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View MTH 225 module level objectives.tex
\section{Appendix B: MTH 225 Learning Targets}
\begin{subsubsection}{Module 1: Computer Arithmetic}
\item[CA.1] \textbf{(CORE)} \ I can represent an integer in base 2, 8, 10, and 16 and represent a negative integer in base 2 using two's complement notation.
\item[CA.2] I can perform addition, subtraction, multiplication, and division in binary.
View MTH 225

Course module structure: The course content is split up into five modules:

  • Module 1: Computer arithmetic. Representing integers in binary, octal, and hexadecimal; binary arithmetic; the Division Algorithm and modular arithmetic.

  • Module 2: Logic. Logical propositions, conditional statements, truth tables, predicates, and quantification.

View MTH 225 course level

Course-level learning objectives: Upon completion of MTH 225, you will be able to:

  • Represent integers using different number bases, and perform integer arithmetic using different bases and modular arithmetic.

  • Formulate, manipulate, and determine the truth of logical expressions using symbolic logic.

  • Formulate and solve computational problems using sets and functions.


MTH 225 Learning Objectives

By module

  • Module 1: Arithmetic
    • Given an integer in base 2, 8, 10, or 16, represent it using another base.
    • Add, subtract, multiply, and divide integers in base 2, 8, and 16.
    • Use two's complement to represent a negative integer in binary.
    • State the Division Algorithm and use it to find the quotient and remainder when dividing one positive integer by another.
# Code for generating Five-Question Summary reports.
# Import basic packages
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
# Read in student response data; change name of file as needed
col_names = ["Challenge", "Support", "Competence", "Autonomy",

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def fib(n):
if n == 0 or n == 1:
return 1
return fib(n-1) + fib(n-2)
def A(n):
if n == 1:
return 1
elif n == 2:
return 4
return A(n-1) + 2*A(n-2)
RobertTalbert /
Last active Oct 16, 2020
Sage code for generating random weighted undirected graph
## Generates a random weighted undirected graph.
## n = number of nodes
## p = probability that two nodes are adjacent; must be between 0 and 1.
## lower_weight and upper_weight = lower and upper edge weights, respectively. If left out, the defaults are 1 and 100.
## Examples of usage:
## g = random_weighted_graph(20, 0.5) <-- Uses default lower and upper weights of 1 and 100.
## h = random_weighted_graph(10, 0.35, 5, 50) <-- Weights will be integers between 5 and 50.
## = True) <-- Include the argument to display the weights
## <-- leave the argument out to hide the weights

Here's a suggested work plan for the week. As always, this assumes you are putting aside 2 hours per weekday for work on MTH 201; if you can do that, and stick to the plan, you'll be free and clear for the weekend.

  • Monday: 30 minutes to get started on Daily Prep for Module 6B; 30 minutes to get started with WeBWorK for Module 5; 30 minutes to work on an AEP (new draft or a revision); 30 minutes on the Derivative Computation WeBWorK set.
  • Tuesday: 30 minutes to complete Daily Prep 6B; 30 minutes on an AEP; 30 minutes on the WebWorK for Module 6; 30 more minutes the Derivative Computation set.
  • Wednesday: 30-45 minutes to complete Followup for Module 6A; 30 minutes on WeBWorK for Module 6; 30 minutes on an AEP; 30 minutes checking in with Campuswire and asking questions.
  • Thursday: 30 minutes to start Followup for Module 6B; 30 minutes for WeBWorK; then an hour on an AEP.
  • Friday: 30 minutes to complete Followup for Module 6B; 30 minutes to complete WeBWorK for Module 6; 30