1 / 11

chapter1

chapter1. basic_concepts. Population and sample. Population Target population Accessible population Sample Descriptive statistics vs. Census Inferential statistics: infer from the sample to the population. Data. Raw data: unprocessed Summary data Information: actionable

dbooth
Download Presentation

chapter1

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. chapter1 basic_concepts

  2. Population and sample • Population • Target population • Accessible population • Sample • Descriptive statistics vs. Census • Inferential statistics: infer from the sample to the population

  3. Data • Raw data: unprocessed • Summary data • Information: actionable • “Your LDL cholesterol is 189” • “OK, so what?” • “If you do nothing, the probability that you die of heart disease within 5 years is .65. Go to the gym now! Eat veggie now!”

  4. What is this? • Raw data (unprocessed) • Processed data • Information

  5. Variable • Opposite to constant • The value can vary • DV : outcome, response, criterion • IV : factor

  6. Example: • The campus pastor at John Smith University selects a random sample of 100 students in 2011 and invites them to participate in a survey about how often they engage in binge drinking. The response rate of the survey is 50%, meaning that 50 students responded to the invitation. The respondents report an average of 2.5 binge drinking episodes per week. The pastor reports, "The average level of binge drinking among all John Smith College students is about 2.5 episodes per week." • Which method did the pastor employ? Descriptive statistics or inferential statistics?

  7. This is inferential statistics because the analyst infers from the sample statistics to the population parameter.

  8. Example: • The admission officer at John Doe College checked the Scholastic Aptitude Test (SAT) math scores for all the students admitted in 2012 (mean = 640) and the SAT math scores for all the students admitted in 2013 (mean = 570) and concludes that the students admitted in 2012 had higher average SAT math scores than the students admitted in 2013.   • Which method did the admission officer employ? Descriptive statistics or inferential statistics?

  9. Strictly speaking, it is descriptive, but not descriptive statistics, because the data set contains the entire population. In other words, it is a census. We use the sample statistics to estimate the population parameters. But when we have the population parameters at hand, there is no need to make any estimation based on statistics.

  10. True and invariant population parameter? • A population parameter is said to be an invariant value. There is one and only one true parameter. But, is it true? • Let us assume that we can measure the height of every American male aged 18 or over. We draw the conclusion that the mean height of these men is 1.51 meters. However, this mean height is not a fixed constant. Its value will change a second later, since every second thousands of American men die and thousands of American males reach their 18th birthday.

  11. Distribution within • Thurstone (1937) observed the existence of distributions both between people and within people. Since people are different, this between-subject variability forms a distribution. However, the same person also has different task performance levels and attitudes toward an issue at different times.

More Related