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Statistics 151 – Course Outline Fall 2024
STATISTICS 151 – INTRODUCTION TO APPLIED STATISTICS I (Fall 2024)
Course Description: STAT 151 is an introductory statistics course focusing on statistical reasoning and data analysis.
Topics include: Data collection and presentation, descriptive statistics, probability distributions, sampling distributions, and the Central Limit Theorem. Point estimation, confidence interval and hypothesis testing. Correlation and regression analysis. ANOVA. Goodness offit and contingency tables.
Course Prerequisite: Mathematics 30-1 or 30-2. It is important to prepare yourself for this course through a review of the prerequisite material. Students who do not have the required prerequisites at the time of taking this course should not expect supplementary professorial tutoring from the instructor.
Notes: (1) Credit can be obtained in at most one of STAT 151, STAT 161, and STAT 235. (2) This course may not be taken for credit if credit has been obtained in STAT 222, STAT 266, STAT 276, KIN 109, PEDS 109, PSYCH 211, PTHER 352, SCI 151 or SOC 210.
Course Objectives and Expected Learning Outcomes: This course provides an introduction to statistical methods and their applications. The main topics are: obtaining and summarizing data with graphs and numeric measures, probability theory, and statistical inference (drawing conclusions from sample data by calculating a confidence interval and/or carrying out a hypothesis test). This course also comes with lab assignments; students will use a computer program, R COMMANDER, as a tool to further help their understanding of statistical analysis. At the end of this course, students should be able to make objective decisions based upon statistical data.
Course Delivery:
- Students are highly recommended to go through the online course materials according to the tentative schedule.
- For students who prefer to learn by reading a textbook, you are recommended to go over the module/ interactive textbook through the link called “Modules/Interactive Textbook” on eClass.
- For students who prefer a lecture style of learning, you are recommended to download my notes and watch the videos from the link called “Notes and Videos” in the “ Lecture Notes and Videos” block on eclass.
- Depending on the interest of students, I may host a few online review seminars through Zoom from time- to-time. During which, I plan to review some important concepts and examples with students.
Required Course Materials:
1) R Commander: free to download
a) You will need to download R (another free statistical software) to install R Commander. To learn more about how to download R Commander, read the introductory lab manual and watch the
video for Installing R Commander in the Labs section on eClass.
b) Students can access R to open R Commander online through eClass. Please visit the link “R & R
Commander (Online access)” in the Lab sections on eClass for access. There is a guide right below this link that explains how to use the online access.
c) Students can also work on their lab assignments at the computer labs on the 3rd floor of CAB.
2) A non-programmable calculator (for your exams).
Extra Required Course Materials (For Online Learning):
1) Desktop/Laptop
2) Webcam & Microphone (you don’t have to purchase them if both of these come with your desktop/laptop; if not, please purchase an external USB webcam that comes with a microphone)
3) Internet
4) SEM through Google Chrome
Recommended Textbook and References:
1) eBook – can be purchased through eClass
Title: Stats: Data and Models (3rd Edition)
Author: Richard D. De Veaux et al
ISBN: 9780135641835
Suggested list price: $65.00
Recommended or Optional Learning Resources:
1) Practice midterm and final exams will be posted on eClass.
Optional Online Learning Resources:
Additional learning resources aimed at facilitating student learning, and perhaps including formative assessment tools, are available from the textbook publisher and may be accessed for a fee paid by the student to the third-party provider (e.g., the textbook company). Students choosing to access and use the online resources should note the following:
1. Registration in the system and any monetary transactions are of your own accord and not the responsibility of the University.
2. Students should be mindful of protecting their personal information and should be aware of how their personal information might be used and/or shared.
3. Students MUST NOT use their @ualberta email address or CCID to register into the system and instead should use a non-identifying email address or account.
Syllabus: Here is the tentative outline with the approximate number of hours indicated for each topic.
|
Module |
Description |
Hours |
|
1-1 |
Introduction |
1 |
|
1-2 |
Data and Variables |
1 |
|
1-3 |
Gathering Data (Assigned Reading) |
0 |
|
2 |
Descriptive Statistics |
3 |
|
3 |
Normal Distribution |
3 |
|
4 |
Probability, Probability Models, and Linear Combinations (E(aX ± bY) and V(aX ± bY)) |
6 |
|
5 |
Sampling Distributions |
2 |
|
6 |
Inference for Proportion(s) |
5 |
|
7 |
Chi-Square Tests |
3 |
|
8 |
Inference for Mean(s) (including both pooled and non-pooled tests) |
6 |
|
9 |
ANOVA |
2 |
|
10 |
Simple Linear Regression |
2 |