Lecture7_sampling

# Lecture7_sampling - STAT 350 LECTURE 7 Sampling POPULATION...

This preview shows pages 1–8. Sign up to view the full content.

STAT 350 L ECTURE 7 Sampling

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
P OPULATION VS SAMPLE Example: Presidential Election Population all eligible voters Sample a subset of all eligible voters Statistical Inference Generalizations from the sample to the population Impractical to study the whole population Example of (Population) Parameters: The average age of all eligible voters The percentage of all eligible voters who are currently registered to vote
S TATISTICS Statistics: Numbers which can be computed from a sample Example: A sample of 10,000 Americans We can compute two statistics: The average age of all eligible voters in the sample The percentage of all eligible voters in the sample who are currently registered to vote Statistics are what we know Parameters are what we want to know

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
T HE L ITERARY D IGEST P OLL The 1936 Presidential Election Franklin D. Roosevelt vs Alfred Landon The Literary Digest Poll Predicted an overwhelming victory for Landon Predicted Roosevelt getting 43% of popular vote Based on 2.4 million individuals (largest ever) Digest had called the winner in every presidential election since 1916 But … Roosevelt won the 1936 election by a landslide 62% to 38%
G ALLUP S POLL Sample of 50,000 people Correctly forecasted Roosevelt victory Summery of 1936 Election Roosevelt’s Percentage The election result 62 Digest’s Prediction 43 Gallup’s Prediction 56

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
S ELECTION B IAS Digest’s Procedure: Mail questionnaires to 10 million people These names and addresses were from telephone books and club membership Back in 1936, ¼ household had a telephone Strong selection bias against the poor When a selection procedure is biased, taking a large sample does not help.
N ON - RESPONSE BIAS Non-response bias -- A large number of those selected for the sample do not respond to the questionnaire or the interview.

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

### What students are saying

• As a current student on this bumpy collegiate pathway, I stumbled upon Course Hero, where I can find study resources for nearly all my courses, get online help from tutors 24/7, and even share my old projects, papers, and lecture notes with other students.

Kiran Temple University Fox School of Business ‘17, Course Hero Intern

• I cannot even describe how much Course Hero helped me this summer. It’s truly become something I can always rely on and help me. In the end, I was not only able to survive summer classes, but I was able to thrive thanks to Course Hero.

Dana University of Pennsylvania ‘17, Course Hero Intern

• The ability to access any university’s resources through Course Hero proved invaluable in my case. I was behind on Tulane coursework and actually used UCLA’s materials to help me move forward and get everything together on time.

Jill Tulane University ‘16, Course Hero Intern