SAS
Introduction to Statistical Analysis: Hypothesis Testing
SAS

Introduction to Statistical Analysis: Hypothesis Testing

Jordan Bakerman

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

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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
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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 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)
Jordan Bakerman
SAS
4 Courses42,408 learners

Offered by

SAS
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4.6

82 reviews

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WT
5

Reviewed on Sep 21, 2021

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5

Reviewed on Apr 28, 2022

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5

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Recommended if you're interested in Data Science

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