Is Math 40 Difficult?
All things are difficult before they are easy.
~Thomas Fuller
~Thomas Fuller
Statistics is the study of data. Because data can consist of a lot of numbers, we need to use technology, like Excel, Google Sheets, or Python programming. Most students struggle with the technology aspect of statistics, mostly because of the immense attention to detail that is needed for coding or entering commands. We will work together on this! Detail orientation is a skill that needs practice.
There are a lot of new vocabulary words that you'll need to know and apply. I won't quiz you on direct word-for-word definitions, but after some practice, you should be able to use the vocabulary in the correct contexts and understand the questions that are asked. We're learning a new field of study here, and there is lingo to know with every field of study.
Statistics has a direct application to your life and the world. Students who never understood why we learn math see it in practice in a statistics class. This is why I love teaching it!
How Much Reading? Every week, zero-cost readings and videos via Canvas are carefully selected to ensure the essential questions can be answered. The readings may be challenging, yet effective time management is part of the college experience.
How Much Weekly Work? Four assignments accompany the lessons: Textbook readings, Focused Notes, Lab and Practice.
Textbook readings help you get familiar with the content so that when you get into the examples, you have a foundation to build on with the vocabulary. I'm not expecting you to understand the reading at first; the intention is to get you familiar with the vocabulary and content. We'll be using Hypothesis to create annotations within the textbook and you'll be able to share comments, questions, memes, etc. within this platform that the class can view.
Focused Notes are provided to help you organize your learning, and to help follow along with the lessons.
Lab assignments focus on applying statistics using various technology. Many of these will be completed along with the lessons and some will be on your own. Several of these assignments will support your Project (see below), and may be done with help from your group.
Practice is exactly what it is: Practice statistics. These are usually short "homework" assignments.
How Many Tests? In this class, we'll refer to tests as assessments. There are 2 types of Assessments:
A Formative Assessment is a small and simple assessment designed to measure the process of your understanding of the course content. Feedback provides guidance toward learning the content, and helps you correct mistakes before the summative assessments. The focused notes, labs, and practice are formative assessments and occur for each chapter.
A Summative Assessment is designed to measure your application of the unit course content. There are 6 summative assessments: 4 Exams, a Final Exam, and a Project . You will have opportunities to improve your scores for the 4 exams after feedback is given to learn from your mistakes.
A Project? Because analyzing data will occur in nearly every field, it is important that we can apply our statistical learning to a data set and decide on the best statistical test or graph to accurately demonstrate what the data shows and how that information can be applied more widely. This project is broken into smaller assignments throughout the semester that you will have assembled by the end of class. The final project product could be a paper, a slide presentation, a video, a website, or possibly something else creative that showcases all the work your group completed. There will be specific components required in the final product, but delivery can occur in one of multiple ways. In summer, the project due dates are on the non-exam weeks.
Grading? A rubric is attached to each assignment. A rubric contains evaluative criteria, quality definitions for those criteria at particular levels of achievement, and a scoring strategy. Reading the rubric will guide you toward your best possible outcome. Feedback will enable you to understand how to maintain your focus on a successful outcome. Grading is usually completed within a week.
Any Extra Credit? One opportunity for extra points on the final exam, you can attend three virtual Smart Shops for three points added to your final exam grade. You will need to make sure you complete the survey at the end of the Smart Shop to receive credit, and include my name as the only instructor. You won't be allowed to "double-count" a Smart Shop for two or more classes.
Course Calendar - Fall 2023
Here's a general guide to the content, but it is subject to change.
Week 1: Get up and running - learn about the course, navigate Canvas, get materials, Annotate the syllabus.
Week 2: Learn Nature of Statistics (Chapter 1), Learn Probability (Chapter 4)
Week 3: Learn Probability (Chapter 4); Learn Frequency Distributions and Graphs (Ch 2)
Week 4: Ch 2 continued
Week 5: Review for Exam 1; Exam 1 (Ch 1, 2, 4); Project Part 1 due
Week 6: Learn Data Description (Ch 3)
Week 7: Learn Discrete Probability Distributions (Ch 5)
Week 8: Learn Continuous Probability Distributions (Ch 6)
Week 9: Review for Exam 2; Exam 2 (Ch 3, 5, 6); Project Part 2 due
Week 10: Learn Confidence Intervals (Ch 7)
Week 11: Ch 7/8 continued
Week 12: Hypothesis Tests (Ch 8)
Week 13: More Hypothesis Tests (Ch 9)
Week 14: Ch 9 Continued
Week 15: Review for Exam 3; Exam 3 (7, 8, 9); Project Part 3 due
Week 16: Linear Regression (Ch 10), Chi-Square Tests and ANOVA (Ch 11)
Week 17: Review for Final Exam
Finals Week: Project part 4 due; Final Exam (cumulative; Ch 1-11)
Don’t be afraid of fear. Because it sharpens you, it challenges you, it makes you stronger; and when you run away from fear, you also run away from the opportunity to be your best possible self. ~ Ed Helms
Media Credits:
Course Banner: Man Reading Newspaper on Fire, Photo by Elijah O'Donnell on Unsplash
Bottom Quote Background, Empty Hallway, Photo by Andy Li on Unsplash