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Entered data are kept in memory until @ c or m 3
are pressed. Before entering new data, clear the memory contents.
[Data Entry]
Single-variable data
Data k
Data & frequency k (To enter multiples of the same
data)
Two-variable data
Data x & Data y k
Data x & Data y & frequency k (To enter multiples
of the same data x and y.)
[Data Correction]
Correction prior to pressing k:
Delete incorrect data with N.
Correction after pressing k:
If nothing else but k is entered, press @J to delete,
then enter the correct value.
Single variable Statistical Calculations
Score
95
m30
80
95 k
80
80 k
75
k
75
75 & 3 k
75
50 k
50
R~
x
Rp
x
Rz
x
Rw
x
R£
sx
L=
sx
@π 60 @ü)=
x = 60
P(t) ?
R(t) ? @∏ 0.5 ±)=
t = –0.5
Regression Calculations
Given the two variable sample data (x,y), determine the standard
deviation of data sets x and y; the coefficients of the linear regres-
sion equation, and the correlation coefficient between x and y.
(Exponential, logarithmic, power, and inverse regression can also
be calculated in much the same way as linear regression.)
x
y
m31
2 & 5 k
2
5
k
2
5
12 & 24 k
12
24
21 & 40 & 3 k
21
40
15 & 25 k
21
40
Ra
21
40
Rb
15
25
Rr
R£
R¢
The following values are estimated:
3 @y
x=3
y'=?
46 @x
y=46
x'=?
Quadratic Regression Calculation
Given the sample data shown, determine the coefficients a, b, and
c of the quadratic regression equation and estimate the following
values:
x
y
m32
12 & 41 k
12
41
8 & 13 k
8
13
5 & 2 k
5
2
23 & 200 k
23 200
15 & 71 k
15
71
Ra
Rb
R©
10 @y
x=10 y'=?
22 @x
y=22 x'=?
û*
ù
* When there are two x values.
Statistical Calculation Formulas
Type
Linear
Exponential
Logarithmic
Power
Inverse
Quadratic
x = x n
sx =
y
y =
n
0.
1.
2.
sy =
3.
6.
7.
75.71428571
12.37179148
In the statistical calculation formulas, an error will occur when:
• the absolute value of the intermediate result or calculation result
530.
is equal to or greater than 1
41200.
• the denominator is zero.
13.3630621
• an attempt is made to take the square root of a negative number.
178.5714286
• no solution exists in the quadratic regression calculation.
0.102012
0.691463
[Normal Probability Calculations]
0.
1.
2.
3.
6.
7.
1.050261097
1.826044386
0.995176343
8.541216597
15.67223812
x – x
t = ––––
x
6.528394256
* P(t), Q(t), and R(t) will always take positive values, even when
24.61590706
t<0, because these functions follow the same principle used
when solving for an area.
Values for P(t), Q(t), and R(t) are given to six decimal places.
0.
1.
2.
3.
4.
5.
5.357506761
–3.120289663
0.503334057
24.4880159
9.63201409
–3.432772026
9.63201409
Regression formula
y = a + bx
bx
y = a • e
y = a + b • ln x
y = a • x
b
1
y = a + b —
x
y = a + bx + cx
2
x =
x = x
x
2
– nx
2
2
= x
x
n – 1
y =
xy = x
y
2
– ny
2
y = y
n – 1
2
y
= y
10
100
··· Standardization conversion formula
x
2
– nx
2
n
+ x
+ ··· + x
1
2
n
2
+ x
2
+ ··· + x
2
1
2
n
y
2
– ny
2
n
y
+ x
y
+ ··· + x
y
1
1
2
2
n
n
+ y
+ ··· + y
1
2
n
2
2
2
+ y
+ ··· + y
1
2
n
(n: Number of samples)
.
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