BIOStatistics
SEM 3 I FALL 2020
-
Tanya
Karakyriakou
kriekenpitplein ( G ) b-d
, 02/09/2020
Class 1 : Introduction & Basic Concepts
Probability frequency of the occurrence of an event
Pex) Odds / ( t + Odds)
=
Odds :
probability of event
happening / probability of event not
happening
odds =
P ( x ) / ( t Pex )) -
→
Outcome space = the set of all possible outcomes of an event
Making Abstract concepts Concrete T.mg?em?ePanm.piaetneeie-oman-o
comtnctvalisdittedam
GntentValidityidoyovrvaiabesaveraeethereeerar#
④ Provide a conceptual definition .
What do
you mean by X ?
② Provide operational definitions How variables sampled defined measured? aspects of the construct
of interest?
. are
your , ,
Population VS. Sample
taxenp.fpumea a.de?incd/estinfmatesaeuM-esthe
the entire collection of a collection of units
units of interest from
which sample is taken the
a
population
.
1--
Probability Samples Non -
probability Samples ( aka biased samples)
any sample for which that ends up in
→
particular for
→
unit the sample be which that a unit will
a can
any sample you cannot
compete the chance
given
calculated in advance .
end
up in the
sample .
→
require a SAMPLING FRAME +
accident all * snowball
convenience
+
Simple random sample
+
cluster sample t quota + purposive
+
stratified random sample &
Not suited for testing numerical hypotheses about populations
* can calculate a MARGIN OF ERROR
& (parameters)
SUITE'S for testing numerical hypotheses about population characteristics .
PET Terms
⑨ Probability There is 1/2 chance of getting flipping it
: a the heads side of a coin when once .
② Odds : The odds of getting the tails side of a coin when
flipping it once are even .
③ Odds Ratio :
The odds ratio of getting the tails side of a coin when
flipping it once is 50/50 .
④ Outcome Space : When
flipping a coin there are two outcomes i
taikorhea = outcome space ( aka sampler space) .
⑤ Conceptual definition
'
: A
coin has two sides front humeri call heads ( illustration) is called the faith
'
.
The is called the .
The back
⑥ Operational definition : To measure chances of
getting head or tails ,
a coin is
going to be flipped 10 times and the times of heads Ho and tails 110 will be measured .
. .
④ Construct Validity :
Measuring systolic top
when
examining proportion of high bp patients in a sample .
⑧ Content validity : high top can be captured by the systolic bp measurement .
⑨ Probability Sample : 5%5%0 every student Teacher randomly choses the question by chasing ( blind to student assignment)
gets assigned a number who answers number number
a .
.
⑥ Non probability Sample Sample :
population is selected be of being acquainted to the researcher ( convenience sampling)
-
.
④ Sampling frame : All patients in the
cardiology dept .
of a hospital when researching high top in that hospital la real wider
region .
SEM 3 I FALL 2020
-
Tanya
Karakyriakou
kriekenpitplein ( G ) b-d
, 02/09/2020
Class 1 : Introduction & Basic Concepts
Probability frequency of the occurrence of an event
Pex) Odds / ( t + Odds)
=
Odds :
probability of event
happening / probability of event not
happening
odds =
P ( x ) / ( t Pex )) -
→
Outcome space = the set of all possible outcomes of an event
Making Abstract concepts Concrete T.mg?em?ePanm.piaetneeie-oman-o
comtnctvalisdittedam
GntentValidityidoyovrvaiabesaveraeethereeerar#
④ Provide a conceptual definition .
What do
you mean by X ?
② Provide operational definitions How variables sampled defined measured? aspects of the construct
of interest?
. are
your , ,
Population VS. Sample
taxenp.fpumea a.de?incd/estinfmatesaeuM-esthe
the entire collection of a collection of units
units of interest from
which sample is taken the
a
population
.
1--
Probability Samples Non -
probability Samples ( aka biased samples)
any sample for which that ends up in
→
particular for
→
unit the sample be which that a unit will
a can
any sample you cannot
compete the chance
given
calculated in advance .
end
up in the
sample .
→
require a SAMPLING FRAME +
accident all * snowball
convenience
+
Simple random sample
+
cluster sample t quota + purposive
+
stratified random sample &
Not suited for testing numerical hypotheses about populations
* can calculate a MARGIN OF ERROR
& (parameters)
SUITE'S for testing numerical hypotheses about population characteristics .
PET Terms
⑨ Probability There is 1/2 chance of getting flipping it
: a the heads side of a coin when once .
② Odds : The odds of getting the tails side of a coin when
flipping it once are even .
③ Odds Ratio :
The odds ratio of getting the tails side of a coin when
flipping it once is 50/50 .
④ Outcome Space : When
flipping a coin there are two outcomes i
taikorhea = outcome space ( aka sampler space) .
⑤ Conceptual definition
'
: A
coin has two sides front humeri call heads ( illustration) is called the faith
'
.
The is called the .
The back
⑥ Operational definition : To measure chances of
getting head or tails ,
a coin is
going to be flipped 10 times and the times of heads Ho and tails 110 will be measured .
. .
④ Construct Validity :
Measuring systolic top
when
examining proportion of high bp patients in a sample .
⑧ Content validity : high top can be captured by the systolic bp measurement .
⑨ Probability Sample : 5%5%0 every student Teacher randomly choses the question by chasing ( blind to student assignment)
gets assigned a number who answers number number
a .
.
⑥ Non probability Sample Sample :
population is selected be of being acquainted to the researcher ( convenience sampling)
-
.
④ Sampling frame : All patients in the
cardiology dept .
of a hospital when researching high top in that hospital la real wider
region .
