I

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I

i
i Returns the complex number i.	y V

Returns the complex number i.

y V

identity(
identity(dimension) Returns the identity matrix of dimension rows x dimension columns.	y > MATH 5:identity(

identity(

identity(dimension)

Returns the identity matrix of dimension rows x dimension columns.

y >
MATH
5:identity(

If
If condition:commandA:commands If condition = 0 (false), skips commandA.	† ¼ CTL 1:If

If condition:commandA:commands

If condition = 0 (false), skips commandA.

† ¼
CTL
1:If

If Then End
If:conditionThen:commandsEnd:commands Executes commands from Then to End if condition = 1 (true).	† ¼ CTL 2:Then

If
Then
End

If:conditionThen:commandsEnd:commands

Executes commands from Then to End if condition = 1 (true).

† ¼
CTL
2:Then

If Then Else End
If:conditionThen:commandsElse:commandsEnd:commands Executes commands from Then to Else if condition = 1 (true); from Else to End if condition = 0 (false).	† ¼ CTL 3:Else

If
Then
Else
End

If:conditionThen:commandsElse:commandsEnd:commands

Executes commands from Then to Else if condition = 1 (true); from Else to End if condition = 0 (false).

† ¼
CTL
3:Else

imag(
imag(value) Returns the imaginary (non-real) part of a complex number or list of complex numbers.	» CMPLX 3:imag(

imag(

imag(value)

Returns the imaginary (non-real) part of a complex number or list of complex numbers.

»
CMPLX
3:imag(

invBinom(
invBinom(area,trial,p) The inverse binomial cumulative distribution function results in the minimum number of successes, such that the cumulative probability for that minimum number of successes ≥ the given cumulative probability (area). If more information is needed, also find the binomcdf for the result from invBinom( as shown below for a full analysis.	y = DISTR C:invBinom(
Details: Assume the toss of a fair coin 30 times. What is the minimum number of heads you must observe such that the cumulative probability for that number of observed heads is at least 0.95? The results on the screen first show that the minimum number of successes to obtain at least the given cumulative probability of 0.95 is 19. Next, the cumulative probability for up to 19 is computed using binomcdf( and is approximately 0.9506314271 which meets the criteria of 0.9506314271≥0.95
Alternate Method: Set Y1=binomcdf(30,0.5,X) and use the table of values (starting at 0 and increment by 1) to find when the cumulative probability is at or just above the given cumulative probability. This gives you a view of all values to make decisions. For this example, search in the table to find the cumulative probability just larger than 0.95. Again, the number of successes is 19.

invBinom(

invBinom(area,trial,p)

The inverse binomial cumulative distribution function results in the minimum number of successes, such that the cumulative probability for that minimum number of successes ≥ the given cumulative probability (area). If more information is needed, also find the binomcdf for the result from invBinom( as shown below for a full analysis.

y =

DISTR

C:invBinom(

Details:

Assume the toss of a fair coin 30 times. What is the minimum number of heads you must observe such that the cumulative probability for that number of observed heads is at least 0.95?

The results on the screen first show that the minimum number of successes to obtain at least the given cumulative probability of 0.95 is 19. Next, the cumulative probability for up to 19 is computed using binomcdf( and is approximately 0.9506314271 which meets the criteria of 0.9506314271≥0.95

Alternate Method:

Set Y1=binomcdf(30,0.5,X) and use the table of values (starting at 0 and increment by 1) to find when the cumulative probability is at or just above the given cumulative probability. This gives you a view of all values to make decisions. For this example, search in the table to find the cumulative probability just larger than 0.95. Again, the number of successes is 19.

IndpntAsk
IndpntAsk Sets table to ask for independent-variable values.	† y - Indpnt: Ask

IndpntAsk

Sets table to ask for independent-variable values.

† y -
Indpnt: Ask

IndpntAuto
IndpntAuto Sets table to generate independent-variable values automatically.	† y - Indpnt: Auto

IndpntAuto

Sets table to generate independent-variable values automatically.

† y -
Indpnt: Auto

Input
Input Displays graph.	† ¼ I/O 2:Input

Input

Displays graph.

† ¼
I/O
2:Input

Input
Input [variable] Input ["text",variable] Prompts for value to store to variable.	† ¼ I/O 2:Input

Input

Input [variable]

Input ["text",variable]

Prompts for value to store to variable.

† ¼
I/O
2:Input

Input
Input [Strn,variable] Displays Strn and stores entered value to variable.	† ¼ I/O 2:Input

Input

Input [Strn,variable]

Displays Strn and stores entered value to variable.

† ¼
I/O
2:Input

inString(
inString(string,substring[,start]) Returns the character position in string of the first character of substring beginning at start.	y N inString(

inString(

inString(string,substring[,start])

Returns the character position in string of the first character of substring beginning at start.

y N
inString(

int(
int(value) Returns the largest integer a real or complex number, expression, list, or matrix.	» NUM 5:int(

int(

int(value)

Returns the largest integer a real or complex number, expression, list, or matrix.

»
NUM
5:int(

GInt(
GInt(pmt1,pmt2[,roundvalue]) Computes the sum, rounded to roundvalue, of the interest amount between pmt1 and pmt2 for an amortization schedule.	Œ 1:Finance CALC A: G Int(

GInt(

GInt(pmt1,pmt2[,roundvalue])

Computes the sum, rounded to roundvalue, of the interest amount between pmt1 and pmt2 for an amortization schedule.

Œ 1:Finance
CALC
A: G Int(

invNorm(
invNorm(area[,µ,σ,tail]) tail [catalog]: LEFT, CENTER, RIGHT Computes the inverse cumulative normal distribution function for a given area under the normal distribution curve specified by m and s.. The optional argument tail can be LEFT (-∞,-a), CENTER [-a,a] or RIGHT (a, ∞) for Real a. The tokens LEFT, CENTER and RIGHT can be found in [catalog].	y = DISTR 3:invNorm(

invNorm(

invNorm(area[,µ,σ,tail])

tail [catalog]: LEFT, CENTER, RIGHT

Computes the inverse cumulative normal distribution function for a given area under the normal distribution curve specified by m and s.. The optional argument tail can be LEFT (-∞,-a), CENTER [-a,a] or RIGHT (a, ∞) for Real a.

The tokens LEFT, CENTER and RIGHT can be found in [catalog].

y =
DISTR
3:invNorm(

LEFT
LEFT LEFT is a tail argument for the invNorm( command where the optional argument tail can be LEFT (-∞,-a), CENTER [-a,a] or RIGHT (a, ∞) for Real a. See also invNorm(.	y N LEFT

LEFT

LEFT is a tail argument for the invNorm( command where the optional argument tail can be LEFT (-∞,-a), CENTER [-a,a] or RIGHT (a, ∞) for Real a.