Maths & Statistics
, Week e
International of Units CSI)
System
length ( metre )
-
Mass
Cig )
-
.
-
Time ( seconds
-
Electrical Current (
amperes
)
Temperature ( Kelvin )
-
luminous
-
intensity ( candelas )
-
Amount of substance ( moles )
Amount of substance ( males)
The male is defined as the amount of substance that contains an
equal number of
elementary entities
Example : Atomic mass of
hydrogen t.nnsru-i.onsrg.fm at
Atomic mass of
oxygen 16 .no u=
16g -
final -
In I
.
-
|
n
-
number of males
µ = ma, , of substance
Mr = relative molecular mass
|Cix/
-
-
I
-
n
-
-
c -
VI for cin
v
Significant Figures
\ C
v
a
z
concentration ( mall
volume of salvation
L2
in
molarity )
L
Example : S
13
-
Og
gurl
.
'
(
'
2
(
Srf )
25 .f
.
.
)
) ,,5j ,
. ,
= 0.384615384 . . .
I 0.38 mat # mL
Whall
→
"
→
L
,
+ in
- '
mall
- '
( Sif )
Is 0.0004 → 4E 4 I
-
.
,
8. 1am → ( Ssf ) .
3. argon → ( SE 46 Sif this could be 7 Sif if all values measured at this
accuracy
I .
or .
were
,
# Round the to the number of places of problem
answer
least any
number in the .
, Loss
Example
.
:
Mega la =
born, Ono
watts
1
Megawatt =
yarn, aan
18106 watts =
gear, and watts
lob =
yangon a flag , .
( cyan, aan ) = 6
# Base 2 :
dagzlx) -
often used in
computer science
" "
natural
Base
Lage ( x) also known the lag where
-
e : as e- e 2.718281828 . .
.
Is .÷:÷::÷:c:c:*: :c:c:: : ÷ :"
"
small variable
with a
change in one .
calculations Car &
Benefits of using Logs Makes the with large small ) numbers
-
easy
very
lag cabs -
-
lgatlgb log ( az) -
laga Rgb -
lag Ca 's =
cxlga
Logarithm Scales -
Decibels are also measured on an
logarithm scale
pH is
logarithm measure of the
acidity of a solution
[
Calculated based on the [ Ht]
•
for strong acid in water pH = -
log [ Ht]
Example :
f
>
dog
:÷:
[ Ht ] [ can ]
-
>
7)
-
C
II
•
→ 7 '
l Xin = =
:: :
a - -
'
-
÷ :÷÷÷ :
' "' "
-
'
" " → " s
13
2 3
( ti )
-
- 12 -
-
i → 5.01×10
→
pH 12.3 →
•
2. Gx , a = to
, Statistics
(
collecting / Classifying / Summarizing ✓ Analysing / Interpreting
Descriptive -
utilises numerical and graphical methods to hear for patterns in a data set
,
to summarize the
information reveal Vod in a data set and to present that information in a convenient farm .
(
Average spread
, , range , frequency ,
histogram ,
median
,
scatter plot ,
made
,
iuterguantrle range )
Inferential -
utilises sample data to make estimates ,
decisions
, predictions or other
generalisations about a
larger
set of data .
(
Hypothesis least of )
test
,
2. Anova
,
confident interval
,
ordinary squares 2
, margin error
,
t . . .
t
Sampling
#
Population -
the complete collection of items to be studied
" "
)
(
examining every single one → conduct a census
characteristic
property of individual
Variable - a or an
unit
of these characteristics will not
( values , surprisingly ,
vary )
sample -
a subset of the population
-
Reliability
}
-
No selection bias
No bras Random selection
-
response
.
sample
-
Measurement error .
Large sample size
A measure of
reliability statement about the degree of
uncertainty associated with statistical inference
-
a a
[ "
"
soda
Based on our
analysis ,
we think -
f of drinkers prefer Pepsi to Coke
,
I -
t.
