Transcript chapter1_basic_concepts - Creative

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
• “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!”
What is this?
• Raw data
(unprocessed)
• Processed
data
• Information
VARIABLE
•
•
•
•
Opposite to constant
The value can vary
DV : outcome, response, criterion
IV : factor
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?
• This is inferential statistics because the analyst infers
from the sample statistics to the population
parameter.
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?
• 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.
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.
DISTRIBUTION WITHIN
• Thurstone (1937) observed the existence of
distributions both between people and within
people. Since people are different, this betweensubject variability forms a distribution. However, the
same person also has different task performance
levels and attitudes toward an issue at different
times.