Course Syllabus

 

The course syllabus has been one of the most recognized tools that facilitate the learning process in higher education. The syllabus is a roadmap for you to understand what you “will have to do” to complete a course. The syllabus is also an agreement or even a legal contract between you and me. If you stay enrolled in a course, de facto, you agree to abide by the syllabus. Similarly, I agree to follow and execute in good faith the terms of the syllabus as presented. 

 

STATISTICAL TECHNIQUES

SPEA K300 19372 – Fall 2026

Name:	Su Jin Park (Dr. P) Meet your instructor
Email:	park268@iu.edu
Office Hours:  Virtual Office:	By appointment via Zoom

 

• • The most important tip for a successful class is the active interaction and communication between you and me, though this class runs online.
  • I am available to meet with you by appointment via zoom during this semester. Contact me via email to set up a time.
  • When you email me, please indicate the reason you reach me in the title of your email, including the course name and number: e.g., “K300_19372_Office hour request”/ “K300_19372_Assignment question”.
  • Using Canvas Inbox is the best way to contact me; it indicates which course the mail comes from.
  • I will do my best to respond as soon as possible, yet please allow me a 24-hour turn-around time at least. Also, the last-minute emails on the due night (Sunday night) are highly likely not to be read right away.

 

 Course Description

Just as it is fair to assume that high school graduates can read and write, it is assumed that college graduates can understand and use a fundamental statistical and quantitative method of analysis. In fact, most college students are afraid of statistics and believe that statistics is math/formula and too difficult and complicated to learn. However, when students navigate inside the statistics world, they realize that statistics is not a knotty subject because the process toward a solution and the interpretation of outcomes are quite straightforward.

This course is designed to provide students with basic skills and knowledge for statistical analysis and evaluation/interpretation. Topics covered in this class include (but are not limited to) the following:

• • • • Nature of statistics and research design
      • Descriptive statistics (including graphs and tables, measure of central tendency, and measure of variation and position),
      • Probability and probability distribution (discrete vs. continuous)
      • Sampling Distribution of Sample Means and Central Limit Theorem
      • Inferential statistics
        • Confidential Interval
        • Hypothesis Testing
        • Means Difference test
      • Correlation and Regression
      • Chi-square test
      • Analysis of Variance

 

 Course Goals

The focus of this course is on understanding and getting used to statistical terminology, applying different statistical techniques for different problems, interpreting statistical outcomes, and ultimately conducting an independent research analysis based on his or her research interest and research question. 

 

 Course Objectives

Upon successful completion of this course, students should be able to:

• • • explain the vocabulary and concepts of basic statistical methods (i.e. population (parameter) vs. sample (statistic), level of measurement, unit of analysis, sampling technique, and descriptive statistics vs. inferential statistics) used in a profession or academic environment and identify them in reality
    • apply basic statistical techniques for data analysis in solving practical and real problem including how to collect data, how to describe and present the data using graphs and table, and how to compute the central tendency and variation
    • understand the critical rule of probabilities (i.e., addition, multiplication, complementary, and conditional probability)
    • compute the probabilities from probability distribution (especially (standard) normal distributions and t distribution) using Central Limit Theorem
    • estimate population parameter using Confidential Interval
    • make and analyze students’ own hypotheses (as well as given problems); conduct a hypothesis test (including traditional hypothesis test, p-value approach, and confidence interval approach)
    • test whether there is a difference between two groups
    • test whether there is a correlation between independent variable and dependent variable; identify the strength, direction, and degree of the correlation; develop a regression model for linear data
    • find regression equation and interpret the marginal change from slope
    • test a distribution for goodness of fit, using chi-square test.
    • use the ANOVA techniques to determine if there is a significant difference among three or more means.
    • eventually, interpret the regression equation outcome from any stat packages

 

Tentative Instruction Plan

 

Module 1: Introduction to Statistics (1 week)

• • • Unit 1: Overview of Statistics (population parameter vs. sample statistic, descriptive statistics vs. inferential statistics, level of measurement, etc.)
    • Unit 2: Research Design (experimental study vs. observational study, sampling techniques)
    • Unit 3: Misuse of statistics

Module 2: Descriptive Statistics (2 weeks)

• • • Unit 1: Frequency Distribution
    • Unit 2: Data Description (table and graphs)
    • Unit 3: Central Tendency
    • Unit 4: Measure of Variation
    • Unit 5: Measure of Position

Module 3: Probability Distributions (2 weeks)

• • • Unit 1: Probability (fundamental rule of probability)
    • Unit 2: Discrete Probability Distributions
    • Unit 3: Normal Probability Distributions

Module 4: Sampling Distribution and Central Limit Theorem (1 Week)

• • • Unit 1: Applications of Normal Distribution
    • Unit 2: Sampling Distribution
    • Unit 3: Central Limit Theorem

Module 5: Inferential Statistics (3 weeks)

• • • Unit 1: Confidence Intervals
    • Unit 2: Hypothesis Testing (traditional approach, p-value approach, and confidence interval approach)
    • Unit 3: Two-Sample Inference: Means Difference Test (t-test)

Module 6: Relationships among variables (2 weeks)

• • • Unit 1: Correlation (sample correlation coefficient, hypothesis testing)
    • Unit 2: Regression (computation of slope and intercept, coefficient of determination, standard error of estimate, prediction interval, interpretation of regression outcome, etc.)

