Syllabus
Learning Objectives
This course covers the foundations of statistical thinking. The objective of the course is to introduce students to the importance of statistics in various fields, and equip them with the tools necessary to interpret, analyze, and make informed decisions based on data. By the end of this course, you should be able to understand and analyze everyday data with a keen statistical insight. The core learning objectives include:
- Data Summarization. Understand how to effectively describe and represent data.
- Probability and Randomness. Explore the principles governing random events and outcomes.
- Inferential Analysis. Learn to make informed conclusions and predictions from data.
- Data Relationships. Investigate how variables interact and influence one another.
By the end of this course, you should be able to adeptly interpret and analyze statistical data encountered in everyday scenarios.
List of Topics
- Data, Visualization, and Descriptive Statistics
- Types of data: qualitative vs. quantitative
- Data collection and sampling methods
- Basic data visualization techniques
- Measures of central tendency and dispersion: mean, median, mode
- Probability
- Fundamental concepts and definitions
- Conditional probability and independent events
- Discrete and continuous probability distributions
- Statistical inference
- Population vs samples
- Introduction to confidence intervals
- Inference from a single sample
- Inference from two samples
- Hypothesis testing
- Regression and Correlation
- Simple linear regression
- Correlation coefficient and its interpretation
Textbooks
OpenIntro Statistics
David Diez • Christopher Barr • Mine Çetinkaya-Rundel
Fourth Edition
Book link
Probability, Statistics, and Data: A Fresh Approach Using R
Darrin Speegle • Bryan Clair
First Edition
UCSD Online Access
Prerequisites
This course will require a background in calculus (MATH 20C or MATH 31BH).
Collaboration & Academic Integrity
You are expected to complete the assignments on your own. If you happen to discuss them with a fellow Math 183 student that’s okay; Please acknowledge your collaborators. However, you are expected to write up your own solutions from scratch and list the students you collaborated with. In a nutshell, each student must understand their assignment solution well enough in order to reproduce it by themselves.
✅ The following is OK:
You and your friends work through the problems together over a couple of study sessions. Afterwards, each member writes their own solution to the homework problems without referring to others’ write-ups. For example, you might brainstorm different approaches to a constructing a confidence interval during the group meeting, then individually implement and document your chosen method.
❌ The following is NOT OK:
You and your friends work through the problems together over a couple of study sessions. You bounce ideas off each other, and eventually come up with a pretty good solution. One of your friends types up their solutions first. Since you participated in the study session and helped come up with the answers, you take the liberty to use your friend’s solutions as a starting point for your own. Or, worse yet, you submit their solutions as your own.
Here are a few of the examples of honor code violations:
- Looking at the writeup of another student.
- Showing your writeup to another student.
- Discussing homework problems in such detail that your solution is almost identical/ or showing high similarity to another student’s answer.
- Uploading your writeup or code to a public repository (e.g. github, bitbucket, pastebin) so that it can be accessed by other students.
- Looking at solutions from online repository or previous years’ homeworks
- Collaborating with others during exams.
- Entering homework questions into any software, apps, or websites. Accessing resources that directly explain how to answer questions from the actual assignment or exam is a violation of course policy.
Students who do not follow the policies of the course on collaboration and academic honesty will be reported to The Academic Integrity Office and should expect to receive an F in the course.