SAS

Statistics with SAS

Taught in English

33,076 already enrolled

Course

Gain insight into a topic and learn the fundamentals

Jordan Bakerman

Instructor: Jordan Bakerman

4.7

(286 reviews)

Intermediate level
Some related experience required
20 hours to complete
3 weeks at 6 hours a week
Flexible schedule
Learn at your own pace

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Assessments

61 quizzes

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There are 8 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 videos4 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 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 readings14 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 reading5 quizzes

In this module you explore several tools for model selection. These tools help limit the number of candidate models so that you can choose an appropriate model that's based on your expertise and research priorities.

What's included

11 videos3 readings4 quizzes

In this module you learn to verify the assumptions of the model and diagnose problems that you encounter in linear regression. You learn to examine residuals, identify outliers that are numerically distant from the bulk of the data, and identify influential observations that unduly affect the regression model. Finally, you learn to diagnose collinearity to avoid inflated standard errors and parameter instability in the model.

What's included

18 videos7 quizzes

In this module you learn how to transition from inferential statistics to predictive modeling. Instead of using p-values, you learn about assessing models using honest assessment. After you choose the best performing model, you learn about ways to deploy the model to predict new data.

What's included

11 videos1 reading4 quizzes

In this module you look for associations between predictors and a binary response using hypothesis tests. Then you build a logistic regression model and learn about how to characterize the relationship between the response and predictors. Finally, you learn how to use logistic regression to build a model, or classifier, to predict unknown cases.

What's included

25 videos18 quizzes

Instructor

Instructor ratings
4.7 (99 ratings)
Jordan Bakerman
SAS
4 Courses50,917 learners

Offered by

SAS

Recommended if you're interested in Data Analysis

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Showing 3 of 286

4.7

286 reviews

  • 5 stars

    83.21%

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    11.88%

  • 3 stars

    2.44%

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    0.69%

  • 1 star

    1.74%

SS
5

Reviewed on May 1, 2022

AS
5

Reviewed on Sep 4, 2019

LG
4

Reviewed on Jan 4, 2022

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