Spring 2020 – Math 58 & 58B HW

Spring 2020 Math 58 & 58B HW Schedule

Introduction to Statistics / Biostatistics

Math 58 & 58B, Spring 2020

Jo Hardin
2351 Millikan

Office Hours: Mon 9-11am, Wed 1:30-4pm, or by appointment

Mentors: Sophia Sun & Ethan Ong

See Sakai for Zoom address:

Sunday (Sophia & Ethan) 8-9pm;  Monday (Ethan) 8-9pm; Wednesday (Sophia) 5-6pm; Thursday (Sophia & Ethan) 8-10pm

LiCMath Mentor: Ethan Ashby

Ask Ethan Ashby for Zoom address

• The Math58 community will meet Thursday from 2:45-4:15 pm
• The Math58B community will meet Saturday from 2:45-4:15 pm


Important Websites:

Exam 1 (Thursday, March 12)

Exam 2 (take-home, last week of classes)

Final Data Analysis Project:

  • Math 58 — due Monday, 5/11/20, 2pm
  • Math 58B — due Thursday, 5/14/20, 2pm
  • Seniors are now in line with all students (grades are due on the same day)

Text: I will follow Introductory Statistics with Randomization and Simulation by Diez et al. reasonably closely (https://www.openintro.org/book/isrs/).  The examples are quite insightful, and if you read them closely, you will gain a deep understanding of the course material. I have posted the daily sections on the course homework page. It would do you well to read over the text before we cover the material in class.

We will start with chapter 2 (and proceed forward), and we will use chapter 1 as a reference.  The material in chapter 1 will be covered throughout the semester, so be sure to go back to chapter 1 as you have questions or start studying for exams.

Many of the examples and all of the applets will be taken from Investigating Statistical Concepts, Applications, and Methods, by Chance & Rossman (if you want to see the details of the examples, you can purchase the R version of the text (.pdf) here for $5: http://rossmanchance-2.myshopify.com/collections/r-1).

ISCAM website with homework & applets



  • Homework will be assigned from the text and due every Thursday.
    • One homework grade will be dropped.
    • HW is graded on a scale of 5/4/3/2/1. See the first HW assignment for more information.  One point will be deducted if superfluous information is printed or if assignment is excessively long. 
    • All R HW problems should be turned in as pdf documents compiled from an R Markdown file.  Remember:  knit early and often!


Date topic ISRS section

(base text with HW and reference material)

ISCAM investigation

(mostly in-class examples & applets)

Lab due:

Tuesday (5pm)


HW due:

Thursday (5pm)

Tue 1/21  test infants   Inv 1.1    
Th 1/23 structure of hyp testing 2.1 & 2.2 & 2.3     syllabus quiz

Wed 1/22

Fri 1/24

      R & the tidyverse  
Tue 1/28 central limit theory  2.4 & 2.5 Inv 1.8 Lab#1  as .pdf

Lab#1 as .Rmd

What is the final write up supposed to look like?  Click here

Th 1/30 normal probabilities 2.6 & 2.7 1.9 In class:



HW#1 as .pdf

HW#1 as .Rmd


Wed 1/29

Fri 1/31


Tue 2/4

confidence intervals 2.8  Inv 1.10  

Lab#2  as .pdf

Lab#2 as .Rmd


Th 2/6

        HW#2 as .pdf

HW#2 as .Rmd


Wed 2/5

Fri 2/7


Tue 2/11

sampling 1.3-1.4 Inv 1.12  

Lab#3  as .pdf

Lab#3 as .Rmd


Th 2/13

errors & power 3.1 & 2.3 Inv 1.7   HW#3 as .pdf

HW#3 as .Rmd


Wed 2/12

Fri 2/14


Tue 2/18

58: Binomial / 58B: RR & OR no ISRS   58: Inv 1.2 & 1.3 / 58B: Inv 3.9 & 3.10 Lab#4  as .pdf

Lab#4 as .Rmd


Th 2/20

        HW#4 as .pdf

HW#4 as .Rmd


Wed 2/19

Fri 2/21


Tue 2/25

2 categorical variables 3.2  Inv 3.1 Math 58: Lab#5  as .pdf

Math 58: Lab#5 as .Rmd


Math58B: Lab#5  as .pdf

Math58B: Lab#5 as .Rmd


Th 2/27

experiments 1.4 & 1.5 Inv 3.3 & 3.4   Math58: HW#5 as .pdf

Math58: HW#5 as .Rmd


Math58B: HW#5 as .pdf

Math58B: HW#5 as .Rmd


Wed 2/26

Fri 2/28

Tu 3/3 chi-square — goodness-of-fit 3.3  Inv 5.1 Lab#6  as .pdf

Lab#6 as .Rmd


Th 3/5

chi-square —

test of independence

      HW#6 as .pdf

HW#6 as .Rmd


Wed 3/4

Fri 3/6

    Inv 5.2    

Tue 3/10

catch-up / review     Lab#7  as .pdf

Lab#7 as .Rmd


Th 3/12

exam1       NOT DUE (ever!)

HW#7 as .pdf

HW#7 as .Rmd


Wed 3/11

Fri 3/14

  4.5 Inv 2.9    

Tue 3/17

spring break 1        

Tue 3/24

spring break 2

census & COVID-19


Tue 3/31

one mean 4.1  Inv 2.4 no lab due  

Th 4/2

    Inv 2.5 Take home due

(posted on Sakai)

no HW due


Wed 4/1

Fri 4/3

wrangling & graphing quantitative data

Lab#9  as .pdf

Lab#9 as .Rmd


Tue 4/7

prediction intervals    Inv 2.6 Lab#8  as .pdf

Lab#8 as .Rmd


Th 4/9

two means 4.3 Inv 4.2 (maybe: 4.3)   due FRIDAY April 10 HW#8 as .pdf

HW#8 as .Rmd


Wed 4/8

Fri 4/10

R code for inference on one quantitative variable (one group & two groups)

Lab#10  as .pdf

Lab#10 as .Rmd


Tue 4/14

two means 4.3  Inv 4.5 & 4.6 no lab due  

Th 4/16

correlation 5.1 Inv 5.6 & 5.7   due FRIDAY April 17 HW#9 as .pdf

HW#9 as .Rmd


Wed 4/15

Fri 4/17

plotting & wrangling two quantitative variables

Lab#11  as .pdf

Lab#11 as .Rmd


Tue 4/21

SLR inference 5.4  Inv 5.10 & 5.11 no lab due  

Th 4/23

transformations 5.3 Inv 5.14   due FRIDAY April 24 HW#10 as .pdf

HW#10 as .Rmd


Wed 4/15

Fri 4/17

R code for inference on two quantitative variables

Lab#12 as .pdf

Lab#12 as .Rmd


Tue 4/28

58: multiple regression / 58B: logistic regression 58: 6.1 – 6.3 / 58B: 6.4   no lab due  

Th 4/30

        due FRIDAY May 1 HW#11 as .pdf

HW#11 as .Rmd


Wed 4/29

Fri 5/1

 no lab        

Tue 5/5

catch-up / review        
Math 58 — Mon, 5/11/20, 2pm

Math 58B — Th, 5/14/20, 2pm

seniors are now on the same grading schedule as all students       Take Home Project based on a regression data analysis