Course Description: An introduction to statistics suitable for social and behavioral science majors, but also suitable for students in other disciplines. Topics include statistical theory and experimental design, descriptive statistics, probability distribution models, regression analysis and correlation, inference, and sampling methods. Credits: 3 Prerequisites: Course placement determined by Multiple Measures MEETS THE FOLLOWING MNTC GOAL AREAS: Goal 4: Mathematical/Logical Reasoning COURSE MEETING DAYS/TIME: Monday and Wednesday 9-10:15pm MEETING DATES: January 12 - May 12 DELIVERY METHODOLOGY: in class CLASSROOM LOCATION: room 228
Fond du Lac Tribal & Community College 2101 14th Street Cloquet, Minnesota 55720 Office: W217 Phone: 218-879-0840 Email: ted@fdltcc.edu Spring 2026 Class Schedule: Time Days Room Course 8:00- 8:50 M_W__ W217 Office Hour 9:00-10:15 M_W__ 228 Math 1030 10:30-11:20 M_W__ 228 Math 0025 12:00- 1:00 M_W__ W217 Csci 1010 1:00- 2:00 M_W__ W217 Office Hour 2:15- 3:30 M_W__ 228 Math 1010 asynchronous D2L Math 2001
Office Hours in Room W217: Mon Tues Wed Thurs Fri 8-9 ---- 8-9 ----- --- 1-2 ---- 1-2 ----- ---
Email me questions anytime. Check your email, and check class announcements on D2L. Pop in during office hours.
All class materials will be on D2L: this syllabus, handouts, homework, and sample exams as PDF documents.
You should not print out the textbook. It will not disappear. You can download the PDF for viewing on your own machine if this is handy for you. You will probably read some sections more carefully than others. Sections are referenced in the tentative scheule as needed.
Statistics textbooks vary in details; you will note differences if you look through other texts and references. We will use the conventions in this textbook. One weakness of this textbook is that the tables are difficult to use and, notably, difficult to print out in readable form. Here are some common tables in better form:
Online: Standard Normal, Binomial, and T Tables
You may have a calculator already, but make sure that it is a scientific calculator. If you need to buy one, I recommend a cheap calculator like a TI-30XS Multiview or a TI-36X Pro. These do what you need, and the FDLTCC bookstore sells at least one of them for under $20 . You need to have it available for all assignments. You do not need a more expensive graphing calculator, but, if you have one, that will be fine.
Keep your calculator handy! You must have it for homework, exams, and in-class work.
However, here are some online calculators you may find helpful:
Basic Statistics and Standard Normal Distribution Calculators
These days we have to have these for some things, but one can survive without them for at least a few hours. In class, turn them off or mute the ringer, and put them away. Do not use PEDs for tests; use a calculator as above. Do not use AI to do homework.
Show your work on homeworks and exams! That is what I'm looking for, not just lists of answers--though of course correct answers are important.
4 tests 4x100 = 400
1 final 200
20 homework 5x20 = 100
-----------------------
700 total
90-100% A
80-90% B
70-80% C
60-70% D
0-60% F
Scores from tests are posted on D2L here:
https://fdltcc.learn.minnstate.edu/
This course addresses FDLTCC liberal education requirements (Competencies Across the Curriculum) in problem solving and technology. You should attend class everyday! This is the easy way to do well in any course, and it is especially true for math classes. There are exercises in the text for you to do, and these are usually answered at the end of each chapter. You will also get homework assignments on handouts, and you should complete then hand these in at the beginning of the next class. You homework grade is based on completing and turning in these homework handouts. You will also get sample exams which will be similar in length and content to the in-class exams. Let me know if there is are accommodations you need for the class.
A feature of statistics study is that one does not have to make up applications out of the blue. Applications abound! To be sure, our examples for studying statistics are somewhat contrived, for practical convenience. We do not need to handle 1,200,000 numbers when just 12 numbers will do. Theory, methods, and key steps are essentially identical for large and small sets. It just takes more labor handling large data sets.
The tentative schedule below shows class days. I'll post homework, materials, and sample tests on D2L under Materials >> Content.
You are required to do homework and tests on your own efforts without using other people or AI.
