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
20,130 already enrolled
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Gain insight into a topic and learn the fundamentals.
4.7
(164 reviews)
Intermediate level
Some related experience required
10 hours to complete
3 weeks at 3 hours a week
Flexible schedule
Learn at your own pace
Skills you'll gain
Details to know
Shareable certificate
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Assessments
28 assignments
Taught in English
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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.
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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 readings9 assignments
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 readings14 assignments
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 reading5 assignments
Instructor
Instructor ratings
4.6 (57 ratings)Offered by
Recommended if you're interested in Data Analysis
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University of California, Santa Cruz
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Showing 3 of 164
RM
5
Reviewed on Jun 14, 2021
Thank you so much to the instructor, Jordan Bakerman for teaching this course.
KK
4
Reviewed on Jan 23, 2021
If only...
PS
5
Reviewed on Sep 29, 2023
The Course was excellent. The study materials were very clear and understandable.
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