Business Statistics

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Business Statistics

• Course Overview

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In this course you will learn to

• Organize Data
• Analyze Data
• Reach Conclusions from Data

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Why? Because

• Thinking with numbers is essential in business
  and in life
• Being able to translate raw data into valid
  general conclusions adds value to processes
• Making decisions founded in reason, logic and
  observed evidence is expected due diligence

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Why is this a GE course?

• Both the private sector and society value
  effective and ethical problem solvers
• The state of California thus mandates that an
  educated citizen be able to solve problems and
  validly analyze situations with properly
  collected data

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Course Outline

• Organize Data
• Two questions
• What is happening? VALUE
• How often? FREQUENCY

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Course Outline

• Organize Data
• Visually (chapter 2)
• Create Frequency Tables
• Graph, Chart or Plot value versus frequency from
  Frequency Tables

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Course Outline

• Organize Data
• Numerically (Chapter 3)
• Statistical Measures of Central Tendency,
  Dispersion, Location, and Association.
• Frequency Measures Empirical Rule and
  Chebyshevs Theorem
• Distribution Qualifiers Skewness versus Symmetry

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Course Outline

• Analyze Data
• Probability Theory (Chapter 4)
• Rules of Probability Marginal, Conditional,
  Multiplication and Addition
• Events Complement, dependent, independent,
  mutually exclusive

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Course Outline

• Analyze Data
• Counting Rules (Chapter 4 and notes)
• Fundamental
• Factorial
• Shuffles or Permutations
• Combinations

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Course Outline

• Analyze Data
• Probability Distributions (Chapters 5 and 6)
• Properties mean, median, mode, variance,
  standard deviation
• Probabilities
• Special Case (5) Binomial processes
• Special Case (6) Normal populations

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Course Outline

• Analyze Data
• Sampling Distributions (Chapter 7)
• For sample means, s known
• For sample means, s unknown
• For sample proportions

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Course Outline

• Inference
• Confidence Interval Estimation (Chapter 8)
• For sample means, s known
• For sample means, s unknown
• For sample proportions

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Course Outline

• Inference
• Hypothesis Testing (Chapters 9-11)
• For population means, s known (9)
• For population means, s unknown (9)
• For population proportions (9)
• For the difference between two population means
  or proportions (10)
• For multiple (3) proportions (11)

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Course Outline

• Inference
• Simple Linear Regression (Chapter 12)

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Course Outline

• Inference
• Intermediate Topics
• More Hypothesis Tests
• F tests ANOVA (from notes)
• Multiple Regression Analysis (Chapter 13)