finalize draft
  • Last chance for bad ggplots!

Week 15

Tues

  • Bad ggplots contest!
  • You should have previously submitted some of your worst plots of the semester
  • Bonus points and prizes will be awarded
Task List for THIS Week:
  • Hand in final project on Wed!