Chapter 10: Analysis of Variance:
Comparing More Than Two Means
10.1 Elements of a Designed Experiment
MA 214: Applied Statistics
10.2 The Completely Randomized Design
Instructor : Remus Oan
10.3 Multiple Comparisons of Means
10.4 The Randomized Block Des
Statistics
Chapter 7: Inferences Based on a
Single Sample: Estimation with
Confidence Interval
Where Weve Been
Populations are characterized by
numerical measures called parameters
Decisions about population
parameters are based on sample
statistics
Infer
Chapter 6: Sampling
Distributions
Where Weve Been
The objective of most statistical
analyses is inference
Sample statistics (mean, standard
deviation) can be used to make
decisions
Probability distributions can be used to
construct models of populations
M
Chapter 12
Multisample inference:
Analysis of Variance
Analysis
EPI809/Spring 2008
EPI809/Spring
1
Learning Objectives
1.Describe Analysis of Variance (ANOVA)
2.Explain the Rationale of ANOVA
3.Compare Experimental Designs
4.Test the Equality of 2 or More
+
Probability Distribution of Random
Error
Chapter 11
Sections 11.1-11.4
Click to Columna subtitle style
Rene edit Master (10-0123)
Valerie Bodden K. (10-0014)
8/9/11
+Section 11.1
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8/9/11
Page 560
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33
Probabilistic Models
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Key Terms:
n
Deterministic M
Chapter 11. Simple Linear Regression
11.1 Probabilistic Models
MA 214: Applied Statistics
11.2 Fitting the Model: The Least Squares Approach
Instructor : Remus Oan
11.3 Model Assumptions
11.4 Assessing the Utility of the Model: Making Inferences
About the
Chapter 10: Analysis of Variance:
Comparing More Than Two Means
10.1 Elements of a Designed Experiment
MA 214: Applied Statistics
10.2 The Completely Randomized Design
Instructor : Remus Oan
10.3 Multiple Comparisons of Means
10.4 The Randomized Block Des
Statistics
Chapter 8: Inferences Based on a
Single Sample: Tests of Hypotheses
Where Weve Been
Calculated point estimators of
population parameters
Used the sampling distribution of a
statistic to assess the reliability of an
estimate through a confidence