TTH 12:00 pm - 2:15 pm in room D328
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
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 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. IAI: M1 902 Mathematics. IAI: BUS 901 Business.
Prerequisite:
Appropriate assessment score or Math 1424 with a grade of C or better, or Math 0985 with a C or better, and ENGL 1413 with a grade of C or better, or appropriate assessment score. Must be completed prior to taking the course. This course serves as a general introduction to statistics, focusing on mathematical reasoning and the solving of real-life problems. Contents include descriptive methods, measures of central tendency and variability, elementary probability theory, probability distributions, sampling techniques, confidence intervals for the mean or proportion, tests of hypotheses, chi-square, correlation and linear regression, and the F-test and one-way analysis of variance. Students cannot receive credit for both MATH 1774 and BSNS 2514. AAS: Mathematics elective; IAI: M1 902 Mathematics.
Faculty Contact Information
Jorge R. Gavillan, M.S.
email: jgavillan@kcc.edu
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
Statistics: Informed Decisions Using Data, 7th Edition
Author(s): Sullivan III, Michael
Textbook ISBN-13: 9780138253332
MyStatLab Access
We will use Excel extensively in this course. You have access to Excel through Office 365. Download the app, and it's recommended not to use the online version.
Category Percentage of final grade
Pass Quiz 5%
Homework 15%
Semester Project 40%
Final Presentation 40%
Liberal Arts & Sciences
Dean, Jennifer Huggins; 815-802-8484; R310; jhuggins@kcc.edu; Division Office- W102; 815-802-8700
Course Policies
Attendance Policy: Please be prompt for all classes. Students are fully responsible for any and all information missed due to absence. Assignments not finished and quizzes and tests not taken due to absences will result in a “0.” Attendance is taken every class hour. Attendance is used as a data tool for athletes, grade analysis, and financial aid purposes. It does not count for a grade. If you are tardy, please see the instructor at the end of class so your attendance can be counted. Calculator Usage Policy: We will be using Excel, so a graphing calculator will not be required. Homework: Homework will be assigned and completed using MyLab & Mastering. 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 MyLab & Mastering.
Project: The semester projects will be done individually. Information about the project will be given out in ample time before the due date.
Final Presentation: There will be one final presentation. Specific information about the project will be given later.
Students are expected to conduct themselves in a respectful, professional, and responsible manner in all classroom and online learning environments. This includes demonstrating courtesy toward instructors and peers, actively engaging in course activities, and contributing to a positive learning atmosphere.
In the classroom, students should arrive on time, be prepared to participate, and minimize distractions by silencing or using electronic devices appropriately. Respectful communication and collaboration are expected at all times.
In online and remote settings, students are expected to communicate professionally in discussion boards, emails, and virtual meetings. Written communication should be clear, respectful, and appropriate for an academic environment. Students should adhere to course deadlines, follow netiquette guidelines, and respect diverse perspectives.
Disruptive, disrespectful, or inappropriate behavior, whether in person or online, may result in removal from class activities, academic consequences, or referral to the appropriate college offices in accordance with institutional policies.
