Transcript Overview of STAT 270

Overview of STAT 270
Ch 1-9 of Devore
+
Various Applications
Ch 1
• Overview and Descriptive Statistics
– Design (Data Collection)
– Descriptive Statistics
– Inference
• Descriptive Statistics
– Graphical
– Numerical
Ch 2
• Probability
– Random selection or allocation
– Models for variability
Ch 3
• Discrete Probability Distributions
– Models
– Relationships between models
– Applying Models
Ch 4
• Continuous Probability Distributions
– Models
– Normality (& why it is ubiquitous)
– Calculus of Probability
d
f (x) 
F (x)
dx
x
F (x) 


f ( x )dx
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TIFF (Uncompressed) decompressor
are needed to see this picture.
Ch 5
• Joint Probability Distributions
– Conditioning
– Independence
– Relationships between variables
f ( x, y )  24 xy
0  x 1
0  y 1
x  y 1
Ch 6
• Point Estimation (of parameters)
– What it is
– Why it is not enough
Mean estimate
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TIFF (Uncompressed) decompressor
are needed to see this picture.
Ch 7
• Interval Estimation
– What it is and what it is not
– Confidence
Interval Estimates
of the mean
Mean
Ch 8
• Hypothesis Testing
– When is an apparent result reproducible?
Ch 9
• Two sample hypothesis tests
More topics
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Simulation - modern inference
Time series - most common data set
Nonparametric smoothing - easy and useful
Analysis of variance - historical
Regression analysis - easy & useful
Quality control - management by exception
and reduction of variability