2. Samples, Surveys, and Results UNIT SELF-TEST QUESTIONS
Statistics and Data Analysis 2
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Correlation and Regressions
Samples, Surveys, and Results
Hypothesis Testing
BIAS
Volunteer
Convenience
Sample Frame
Undercoverage
Non- Respondents
4 Sampling Methods
Confidence Intervals
is about...
Asking Questions
Slope Triangles
Building a Simulation: 6 steps
Standard Deviation for Proportions
Sample Size
Sample Proportion
How can you sample badly?
What are the steps for designing a simulation?
What the different sampling methods?
How do you use the standard rule to determine the confidence interval?
What two things do the confidence interval tell you?
How do you find the standard deviation for a sample proportion?
Is the margin of error always the same?
UNIT SELF-TEST QUESTIONS

3. Notes Making a Simulation Steps for Simulation
What is the component to be repeated?
How will you model the outcome?
How will you simulate the trial?
State the response variable.
Run the trials.
State conclusion.

4. Sample Size
Population Sample Size 1, 5,
10,
50,
1,000,
Sample size is how many respondents you need to make good inference
Depends on:
margin of error you want
Confidence Interval you want
How much money and time you have
Common Equation for sample size:
n*p > and n*q > 10
n = sample size
p = mean proportion of the sampling distribution
q = 1 - p

5. Stratified Sample Break the population into groups
then take random samples from each group

6. Simple Random Sample SRS
a group of subjects (a sample) is selected from a larger group (a population).
Each individual is chosen by a random process (random number generator or a random number table)
Every type of group in the population is represented

7. Systematic Sample
Use a pattern to collect samples (every 4th person who walks by)

8. Notation Name Statistic Parameter Mean μ (pronounced “meeoo”)
Standard Deviation s
σ (sigma)
Correlation r
ρ (rho)
Regression Coefficient b
β (beta)
Proportion p