MW from 8am - 9:40am in L372 from 8/17/26 - 12/10/26
This course focuses on statistical reasoning and on solving problems using real-world data rather than on computational skills. Use of technology-based computations (such as graphing calculators with a statistical package, spreadsheets, or statistical computing software) is required with emphasis on interpretation and evaluation of statistical results. Topics include data collection processes (observational studies, experimental design, sampling techniques, bias), descriptive methods using quantitative and qualitative data, bivariate data, correlation, and least-squares regression, basic probability theory, probability distributions (normal distributions and normal curve, binomial distribution), chi-square tests, one-way analysis of variance, confidence intervals and hypothesis tests using p-values. Students cannot receive credit for both MATH 1774 and BSNS 2514.
Course Alignment
General Education Outcomes are the knowledge, skills, abilities, attitudes, and behaviors that students are expected to develop as a result of their overall experiences with any aspect of the college, including courses, programs, and student services, both inside and outside of the classroom. The General Education Outcomes specifically learned in this course are:
- Communication
- Critical Thinking
Faculty Contact Information
In-Person in R303: MW 10am - 10:45am, TTH 12:00pm - 1:45pm
Always available by email (kburgess@kcc.edu) or Canvas message. Expect a reply within 24 hours or sooner.
Course Information
At the end of this course, students will be able to:
- Organize data using frequency distributions and graphs
- Distinguish between the different types of studies and different types of random sampling
- Describe (summarize) data using measures of central tendency and dispersion
- Perform calculations associated with fundamental distributions and solve related application problems
- Construct confidence intervals for means and proportions
- Perform hypothesis tests for means and proportions using p-values.
- Calculate correlation coefficient and check its significance
- Estimate a regression equation and interpret its coefficients
- Use technology to complete basic statistical analyses
- Data Collection
- Introduction to the Practice of Statistics
- Observational Studies vs Designed Experiments
- Simple Random Sampling
- Other Effective Sampling Methods
- Bias in Sampling
- The Design of Experiments
- Descriptive Statistics
- Organizing Qualitative Data
- Organizing Quantitative Data: The Popular Displays
- Additional Displays of Quantitative Data
- Graphical Misrepresentations of Data
- Numerically Summarizing Data
- Measures of Central Tendency
- Measures of Dispersion
- Measures of Central Tendency and Dispersion from Grouped Data
- Measures of Position and Outliers
- The Five-Number Summary and Boxplots
- Describing the Relation Between Two Variables
- Scatter Diagrams and Correlation
- Least Squares Regression
- Diagnostics on the Least-Square Regression
- Contingency Tables and Association
- Probability and Probability Distributions
- Probability Rules
- The Addition Rule and Complements
- Discrete Probability Distributions
- Discrete Random Variables
- The Binomial Distribution
- The Normal Probability Distribution
- Properties of the Normal Distribution
- Applications of the Normal Distribution
- Assessing Normality
- Sampling Distributions
- Distribution of the Sample Mean
- Distribution of the Sample Proportion
- Estimating the Value of a Parameter
- Estimation a Population Proportion
- Estimating a Population Mean
- Estimating a Population Standard Deviation
- Putting It Together: Which Procedure Do I Use?
- Hypothesis Tests Regarding a Parameter
- The Language of Hypothesis Testing
- Hypothesis Tests for a Population Proportion
- Hypothesis Tests for a Population Mean
- Hypothesis Tests for a Population Standard Deviation
- Inferences on Two Samples
- Inference about Two Population Proportions
- Inference about Two Means: Dependent Samples
- Inference about Two Means: Independent Samples
- Inference on Categorical Data
- Goodness-of-Fit Test
- Tests for Independence and the homogeneity of Proportions
- Comparing Three or More Means
- One-Way Analysis of Variance
Textbook(s): Statistics: Informed Decisions Using Data 8th edition by Michael Sullivan with MyStatLab Access Code. The textbook is NOT required. The MyStatLab access code is part of your course fees.
Graphing Calculator optional, TI 84 preferred. Miner Memorial Library has TI-84s available for loan for free for the entire semester. If this is the only math class you need and you don’t already have a graphing calculator, I would suggest going there to check one out.
