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: Tuesday and Thursday 9-10:15pm MEETING DATES: August 25 to December 15, 2026 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 Fall 2026 Class Schedule: 8:00 - 8:50am _T_Th_ Office Hours W217 9:00 - 10:15am _T_Th_ Statistics 228 10:30 - 11:20am _T_Th_ Statistics Prep 228 12:00 - 12:20pm _T_Th_ Office Hours W217 12:30 - 1:45pm _T_Th_ College Algebra 228
Office Hours in Room W217: Mon Tues Wed Thurs Fri ---- 8-9 ---- 8-9 ----- ---- 12-12:20 ---- 12-12:20 -----
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.
Tue aug25 1 1.1 Basic Definitions and Concepts,
1.2 Overview,
1.3 Presentation of data
H1
Thu aug27 2 2 1. descriptive statistics,displaying data
2.2 central position
Tue sep01 3 2.3 variance
2.4 relative position
Thu sep03 4 2.5 STD DEV and Chebyshev's theorem
Tue sep08 5 Sample Test 1 and review
Thu sep10 6 T1
Tue sep15 7 3.1 sample spaces
3.2 set theory
Thu sep17 8 3.3 conditional probability
Lets Make a Deal
Tue sep22 9 Counting, permutations, and combinations
Thu sep24 10 4.1 discrete random variables
4.2 probability distributions
Tue sep29 11 4.3 binomial distr
Thu oct01 12 Sample T2 and Review
Tue oct06 13 T2
Thu oct08 14 5.1 continuous random variables
Tue oct13 15 5.2 standard normal distr
5.3 computation: using std normal distr
Thu oct16 NC No Classes
Tue oct20 16 5.4 tails of distr
Thu oct22 17 T3 review
Tue oct27 18 T3
Thu oct29 19 6.1 mean and std dev of the sample mean
6.2 sampling distr of sample mean
Tue nov03 20 7.1 large sample estimation
Thu nov05 21 7.2 small sample estimation
Tue nov10 23 7.3 estimation of sample proportion
Thu nov12 24 7.4 sample size considerations
Tue nov17 25 T4 Review
Thu nov19 26 T4
Tue nov24 27 8.1 hypotheses testing
Thu nov26 NC No Classes
Tue dec01 28 8.2 large sample test for population mean
Thu dec03 29 8.3 significance of a test
Tue dec08 28 other distributions
Thu dec10 30 final exam review:
Tue dec15 T1 Math 1030 9:00am - 10:50am room 228
Math 1010 11:00am - 12:50pm room 228
Wed dec17 T2
Thu dec18 T3
Fri dec19 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.