Mon jan12 1 1.1 Basic Definitions and Concepts,
1.2 Overview,
1.3 Presentation of data
Wed jan14 2 2 1. descriptive statistics,displaying data
2.2 central position
Mon jan19 H
Wed jan21 3 2.3 variance
Mon jan26 4 2.4 relative position
Wed jan28 5 2.5 STD DEV and Chebyshev's theorem
Mon feb02 6 Sample Test 1 and review (in class)
Wed feb04 7 T1
Mon feb09 8 3.1 sample spaces
3.2 set theory
Wed feb11 9 3.3 conditional probability
Lets Make a Deal
Mon feb16 H
Wed feb18 10 Counting, permutations, and combinations
Mon feb23 11 4.1 discrete random variables
4.2 probability distributions
Wed feb25 12 4.3 binomial distr
Mon mar02 13 Sample T2 and Review
Wed mar04 14 T2
Spring Break
Mon mar16 15 5.1 continuous random variables
Wed mar18 16 5.2 standard normal distr
5.3 computation: using std normal distr
Mon mar23 17 5.4 tails of distr
Wed mar25 18 T3 (see sample test 3 and KEY on D2L under materials)
Mon mar30 19 6.1 mean and std dev of the sample mean
6.2 sampling distr of sample mean
Wed apr01 20 7.1 large sample estimation
Mon apr06 21 7.2 small sample estimation
Wed apr08 22 7.3 estimation of sample proportion
Mon apr13 23 7.4 sample size considerations
Wed apr15 24 Test 4 Review
Mon apr20 25 T4
Wed apr22 26 8.1 hypotheses testing
Mon apr27 27 8.2 large sample test for population mean
Wed apr29 28 8.3 significance of a test
Mon may03 29 Final Exam Review
Wed may06 T1 Math1030 Room 228 9-10:50am
Thu may07 T2
Fri may08 NC
Mon may11 T3 (Math1010 Room 228 12-1:50pm)
Tue may12 T4
LEARNING GOALS and OUTCOMES (This information can be found in the Master Course Outline) At FDLTCC we have 4 Competencies Across the Curriculum (CAC) areas. They are as follows: A. Information Literacy (the ability to use print and/or non-print tools effectively for the discovery, acquisition, and evaluation of information.) B. Ability to Communicate (the ability to listen, read, comprehend, and/or deliver information in a variety of formats.) C. Problem Solving (the ability to conceptualize, apply, analyze, synthesize, and/or evaluate information to formulate and solve problems.) D. Culture (knowledge of Anishinaabe traditions and culture, knowledge of one’s own traditions and culture, knowledge of others’ traditions and cultures, culture of work, culture of academic disciplines and/or respect for global diversity.) Upon completion of this course, the student will be able to: Learning Outcomes Competencies (CAC) Cultural Standards 1. Organize raw data into C 2 frequency distributions and various graphs for analysis. 2. Describe data using C measures of central tendency, variation, and position. 3. Find the probability of C 4 compound events involving additive, multiplicative, and/or conditioned properties. 4. Calculate descriptive C statistics and probabilities for discrete probability distributions, including the binomial distribution. 5. Analyze the normal C distribution and its applications. 6. Use methods of C 1,4 inferential statistics to test the significance of a hypothesis with one and two variables. 7. Predict the value of a C dependent variable using linear regression. WINHEC Cultural Standards: 1. GIKENDAASOWIN – Knowing knowledge: To develop human beings who value knowledge, learning, and critical thinking and are able to effectively use the language, knowledge, and skills central to an Ojibwe-Anishinaabe way of knowing. 2. GWAYAKWAADIZIWIN – Living a balanced way: To develop balanced human beings who are reflective, informed learners who understand the interrelatedness of human society and the natural environment, recognize the importance of living in harmony with creation, and are able to apply a systems approach to understanding and deciding on a course of action. 3. ZOONGIDE'EWIN – Strong hearted: To increase the students’ capacity to live and walk with a strong heart, humble and open to new ideas and courageous enough to confront the accepted truths of history and society. 4. AANGWAAMIZIWIN – Diligence and caution: To develop students’ capacity to proceed carefully, after identifying, discussing, and reflecting on the logical and ethical dimensions of political, social, and personal life. 5. DEBWEWIN – Honesty and integrity: To increase students’ capacity to think and act with honesty and integrity as they understand and face the realities of increasingly interdependent nations and people. 6. ZAAGI' IDIWIN – Loving and Caring: To encourage students' acceptance of the diversity within their school, community, and environment by developing healthy, caring relationships built on respect for all. 7. ZHAWENINDIWIN – Compassion: To expand students' knowledge of the human condition and human cultures and the importance of compassion especially in relation to behavior, ideas, and values expressed in the works of human imagination and thought.
The primary academic mission of Fond du Lac Tribal and Community College is the exploration and dissemination of knowledge. Academic honesty and integrity are integral to the academic process. Academic dishonesty, cheating, plagiarism, and collusion are serious offenses which undermine the educational process and the learning experience for the entire college community.
Fond du Lac Tribal and Community College students are expected to understand and adhere to the concept of academic integrity and to the standards of conduct prescribed by the college’s policy on Academic Honesty. Students are expected to assume responsibility for their work, and student materials submitted in fulfillment, of course, program, and college academic requirements must represent students’ own efforts. Any act of academic dishonesty attempted by a student at Fond du Lac Tribal and Community College is unacceptable and will not be tolerated.
Violations of academic integrity or other forms of misconduct may result in serious consequences. These can include receiving a failing grade ("F") for the course and may also lead to additional disciplinary actions as outlined by Fond du Lac Tribal and Community College and the Minnesota State system. For full details, please refer to the Student Code of Conduct Policy.
Option 1: No Use of Generative A.I. Allowed Generative AI policies may differ from one course to another. In this course, the use of generative AI tools (ChatGPT, Copilot, Gemini, DALL-E, etc.) is prohibited for all assignments, exams, and projects in this course. All submitted work must be your own. Using generative AI at any stage of your work constitutes a violation of FDLTCC’s academic honesty policy.One cannot avoid AI completely these days. AI is pushed at everyone by search engines and ordinary applications such as a word processor-- and pushed very hard too! Rather, do not use AI to solve any math problems you present as your work. This is your essential skill to develop in this course: solving problems.