Module 7: Chi-square and Analysis of Variance (2 weeks)

• • • Unit 1: Chi-square (test a distribution for goodness of fit and two variables for independence)
    • Unit 2: ANOVA (test if there is a significant difference among three or more means)

 

Prerequisite

• • There is no prerequisite. However, students should have a clear understanding of high school algebra and Microsoft Office applications (e.g. MS Word, Excel, and PowerPoint, etc.)
  • Particularly, you have to have a computer (PC or Mac) that has an MS Excel program.

 

Textbook

• • Bluman, Allen G. (2022). Elementary Statistics: A Step by Step Approach, 10^th Boston: MA, McGraw-Hill
  • You already purchased this textbook and ALEKS (online learning tool) through IU eText. IU eTexts is an IU-created initiative wherein Indiana University has partnered with publishers to offer licensed access to their titles digitally at a significant discount.
  • For more details about IU eText, refer to Student Guide to IU eText.

 

 

  ALEKS (On-line Learning Tool)

• • For active and adaptive learning, this class will utilize ALEKS (published by McGraw-Hill). ALEKS is an exciting, new assignment and assessment platform that helps you improve statistical skills. ALEKS includes a variety of digital educational resources such as workbooks, problem sets, tutorials, videos, simulations, and interactive software, etc.
  • All HOMEWORK ASSIGNMENTS, QUIZ, and EXAMS will be given through ALEKS only.

  • Class code: 94PA3-3T6CH

 

Grading

Grades will be determined as shown in the following assignment chart. 

Assignments	Points	Percentage
Syllabus Quiz	11 pts	1.1%
Homework (13 Assignments)	494pts (38pts*13)	49.4%
Quiz (13 Quizzes)	195pts (15pts*13)	19.5%
Exam	300pts (100pts*3)	30%
Total	1000 pts	100%

 

Grading Scale

No curves and roundings in grading are anticipated. Letter grades will be assigned according to the following point totals:

A	Points ≥ 93%
A-	90% ≤ Points < 93%
B+	87%  ≤ Points < 90%
B	83% ≤ Points < 87%
B-	80% ≤ Points < 83%
C+	77% ≤ Points < 80%
C	73% ≤ Points < 77%
C-	70% ≤ Points < 73%
D+	67% ≤ Points < 70%
D	63% ≤ Points < 67%
D-	60% ≤ Points < 63%
F	Points < 60%
FN	Failure for nonattendance
I	Incomplete
W	Withdraw

 

 

Assignment & Exam Schedule

 

Assignments	Due
Syllabus Quiz	Week 1 (8/24 – 8/30)
Weekly Homework Assignment	Every Sunday at 11:59 PM CST
Weekly Quiz	Every Sunday at 11:59 PM CST
First Midterm Exam	Week 7 (10/5 ~ 10/11)
Second Midterm Exam	Week 11 (11/2 ~ 11/8)
Final Exam	Week 17 (12/14 ~ 12/18)

 

Assignments

1. Homework Assignments

• • • You will have regular, required assignments in ALEKS, and you can expect to spend several hours a week working on them.
    • Understanding the homework assignments is critical in performing well on the quizzes and exams.
    • Students are required to turn in 13 homework assignments through ALEKS.com, which will be worth 38 points each (total 494 points, or 49.4%).
    • You will have Unlimited trials with Guided instruction (such as ‘guided solution’, ‘show example’ or ‘link to textbook’) and the highest score will be taken. Thus, I believe that you should have a perfect score on each homework assignment. During doing homework, you may check what you missed and make it up. Right after submitting it, you may get instant feedback.
    • You must complete the weekly homework assignment with at least 70% by Sunday at 11:59 PM CST. Only those who completed assignments with at least 70% are eligible to take a weekly quiz. If your score is below 70%, you are NOT eligible to take weekly quiz.
    • Note that even though the ALEKS will provide guided instruction, it will NOT directly provide an answer. If you use guided instructions, you would find slightly modified questions when you try it again since ALEKS is based on adaptive learning.

2. Quiz

• • • Statistics is like building blocks, which means that students cannot move forward without building a basic foundation. Accordingly, you have to check and review what you understand and miss frequently. If there is something missing or insufficient, you must catch up.
    • For this reason, students are required to take 13 quizzes through ALEKS.
    • Again, you are allowed to take a weekly quiz ONLY when you completed the weekly homework assignment with at least 70% as a prerequisite. If not, you must complete the homework assignment, first.
    • Unlike homework assignments, there will be no guided solutions (except for ‘link to textbook’ function).
    • This quiz should be done within 3 hours (I think 3 hours are sufficient).
    • Unlike homework assignments, you are not allowed to have unlimited trials. You will have only 1 trial. 
    • After reading the textbook and watching the video, do the weekly assignment. This will be the best strategy.
    • Several quiz questions will be reproduced in your exams.

