PHLT 301 EXAM QUESTIONS WITH 100%
CORRECT ANSWERS!!
How do we know something is a large public health issue?
large amount of people are being affected (look at data)
inductive reasoning
observation <-- pattern <-- hypothesis <-- theory
deductive reasoning
theory --> hypothesis --> observation --> confirmation
Types of data
qualitative and quantitative data
qualitative data
descriptive, observable characteristics
EX: gender, race/ethnicity, education level
quantitative data
numerical, measures or counts,
EX: age, income, date of birth
Categorical data
binomial data, nominal data, ordinal data
binomial data
Two categories: true/false, yes/no
Nomial Data
categories that do not have an implicit rank/order: eye color, city name
ordinal data
, categories that do have an implicit rank/order: educational level, level of agreement (e.g. strongly
agree, agree)
Numeric data
discrete and continuous
discrete
specific value, count or tally
whole numbers
number of students
count of attendees
continuous
value within a range
do not have to be whole numbers
grades/ weight
accuracy
how close measurements are to the true value
precision
how close measurements are to each other
Reliability
repeatable and reproducibility
repeatable
getting the same outcome when the same operator measures the same part multiple times
reproducibility
getting the same outcome when different operators measure the same part multiple times
Epidemiology
CORRECT ANSWERS!!
How do we know something is a large public health issue?
large amount of people are being affected (look at data)
inductive reasoning
observation <-- pattern <-- hypothesis <-- theory
deductive reasoning
theory --> hypothesis --> observation --> confirmation
Types of data
qualitative and quantitative data
qualitative data
descriptive, observable characteristics
EX: gender, race/ethnicity, education level
quantitative data
numerical, measures or counts,
EX: age, income, date of birth
Categorical data
binomial data, nominal data, ordinal data
binomial data
Two categories: true/false, yes/no
Nomial Data
categories that do not have an implicit rank/order: eye color, city name
ordinal data
, categories that do have an implicit rank/order: educational level, level of agreement (e.g. strongly
agree, agree)
Numeric data
discrete and continuous
discrete
specific value, count or tally
whole numbers
number of students
count of attendees
continuous
value within a range
do not have to be whole numbers
grades/ weight
accuracy
how close measurements are to the true value
precision
how close measurements are to each other
Reliability
repeatable and reproducibility
repeatable
getting the same outcome when the same operator measures the same part multiple times
reproducibility
getting the same outcome when different operators measure the same part multiple times
Epidemiology