, Week e
International of Units CSI)
System
length ( metre )
-
Mass
Cig )
-
.
-
Time ( seconds
-
Electrical Current (
amperes
)
Temperature ( Kelvin )
-
luminous
-
intensity ( candelas )
-
Amount of substance ( moles )
Amount of substance ( males)
The male is defined as the amount of substance that contains an
equal number of
elementary entities
Example : Atomic mass of
hydrogen t.nnsru-i.onsrg.fm at
Atomic mass of
oxygen 16 .no u=
16g -
final -
In I
.
-
|
n
-
number of males
µ = ma, , of substance
Mr = relative molecular mass
|Cix/
-
-
I
-
n
-
-
c -
VI for cin
v
Significant Figures
\ C
v
a
z
concentration ( mall
volume of salvation
L2
in
molarity )
L
Example : S
13
-
Og
gurl
.
'
(
'
2
(
Srf )
25 .f
.
.
)
) ,,5j ,
. ,
= 0.384615384 . . .
I 0.38 mat # mL
Whall
→
"
→
L
,
+ in
- '
mall
- '
( Sif )
Is 0.0004 → 4E 4 I
-
.
,
8. 1am → ( Ssf ) .
3. argon → ( SE 46 Sif this could be 7 Sif if all values measured at this
accuracy
I .
or .
were
,
# Round the to the number of places of problem
answer
least any
number in the .
, Loss
Example
.
:
Mega la =
born, Ono
watts
1
Megawatt =
yarn, aan
18106 watts =
gear, and watts
lob =
yangon a flag , .
( cyan, aan ) = 6
# Base 2 :
dagzlx) -
often used in
computer science
" "
natural
Base
Lage ( x) also known the lag where
-
e : as e- e 2.718281828 . .
.
Is .÷:÷::÷:c:c:*: :c:c:: : ÷ :"
"
small variable
with a
change in one .
calculations Car &
Benefits of using Logs Makes the with large small ) numbers
-
easy
very
lag cabs -
-
lgatlgb log ( az) -
laga Rgb -
lag Ca 's =
cxlga
Logarithm Scales -
Decibels are also measured on an
logarithm scale
pH is
logarithm measure of the
acidity of a solution
[
Calculated based on the [ Ht]
•
for strong acid in water pH = -
log [ Ht]
Example :
f
>
dog
:÷:
[ Ht ] [ can ]
-
>
7)
-
C
II
•
→ 7 '
l Xin = =
:: :
a - -
'
-
÷ :÷÷÷ :
' "' "
-
'
" " → " s
13
2 3
( ti )
-
- 12 -
-
i → 5.01×10
→
pH 12.3 →
•
2. Gx , a = to
, Statistics
(
collecting / Classifying / Summarizing ✓ Analysing / Interpreting
Descriptive -
utilises numerical and graphical methods to hear for patterns in a data set
,
to summarize the
information reveal Vod in a data set and to present that information in a convenient farm .
(
Average spread
, , range , frequency ,
histogram ,
median
,
scatter plot ,
made
,
iuterguantrle range )
Inferential -
utilises sample data to make estimates ,
decisions
, predictions or other
generalisations about a
larger
set of data .
(
Hypothesis least of )
test
,
2. Anova
,
confident interval
,
ordinary squares 2
, margin error
,
t . . .
t
Sampling
#
Population -
the complete collection of items to be studied
" "
)
(
examining every single one → conduct a census
characteristic
property of individual
Variable - a or an
unit
of these characteristics will not
( values , surprisingly ,
vary )
sample -
a subset of the population
-
Reliability
}
-
No selection bias
No bras Random selection
-
response
.
sample
-
Measurement error .
Large sample size
A measure of
reliability statement about the degree of
uncertainty associated with statistical inference
-
a a
[ "
"
soda
Based on our
analysis ,
we think -
f of drinkers prefer Pepsi to Coke
,
I -
t.
