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Introduction to Statistical Analysis: Hypothesis Testing

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Introduction to Statistical Analysis: Hypothesis Testing

Ce cours fait partie de Certificat Professionnel SAS Statistical Business Analyst

Enseigné en Français (doublage IA)

Instructeur : Jordan Bakerman

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3 modules

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3 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

175 avis

niveau Intermédiaire

Certaines connaissances prérequises

Planning flexible

1 semaine à 10 heures une semaine

Apprenez à votre propre rythme

96%

La plupart des étudiants ont apprécié ce cours

Compétences que vous acquerrez

Catégorie : Statistical Modeling
Catégorie : Plot (Graphics)
Catégorie : Regression Analysis
Catégorie : Statistical Hypothesis Testing
Catégorie : Data Wrangling
Catégorie : Statistical Methods
Catégorie : Model Evaluation
Catégorie : Statistical Analysis
Catégorie : Sampling (Statistics)
Catégorie : Exploratory Data Analysis
Catégorie : Statistical Inference
Catégorie : Predictive Modeling
Catégorie : Correlation Analysis
Catégorie : Predictive Analytics
Catégorie : Statistical Programming

Outils que vous découvrirez

Catégorie : Statistical Software
Catégorie : SAS (Software)
Catégorie : Graphical Tools

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27 devoirs

Enseigné en Français (doublage IA)

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Ce cours fait partie de la Certificat Professionnel SAS Statistical Business Analyst

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Il y a 3 modules dans ce cours

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.

Détails du module

Welcome! We'll get started with a brief overview of the course and set up data you need to do the practices in this course. Then, you will learn about the models required to analyze different types of data and the difference between explanatory vs predictive modeling. You will 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.

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19 vidéos6 lectures8 devoirs

19 vidéosTotal 54 minutes

Welcome and Meet the Instructor2 minutes
Demo: Exploring Ames Housing Data11 minutes
Overview1 minute
Statistical Modeling: Types of Variables1 minute
Overview of Models3 minutes
Explanatory versus Predictive Modeling1 minute
Population Parameters and Sample Statistics2 minutes
Normal (Gaussian) Distribution3 minutes
Standard Error of the Mean1 minute
Confidence Intervals2 minutes
Statistical Hypothesis Test4 minutes
p-Value: Effect Size and Sample Size Influence3 minutes
Scenario1 minute
Performing a t Test4 minutes
Demo: Performing a One-Sample t Test Using PROC TTEST4 minutes
Scenario1 minute
Assumptions for the Two-Sample t Test2 minutes
Testing for Equal and Unequal Variances2 minutes
Demo: Performing a Two-Sample t Test Using PROC TTEST5 minutes

6 lecturesTotal 51 minutes

Learner Prerequisites1 minute
Access SAS Software and Set up Data (REQUIRED)10 minutes
Completing Demos and Practices10 minutes
Course Logistics FAQs10 minutes
Parameters and Statistics10 minutes
Normal Distribution10 minutes

8 devoirsTotal 145 minutes

Knowledge Check: Statistical Modeling15 minutes
Knowledge Check: Statistical Concepts15 minutes
Knowledge Check: Hypothesis Test & p-value15 minutes
Knowledge Check: One-Sample t Tests15 minutes
Using PROC TTEST to Perform a One-Sample t Test20 minutes
Knowledge Check: Two-Sample t Tests15 minutes
Practice - Using PROC TTEST to Compare Groups20 minutes
Introduction and Review of Concepts30 minutes

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.

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29 vidéos2 lectures14 devoirs

29 vidéosTotal 70 minutes

Overview1 minute
Scenario1 minute
Identifying Associations in ANOVA with Box Plots2 minutes
Demo: Exploring Associations Using PROC SGPLOT2 minutes
Identifying Associations in Linear Regression with Scatter Plots1 minute
Demo: Exploring Associations Using PROC SGSCATTER2 minutes
Scenario1 minute
The ANOVA Hypothesis1 minute
Partitioning Variability in ANOVA2 minutes
Coefficient of Determination1 minute
F Statistic and Critical Values2 minutes
The ANOVA Model3 minutes
Demo: Performing a One-Way ANOVA Using PROC GLM7 minutes
Scenario1 minute
Multiple Comparison Methods3 minutes
Tukey's and Dunnett's Multiple Comparison Methods2 minutes
Diffograms and Control Plots1 minute
Demo: Performing a Post Hoc Pairwise Comparison Using PROC GLM7 minutes
Scenario1 minute
Using Correlation to Measure Relationships between Continuous Variables1 minute
Hypothesis Testing for a Correlation1 minute
Avoiding Common Errors When Interpreting Correlations5 minutes
Demo: Producing Correlation Statistics and Scatter Plots Using PROC CORR6 minutes
Scenario1 minute
The Simple Linear Regression Model1 minute
How SAS Performs Simple Linear Regression1 minute
Comparing the Regression Model to a Baseline Model2 minutes
Hypothesis Testing and Assumptions for Linear Regression1 minute
Demo: Performing Simple Linear Regression Using PROC REG7 minutes

2 lecturesTotal 20 minutes

What Does a CLASS Statement Do?10 minutes
Correlation Analysis and Model Building10 minutes

14 devoirsTotal 155 minutes

Question 2.015 minutes
Question 2.025 minutes
Question 2.035 minutes
Question 2.045 minutes
Practice - Performing a One-Way ANOVA20 minutes
Question 2.055 minutes
Question 2.065 minutes
Practice - Using PROC GLM to Perform Post Hoc Parwise Comparisons20 minutes
Question 2.075 minutes
Question 2.085 minutes
Practice - Describing the Relationship between Continuous Variables20 minutes
Question 2.095 minutes
Practice - Using PROC REG to Fit a Simple Linear Regression Model20 minutes
ANOVA and Regression30 minutes

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.

Inclus

13 vidéos1 lecture5 devoirs

13 vidéosTotal 43 minutes

Overview2 minutes
Scenario1 minute
Applying the Two-Way ANOVA Model4 minutes
Demo: Performing a Two-Way ANOVA Using PROC GLM7 minutes
Interactions3 minutes
Demo: Performing a Two-Way ANOVA With an Interaction Using PROC GLM6 minutes
Demo: Performing Post-Processing Analysis Using PROC PLM4 minutes
Scenario1 minute
The Multiple Linear Regression Model3 minutes
Hypothesis Testing for Multiple Regression1 minute
Multiple Linear Regression versus Simple Linear Regression3 minutes
Adjusted R-Square2 minutes
Demo: Fitting a Multiple Linear Regression Model Using PROC REG7 minutes

1 lectureTotal 10 minutes

The STORE Statement10 minutes

5 devoirsTotal 80 minutes

Question 3.015 minutes
Practice - Performing a Two-Way ANOVA Using PROC GLM20 minutes
Question 3.025 minutes
Practice - Performing Multiple Regression Using PROC REG20 minutes
More Complex Linear Models30 minutes

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