Transcript Document

QM 2113 -- Fall 2003
Statistics for Decision Making
Bivariate Descriptive Statistics
Instructor: John Seydel, Ph.D.
Student Objectives
Plot two related quantitative variables on a
scatterplot
Estimate the equation of the best fitting line
through a set of points
Relate the equation of a line through a set of
points to the relationship between the
variables being plotted
Use Excel to
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Determine the best fitting regression line
Quantify the fit of a straight line through points
Examine the relationship between two
qualitative variables
Administrative Chores
Homework from last week
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Return
Comments
This week’s homework
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Not being collected
Use to study for exam
Basis for discussion tonight
First exam is next week (descriptive statistics)
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Chapters 1-3 (selected portions, per assignments)
Chapter 11 (pages 425-429,434-446)
Excel procedures as discussed in class
Review: Data and Analysis
Statistics
Quantitative Data
Informal
Summary Measures
Inferential Analyses
Qualitative Data
Informal
Summary Measures
Inferential Analyses
The analyses can be univariate (one variable at a time), bivariate, or multivariate
Let’s Look at the Homework
Chapter 1 questions
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At this point, all you can do is quote the
text
However, these are good final exam
questions
Chapter 3:
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Let’s look at #15
Any others?
How about other aspects of the
assignment?
Bivariate Analyses: Quantitative
Variables
Informal analysis
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Scatterplot
Can infer relationship by looking at points
Formal analysis
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Regression
Involves formal means of describing
plotted line through points
Example: Great Northern Insurance
Bivariate Analyses: Qualitative
Variables
Informal analysis
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Joint frequency tables (crosstabulation)
Pie & bar charts
Formal analysis
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Requires understanding of basic probability
Beyond our scope for the moment
Example: KIVZ Television
Miscellaneous Statistics
Less important but need to be familiar with:
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Location
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Variation
 Median
 Mode
 Quantiles (percentiles, quartiles)
 Range
 Min and Max
 CV
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Both (?)
 Z-score
 Empirical Rule
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Other: skew
Let’s look at the homework related to this
Another Notation Quiz
Mean
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Sample
Population
Standard deviation
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Sample
Population
Variance
Range
Number of
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Observations
Elements in the population
Slope coefficient
Intercept
Proportion of variation explained by relationship
Average error from using regression equation for prediction
Summary of Objectives
Plot two related quantitative variables on a
scatterplot
Estimate the equation of the best fitting line
through a set of points
Relate the equation of a line through a set of
points to the relationship between the
variables being plotted
Use Excel to


Determine the best fitting regression line
Quantify the fit of a straight line through points
Examine the relationship between two
qualitative variables
Appendix
Recall Our Purposes Here
What is statistics all about?
It’s about dealing with variation
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Summarizing information (description)
Making decisions based upon that summarization
Type of analysis depends on data type
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Quantitative
Qualitative
Description
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Formal
 Numeric data: average and standard deviaiton
 Categorical data: percentages
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Informal: frequency tables and charts data