Introductory Statistics: Course Syllabus and Key Learning Outcomes

Course Overview

This course, Introduction to Statistics (STAT-C1000E), provides a comprehensive foundation in the principles and methods of statistics. Students will learn to collect, organize, analyze, and interpret data, as well as apply probability and inferential techniques to real-world problems. The course emphasizes both theoretical understanding and practical application using calculators and statistical software.

Key Topics and Learning Outcomes

• Scales of Measurement: Understand and distinguish between nominal, ordinal, interval, and ratio scales, and recognize their implications for data analysis.

• Data Representation: Interpret and construct tables and graphical displays such as histograms, bar charts, and boxplots.

• Probability Concepts: Apply the concepts of sample space, events, and probability rules to calculate probabilities in various contexts.

• Descriptive Statistics: Calculate and interpret measures of central tendency (mean, median, mode) and measures of variation (range, variance, standard deviation).

• Data Collection Methods: Identify standard methods for obtaining data (e.g., surveys, experiments, observational studies) and evaluate their advantages and disadvantages.

• Discrete Probability Distributions: Calculate the mean and variance for discrete random variables and apply probability distributions such as the binomial and Poisson distributions.

• Normal and t-Distributions: Calculate probabilities and critical values using the normal and t-distributions.

• Sampling Distributions and the Central Limit Theorem: Distinguish between sample and population distributions and understand the role of the Central Limit Theorem in inferential statistics.

• Confidence Intervals: Construct and interpret confidence intervals for population parameters.

• Hypothesis Testing: Understand the basic concepts of hypothesis testing, including null and alternative hypotheses, type I and type II errors, and p-values. Formulate and conduct hypothesis tests for one and two populations.

• Statistical Significance: Determine and interpret levels of statistical significance, including the use of p-values.

• Regression and Correlation: Use linear regression techniques for estimation and inference, and interpret correlation coefficients.

• Goodness-of-Fit and Contingency Tables: Analyze categorical data using chi-square tests for goodness-of-fit and independence.

• Analysis of Variance (ANOVA): Apply ANOVA techniques to compare means across multiple groups.

• Technology in Statistics: Interpret the output of technology-based statistical analyses, including calculator and software results.

• Applications: Apply statistical techniques to data from various disciplines, including business, social sciences, psychology, life sciences, and education.

Course Structure and Assessment

• Textbook: Elementary Statistics (14th Edition) by Mario Triola (Pearson Publishing). Includes access to MyStatLab for online homework and resources.

• Calculator: TI-84, TI-84 Plus, TI-83, or TI-83 Plus graphing calculator required. Virtual versions are available online.

• Homework: Consists of recommended (ungraded) and required (graded, mostly online) assignments. Practice is essential for mastering concepts.

• Exams: Four midterm exams (lowest score dropped) and a comprehensive final exam. No calculator sharing during exams.

• Grading Breakdown:

Component	Weight
Homework	20%
Classwork	10%
Midterms	50%
Final Exam	20%

• Grading Scale:

Grade	Percentage
A	90% or above
B	80% - 89.9%
C	70% - 79.9%
D	60% - 69.9%

Exam Schedule and Covered Chapters

Exam	Chapters Covered	Date
Midterm 1	Ch. 1, 2, 3	16 Sep.
Midterm 2	Ch. 4, 5	7 Oct.
Midterm 3	Ch. 6, 7	28 Oct.
Midterm 4	Ch. 8, 9	23 Nov.
Final Exam	All above & 11.1, 11.2, 12.1	9 Dec.

Course Policies and Resources

• Attendance: Regular attendance is strongly recommended for success. Notify the instructor of absences due to religious or school-related events.

• Academic Integrity: Cheating results in a zero for the assignment and notification to the dean.

• Math Lab/Learning Center: Free drop-in tutoring and group help available on campus.

• Inclusivity and Accommodation: The course adheres to college policies on non-discrimination and provides accommodations for students with disabilities.

• Cellphone Policy: Cell phone use is prohibited during class and exams.

Summary Table: Chapters and Main Topics

Chapter	Main Topic
1	Introduction to Statistics
2	Exploring Data with Tables and Graphs
3	Describing, Exploring, and Comparing Data
4	Probability
5	Discrete Probability Distributions
6	Normal Probability Distributions
7	Estimating Parameters and Determining Sample Sizes
8	Hypothesis Testing
9	Inferences from Two Samples
10	Correlation and Regression
11	Goodness-of-Fit and Contingency Tables
12	Analysis of Variance

Additional Information

• Students are encouraged to use online resources and calculator tutorials provided by the instructor.

• All course materials, updates, and handouts will be posted on Canvas.

• Students are responsible for making up missed assignments and reviewing posted materials after absences.

Good luck in your study of statistics!