| Week | Tuesday | Wednesday Online | Thursday |
|---|---|---|---|
| Week 1 June 2-4 | Tue, June 2 Course launch; Semester Project overview; Pew data setup; Chapter 1 Overview/Objectives; Chapter 1 Introduction & Overview; Section 1.1: Introduction to the Practice of Statistics. | Wed, June 3 ONLINE Chapter 1: Section 1.2 Observational Studies Versus Designed Experiments; Section 1.3 Simple Random Sampling; Section 1.4 Other Effective Sampling Methods; Section 1.5 Bias in Sampling. Complete Measurement Scales Practice Quiz Lab 1. | Thu, June 4 Chapter 2 Overview/Objectives; Section 2.1 Organizing Qualitative Data; Section 2.2 Organizing Quantitative Data; Section 2.3 Additional Graphical Displays; Section 2.4 Misleading Graphs. Due: Chapter 1 Homework/Pass Quiz; Chapter 2 Homework/Pass Quiz; Pew data setup checkpoint. |
| Week 2 June 9-11 | Tue, June 9 Chapter 3 Overview/Objectives; Section 3.1 Measures of Central Tendency; Section 3.2 Measures of Dispersion. Apply to Pew data sample. | Wed, June 10 ONLINE Chapter 3: Section 3.3 Numerical Summaries from Grouped Data; Section 3.4 Measures of Position and Outliers; Section 3.5 Five-Number Summary and Boxplots. Excel/descriptive statistics lab. | Thu, June 11 Chapter 4 Overview/Objectives; Section 4.1 Scatter Diagrams and Correlation; Section 4.2 Least-Squares Regression; Section 4.3 Diagnostics; Section 4.4 Contingency Tables and Association. Due: Chapter 3 Homework/Pass Quiz; Chapter 4 Homework/Pass Quiz. |
| Week 3 June 16-18 | Tue, June 16 Chapter 5 Overview/Objectives; Section 5.1 Probability Rules; Section 5.2 Addition Rule and Complements. Begin probability examples from Pew data. | Wed, June 17 ONLINE Probability Lecture Videos; online guided probability practice; draft simple and compound probability questions for project. | Thu, June 18 Chapter 6 Overview/Objectives; Section 6.1 Discrete Random Variables; Section 6.2 Binomial Probability Distribution. Due: Chapter 5 Homework/Pass Quiz; Chapter 6 Homework/Pass Quiz; Project Part 1 draft checkpoint. |
| Week 4 June 23-25 | Tue, June 23 Chapter 7 Overview/Objectives; Section 7.1 Properties of the Normal Distribution; Section 7.2 Applications of the Normal Distribution. | Wed, June 24 ONLINE Chapter 7: Section 7.3 Assessing Normality. Online normal distribution/z-score practice and graph review. | Thu, June 25 Chapter 8 Overview/Objectives; Section 8.1 Distribution of the Sample Mean; Section 8.2 Distribution of the Sample Proportion. Due: Chapter 7 Homework/Pass Quiz; Chapter 8 Homework/Pass Quiz; Project Part 1 - EDA and Descriptive Statistics. |
| Week 5 June 30-July 2 | Tue, June 30 Chapter 9 Overview/Objectives; Section 9.1 Estimating a Population Proportion; Section 9.2 Estimating a Population Mean. | Wed, July 1 ONLINE Chapter 9: Section 9.3 Estimating a Population Standard Deviation. Confidence interval lab using Pew data. | Thu, July 2 Chapter 10 Overview/Objectives; Section 10.1 Language of Hypothesis Testing; Section 10.2 Hypothesis Tests for a Population Proportion. Due: Chapter 9 Homework/Pass Quiz; Project Part 2 - Probability. |
| Week 6 July 7-9 | Tue, July 7 Chapter 10 continued: Section 10.3 Hypothesis Tests for a Population Mean; Section 10.4 Hypothesis Tests for a Population Standard Deviation. Practice the 5-step hypothesis testing method. | Wed, July 8 ONLINE Hypothesis testing lab; compare assigned sample results to Pew national benchmark; confidence interval and p-value practice. | Thu, July 9 Chapter 11 Overview/Objectives; Section 11.1 Inference about Two Population Proportions; Section 11.2 Inference about Two Means - Dependent Samples; Section 11.3 Inference about Two Means - Independent Samples. Due: Chapter 10 Homework/Pass Quiz; Chapter 11 Homework/Pass Quiz; Project Part 3 - Confidence Intervals and Hypothesis Testing. |
| Week 7 July 14-16 | Tue, July 14 Chapter 12 Overview/Objectives; Section 12.1 Goodness-of-Fit Tests; Section 12.2 Tests for Independence and Homogeneity. | Wed, July 15 ONLINE Chapter 13 Overview/Objectives/Lesson; One-Way ANOVA introduction; final paper and poster workshop; peer review/upload draft. | Thu, July 16 Chapter 13 continued/review; course synthesis; final project writing and presentation preparation. Due: Chapter 12 Homework/Pass Quiz; Chapter 13 Homework/Pass Quiz; Project Part 4 - Final Paper and Excel File. |
| Week 8 July 21-23 | Tue, July 21 Final Presentations - Group A. Students present final poster or poster-style slides and discuss data story, graphs, confidence intervals, p-values, and hypothesis decisions. | Wed, July 22 ONLINE Final reflection, peer feedback, and optional poster upload/rehearsal discussion. Students who presented Tuesday complete peer response/reflection; students presenting Thursday complete final rehearsal. | Thu, July 23 Final Presentations - Group B; course wrap-up; final questions; closing reflection. Due: Final Presentation for assigned group. |
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.