This course will be evaluated as follows:
MyLab Homework: 30%
In Class Activities and Attendance: 30%
Projects: 20%
Final Exam: 20%
Grading Scale by Percentage:
90 – 100 A
80 – 89 B
70 – 79 C
60 – 69 D
Below 60 F
MyLab Homework:
Homework will be assigned and completed using the link provided on Canvas. The homework in My Lab will focus on math skills and as many opportunities as necessary are granted to achieve full credit, thus, persistence is the key. Homework is your opportunity to practice and master the material. Homework is due on the date and time listed in My Lab and is completed on your own time. Extensions may be given at the instructor’s discretion.
In-Class Activities and Participation:
Attendance is mandatory. To be successful in this course, a student must attend every scheduled class. You are responsible for work missed due to absence. You must contact your instructor before class has started to be marked as excused. If you come in after class has started, you may be marked absent. Leaving early from class will also be noted.
Attendance will count as a small portion of your grade combined with in-class activities. Note: Math can be taught in the classroom, but can only be learned through practice, critical thinking, and more practice. Please ask questions to help further your understanding, either in class or during office hours.
There will also be small assignments on Canvas every other week or so to check in on your progress in the course.
Final Exam:
The final exam will be given during week 17 of the semester so Monday, December 7th at 8:00am - 9:50am. The final exam will be done on paper. It will be cumulative. There will be a final exam review guide for the final exam. You will be allowed a cheat sheet, both sides of a normal 8.5” by 11” piece of paper, where you can write any notes that you would like to use during the exam. A formula sheet will be provided during the exam as well which you will be able to see the week before the exam.
Liberal Arts & Sciences
Dean, Jennifer Huggins; 815-802-8484; R310; jhuggins@kcc.edu; Division Office- W102; 815-802-8700
Calculator Usage
You will want some type of calculator, but it doesn't have to be a graphing calculator. Graphing calculators may be used throughout this course. The TI-84 is the preferred graphing calculator. Remember, you can always borrow one from the library for free for the whole semester!
Cell Phones or Other Distractions:
Please try to refrain from using cell phones for call, texting, etc while in class. If it is an emergency, please take calls outside the classroom. Using cell phones or other electronic devices on or during the taking of tests/quizzes will be considered cheating and will be subject to academic integrity guidelines below.
Accommodations:
Students must have an official letter from the Office of Disability Services for any accommodations. If students have this letter, please send to the instructor immediately. Accommodations can only be in effect if given to the instructor at least 24 hours before an assessment. Accommodations cannot be applied after a student has completed an assessment.
Artificial Intelligence:
Artificial intelligence (AI) is a resource that you can use to help you learn concepts. If you are using AI to complete all of your homework for you, then you are not utilizing it as a resource, but as a crutch. You will not learn anything from this course if you do not struggle through the homework until you understand what you are doing.
If you are found to be using AI for solutions to homework questions, then you get a warning to not continue using AI to find answers. If you continue using AI, then you will receive a zero for the assignment or possible removal from the course.
Academic integrity:
Cheating will not be tolerated. Infractions will follow the Student Code of Conduct and may result in a zero in the assignment/assessment and/or removal from the class.
| Week and Dates | Topics |
| Week 1 | Chapter 1 |
| Week 2 | Chapter 2 |
| Week 3 | Chapter 3 |
| Week 4 – 5 | Chapter 4 |
| Week 6 | Chapter 6 |
| Week 7 – 8 | Chapter 7 |
| Week 9 | Chapter 8 |
| Week 10 – 11 | Chapter 9 |
| Week 12 – 13 | Chapter 10 |
| Week 13 – 14 | Chapter 11 |
| Week 15 | 12.1 and 13.1 |
| Week 16 | Review for Final Exam |
| Finals Week |
College Policies, Resources and Supports
For information related to the Student Code of Conduct Policy, Withdrawal Policy, Email Policy, and Non- Attendance/Non-Participation Policy, please review the college’s Code of Campus Affairs and Regulations webpage, which can be found at catalog.kcc.edu under the Academic Regulations & Conduct Guide.
KCC offers various academic and personal resources for all students. Many services are offered virtually, as well as in person. Please visit Student Resources - Kankakee Community College to access student resources services such as:
- Clubs and organizations
- Counseling and referral services
- Office of disability services
- Student complaint policy
- Transfer services
- Tutoring services, etc.
The materials on this course are only for the use of students enrolled in this course for purposes associated with this course. Further information regarding KCC's copyright policy is available at https://kcc.libguides.com/copyright.
|Course syllabus/calendar is subject to change.