'Equal variances' diaporamas de présentation

Chapter 11

Chapter 11. Introduction to Linear Regression and Correlation Analysis. Chapter 11 - Chapter Outcomes. After studying the material in this chapter, you should be able to: Calculate and interpret the simple correlation between two variables. Determine whether the correlation is significant.

1.17k views • 58 slides

Theoretical Quantum Optics - In Two Lectures

1.07k views • 54 slides

Learning Using Augmented Error Criterion

Learning Using Augmented Error Criterion . Yadunandana N. Rao Advisor: Dr. Jose C. Principe. AEC. Criterion. MSE. AEC Algorithms. Algorithm. LMS/RLS. Topology. FIR, IIR. Overview. Linear Adaptive Systems. Why another criterion?.

602 views • 44 slides

ANOVA Procedures

ANOVA (1 way) An extension of the 2 sample t-test used to determine if there are differences among > 2 group means ANOVA with trend test Test for polynomial trend in the group means ANOVA (2 way) Evaluate the combined effect of 2 experimental factors ANOVA repeated measures

1.28k views • 42 slides

Real Statistics Using Excel

Real Statistics Using Excel. 102521088 ? ??. Out line . Confidence and prediction intervals for regression Exponential Regression Model Power Regression Model Linear regression models for comparing means. Confidence and prediction intervals for regression.

647 views • 39 slides

The T-Test for Two Independent Samples

The T-Test for Two Independent Samples. Introduction to Statistics Chapter 10 Oct 20-22, 2009 Classes #18-19. A limitation of the t-test from chapter 9. Referred to as the one-sample t-test because can only test hypotheses concerning one sample

1.19k views • 38 slides

Comparing Two Population Means

Comparing Two Population Means. Two kinds of studies or experiments. There are two general research strategies that can be used to compare the two populations of interest:

758 views • 36 slides

Simple Statistical Designs

Simple Statistical Designs. One Dependent Variable. If I have one Dependent Variable, which statistical test do I use? . Is your Dependent Variable (DV) continuous?. YES. NO. Is your Independent Variable (IV) continuous?. Is your Independent Variable (IV) continuous?. YES. NO. YES. NO.

498 views • 36 slides

ENGR 610 Applied Statistics Fall 2007 - Week 9

ENGR 610 Applied Statistics Fall 2007 - Week 9. Marshall University CITE Jack Smith. Overview for Today. Review Design of Experiments , Ch 10 One-Factor Experiments Randomized Block Experiments Go over homework problems: 10.27, 10.28 Design of Experiments , Ch 11

515 views • 34 slides

ANALYSIS OF VARIANCE

ANALYSIS OF VARIANCE . Analysis of variance. A One-way Analysis Of Variance Is A Way To Test The Equality Of Three Or More Means At One Time By Using Variances.

562 views • 28 slides

T Test Jeopardy

379 views • 27 slides

Workshop: Statistical Consulting & Research Center

Workshop: Statistical Consulting & Research Center. November 1, 2012. Introduction. Randy Kolb Coordinator of Statistical Consulting Group, LR&TS, Rkolb@stcloudstate.edu Statistical Assistants: Two Graduate Assistants: Sara Brodeur and Kristin Brietzke

388 views • 27 slides

One-Way and Factorial ANOVA

642 views • 26 slides

Teaching Stroke Classification

578 views • 24 slides

Classroom Simulation: Are Variance-Stabilizing Transformations Really Useful?

528 views • 24 slides

Part IVA

Part IVA Analysis of Variance (ANOVA) Dr. Stephen H. Russell Weber State University Introduction to the concept of ANOVA

1.42k views • 23 slides

Chapter 13

Chapter 13. Factorial Analysis of Variance. Basic Logic of Factorial Designs and Interaction Effects. Factorial research design Effect of two or more variables examined at once Efficient research design Interaction effects Combination of variables has a special effect.

237 views • 23 slides

Chapter 10

Chapters 1. Introduction 2. Graphs 3. Descriptive statistics 4. Basic probability 5. Discrete distributions 6. Continuous distributions 7. Central limit theorem 8. Estimation 9. Hypothesis testing 10. Two-sample tests 13. Linear regression

346 views • 21 slides

Five-step model for Testing Hypotheses

Five-step model for Testing Hypotheses. The five-step model used for all hypothesis tests contains the following steps: Step 1. Evaluating assumptions. Step 2. Stating the research hypothesis and the null hypothesis and setting alpha

1.63k views • 13 slides

Statistics and Data Analysis

Statistics and Data Analysis. Professor William Greene Stern School of Business IOMS Department Department of Economics. Statistics and Data Analysis. Statistical Tests: Variances. Equal Variance Assumption.

240 views • 9 slides