ECON/MGMT 201: Statistics
Review for Final Exam
 Introduction
 What are statistics?
 How can we use statistics?
 What issues can we address with statistics?
 Data
 Sources
 Descriptive Statistics
 Statistical Inference
 Descriptive Statistics
 Three main objectives
 accuracy
 transparency
 completeness
 Tabular and Graphical Methods
 Qualitative Data
 Quantitative Data
 Classes
 Numerical Methods
 Measures of Location
 Measures of Variability
 Measures of Relative Location
 Detecting Outliers
 Measuring the Relationship between Variables
 Weighted Mean
 Grouped Data

 Introduction to Probability
 What is probability?
 Determining the Probability Space
 Venn Diagrams
 Useful Equations
 P(A) + P(Ac) = 1
 P(AB) = P(A) + P(B) – P(AB)
 P(AB) = P(AB)/P(B)
 Bayes’ Rule (Theorem)

PAi B  
P Ai PB Ai 
P Ai  B 

P A1  B   ...  P An  B  P A1 PB A1  ...  P An PB An 
 Discrete Probability Distributions
 Conditions
 Attributes
 Types of Distributions
 Discrete Uniform


Binomial
Poisson
 Approximating the Binomial with the Poisson
 Continuous Probability Distributions
 Conditions
 Interpreting a Continuous Probability Density Function
 Types of Continuous Distributions
 Uniform Distribution
 Normal Distribution
 Standard Normal Distribution
 The Normal Approximation to the Binomial
 The Exponential Distribution
 Sampling and Sampling Distributions
 Statistical Inference
 Sampling
 Sampling Distributions
 The Sampling Distribution of x
 The Central Limit Theorem
 Point Estimation
 Properties of Point Estimators
 Biasedness/Unbiasedness
 Efficiency
 Consistency
 Interval Estimation
 What is interval estimation?
 Interval Estimation of a Population Mean
 Finite Populations
 Infinite Populations
 Basic Intuition: CLT example:
 Interval Estimation using Sample Means
 Margin of Error
 Choosing a Sample Size
 Dealing with Small Samples
 The t Distribution
 difference between t and normal
 Hypothesis Testing
 What is hypothesis testing?
 Null Hypothesis
 Alternative Hypothesis
 No certainty in hypothesis testing
 Type I and Type II Errors
 Testing Hypotheses
 Steps in Hypothesis Testing
 1. Determine H0 and Ha.
 2. Choose an appropriate test statistic

 3. Specify .
 4. Collect data and calculate the test statistic
 5. Interpret the test statistic.
 One-Tailed Tests: Large Samples
 Two-Tailed Tests: Large Samples
 Small Samples
 Tests About Proportions
Understanding Type II Errors
 Tests Concerning Two Populations
 Basic Intuition:
 Characteristics of the difference between two variables.
 Large Samples
 Small Samples
 Pooled Estimation
 Matched Samples
Final Exam Distribution
Topic
Probability
- Basic Probability
- Bayes’ Rule
- Poisson
- Exponential
- Binomial
Hypothesis Testing
- One Tailed Tests
- Two Tailed Tests
- Small Samples
- Large Samples
- One Population
- Two Populations
- Proportions
- Matched Samples
Questions
3.5
Points
34
5.5
66
Type
Numerical Problems
Short Answer
Questions
8
1
Points
92
8