PHLT 301 EXAM 3 QUESTIONS WITH 100%
CORRECT ANSWERS!!
How do we know something is a public health issue?
-number of deaths
-majority of people are imapcted
-population issue
-affects the community
inductive reasoning
1. observation
2. pattern
3. hypothesis
4. theory
deductive reasoning
1. Theory
2. Hypothesis
3. observation
4. confirmation
2 categories of types of data
qualitative and quantitative
qualitative data
-discriptional
-observational
quantitative
-numerical
-measures or counts
,examples of quantitative data
-gender
-race/ethnicity
-education level
examples of qualitative data
-age
-income
-date of birth
types of numeric data
discrete and continuous
discrete data
-specific values
-whole numbers
examples of discrete data
-zip code
-number of students
-count of attendees
continuous data
-value within a range
-does not have to be a whole number
examples of continuous data
-temperature
-grades
-height
-weight
, -time
-age
ordinal data
categories that DO have an implicit rank or order
examples of ordinal data
-educational level
-level of agreement (strongly agree, agree, neutral, disagree, strongly disagree)
binomial data
data that has two categories or two choices
examples of binomial data
-true/false
-yes/no
nominal data
-does NOT have an implicit rank/order
example of nominal data
-eye color
-city name
accuracy
how close measurements are to the true value
precision
how close measurements are to each other
reliability is
repeatable and reproducable
repeatable
CORRECT ANSWERS!!
How do we know something is a public health issue?
-number of deaths
-majority of people are imapcted
-population issue
-affects the community
inductive reasoning
1. observation
2. pattern
3. hypothesis
4. theory
deductive reasoning
1. Theory
2. Hypothesis
3. observation
4. confirmation
2 categories of types of data
qualitative and quantitative
qualitative data
-discriptional
-observational
quantitative
-numerical
-measures or counts
,examples of quantitative data
-gender
-race/ethnicity
-education level
examples of qualitative data
-age
-income
-date of birth
types of numeric data
discrete and continuous
discrete data
-specific values
-whole numbers
examples of discrete data
-zip code
-number of students
-count of attendees
continuous data
-value within a range
-does not have to be a whole number
examples of continuous data
-temperature
-grades
-height
-weight
, -time
-age
ordinal data
categories that DO have an implicit rank or order
examples of ordinal data
-educational level
-level of agreement (strongly agree, agree, neutral, disagree, strongly disagree)
binomial data
data that has two categories or two choices
examples of binomial data
-true/false
-yes/no
nominal data
-does NOT have an implicit rank/order
example of nominal data
-eye color
-city name
accuracy
how close measurements are to the true value
precision
how close measurements are to each other
reliability is
repeatable and reproducable
repeatable