 

3. Exams

• • • There will be 3 exams.
    • The first midterm exam, worth 10% of your final grade, will be done in week 7 (10/5 ~ 10/11)
    • The second midterm exam, worth 10% of your final grade, will be done in week 11 (11/2 ~ 11/8)
    • The final exam, worth 10% of your final grade, will be done in the final week (12/14 ~ 12/18)
  •  
    • Exams will include problems similar to those completed in your homework assignments or quizzes. Each exam will cover predominately the material covered until the prior class sessions, as listed in the syllabus.
    • The exam will be time-limited, and retaking will be allowed only ONCE, so you will have TWO attempts. Note that your second attempt must be FULL RETAKE, which means you must retake all questions.
    • Like a quiz, the guided solution will be limited only to ‘link to textbook.’ 
    • Details will be posted.

 

 

Weekly Schedule

 

WK	Module	Date	Topic	Related Readings §  B: Bluman eText	Assignments Due
1	1	8/24 ~ 8/30	§  Course Introduction §  The Nature of Statistics §  Descriptive and Inferential Statistics §  Variables and Types of Data §  Data Collection & Sampling Techniques §  Computers and Calculators	§  B – Ch.1-1, Ch1-2, 1-3, 1-4, 1-5	§  HW #1 by 8/30 §  Quiz #1 by 8/30 §  Syllabus Quiz by 8/30
2	2	8/31 ~ 9/6	§  Organizing Data §  Frequency Distribution §  Histograms, Frequency Polygons and Ogives §  Other Types of Graphs	§  B – Ch.2-1, 2-2, 2-3	§  HW #2 by 9/6 §  Quiz #2 by 9/6
3	3	9/7 ~ 9/13	§  Data Description §  Measures of Central Tendency §  Measures of Variation §  Measures of Position	§  B – Ch.3-1, 3-2, 3-3	§  HW #3 by 9/13 §  Quiz #3 by 9/13
4	4	9/14 ~9/20	§  Probability §  Sample Space and Probability §  Addition Rule for Probability §  Multiplication Rule for Probability & Conditional Probability	§  B – Ch.4-1, 4-2, 4-3	§  HW #4 by 9/20 §  Quiz #4 by 9/20
5	5	9/21 ~ 9/27	§  Probability Distribution §  Discrete Probability Distribution  §  Normal Distribution	§  B – Ch.5-1, 5-2 §  B – Ch.6-1	§  HW #5 by 9/27 §  Quiz #5 by 9/27
6	6	9/28 ~ 10/4	§  Application of the Normal Distribution §  Central Limit Theorem	§  B – Ch.6-2, 6-3	§  HW #6 by 10/4 §  Quiz #6 by 10/4
7		10/5 ~ 10/11	§  First Midterm Exam	§  B – Ch.1~6	§  Exam #1 by 10/11
8	7	10/12 ~ 10/18	§  Introduction of Inferential Statistics §  Confidence Interval for the Mean when σ is known §  Confidence Interval for the Mean when σ is unknown	§  B – Ch.7-1, 7-2	§  HW #7 by 10/18 §  Quiz #7 by 10/18
9	8	10/19 ~ 10/25	§  Introduction of Hypothesis Testing §  Steps for Hypothesis Testing §  Z test for a mean §  t-test for a mean	§  B – Ch.7-2, 7-3	§  HW #8 by 10/25 §  Quiz #8 by 10/25
10	9	10/26 ~ 11/1	§  Testing the difference between Two means: Using the z-test §   Testing the difference between Two means: Using the t-test	§  B – Ch.9-1, 9-2	§  HW #9 by 11/1 §  Quiz #9 by 11/1
11		11/2 ~ 11/8	§  Second Midterm Exam		§  Exam #2 by 11/8
12	10	11/9 ~ 11/15	§  Correlation	§  B – Ch.10-1	§  HW #10 by 11/15 §  Quiz #10 by 11/15
13	11	11/16 ~ 11/22	§  Regression §  Coefficient of Determination §  Standard Error of the Estimate	§  B – Ch.10-2, 10-3	§  HW #11 by 11/22 §  Quiz #11 by 11/22
14		11/23 ~ 11/29	Thanksgiving Week
15	12	11/30 ~ 12/6	§  Chi-Square Test	§  B – Ch.11-1, 11-2	§  HW #12 by 12/6 §  Quiz #12 by 12/6
16	13	12/7 ~ 12/13	§  Analysis of Variance §  One-way Analysis of Variance	§  B – Ch.12-1	§  HW #13 by 12/13 §  Quiz #13 by 12/13
Final Week		12/14 ~ 12/18	§  Final Exam	§  B – Ch.10 ~ Ch.12	§  Final exam by 12/18

 

Our full syllabus can be found HERE.