This introductory course is for SAS software users who perform statistical analyses using SAS/STAT software. The focus is on t tests, ANOVA, and linear regression, and includes a brief introduction to logistic regression.
Introduction to Statistical Analysis: Hypothesis Testing
Introduction to Statistical Analysis: Hypothesis Testing
This course is part of SAS Statistical Business Analyst Professional Certificate
Instructor: Jordan Bakerman
9,881 already enrolled
Course
Gain insight into a topic and learn the fundamentals
4.6
(82 reviews)
Intermediate level
No previous experience necessary
10 hours (approximately)
Flexible schedule
Learn at your own pace
Skills you'll gain
- Category: Multivariate Time Series Analysis
- Category: Multivariate Analysis
- Category: Multivariate Statistics
- Category: Predictive Modelling
Details to know
Shareable Certificate
Add to your LinkedIn profile
Quizzes and assessments
25 quizzes, 3 assessments
English
Subtitles: Arabic, French,
Course
Gain insight into a topic and learn the fundamentals
4.6
(82 reviews)
Intermediate level
No previous experience necessary
10 hours (approximately)
Flexible schedule
Learn at your own pace
Build your Data Science expertise
This course is part of the SAS Statistical Business Analyst Professional Certificate
When you enroll in this course, you'll also be enrolled in this Professional Certificate.
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate from SAS
There are 4 modules in this course
In this module you learn about the course and the data you analyze in this course. Then you set up the data you need to do the practices in the course.
What's included
2 videos5 readings
In this module you learn about the models required to analyze different types of data and the difference between explanatory vs predictive modeling. Then you review fundamental statistical concepts, such as the sampling distribution of a mean, hypothesis testing, p-values, and confidence intervals. After reviewing these concepts, you apply one-sample and two-sample t tests to data to confirm or reject preconceived hypotheses.
What's included
17 videos2 readings8 quizzes
In this module you learn to use graphical tools that can help determine which predictors are likely or unlikely to be useful. Then you learn to augment these graphical explorations with correlation analyses that describe linear relationships between potential predictors and our response variable. After you determine potential predictors, tools like ANOVA and regression help you assess the quality of the relationship between the response and predictors.
What's included
29 videos2 readings13 quizzes
In this module you expand the one-way ANOVA model to a two-factor analysis of variance and then extend simple linear regression to multiple regression with two predictors. After you understand the concepts of two-way ANOVA and multiple linear regression with two predictors, you'll have the skills to fit and interpret models with many variables.
What's included
13 videos1 reading4 quizzes
Instructor
Instructor ratings
4.8 (33 ratings)Offered by
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
Why people choose Coursera for their career
Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."
Learner reviews
Showing 3 of 82
4.6
82 reviews
- 5 stars
80.48%
- 4 stars
9.75%
- 3 stars
2.43%
- 2 stars
2.43%
- 1 star
4.87%
Recommended if you're interested in Data Science
You are Currently on slide 1
Open new doors with Coursera Plus
Unlimited access to 7,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
Join over 3,400 global companies that choose Coursera for Business
Upskill your employees to excel in the digital economy
Frequently asked questions
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
