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E XPON D IST

In document DA_FunctionReference (Page 141-153)

E XPON D IST

Returns the exponential distribution. Exponential distribution is used to determine the time between consecutive, rare, and random events in a process with no memory. For example, you can use the ExponDist function to determine the time you have to wait before you get your next phone call. If you pass TRUE as the value of the Cumulative argument, ExponDist returns the cumulative distribution calculation. If you pass FALSE as the value of the Cumulative argument, the function returns the probability density calculation.

This function belongs to the Statistical category.

Syntax

ExponDist(X, Lambda, Cumulative)

Return Value

Numeric

Examples

The following function returns 0.78 as the exponential distribution when the X argument is 1 and the Lambda argument is 1.5:

ExponDist(1, 1.5, TRUE)

Argument Datatype Description

X Numeric Required. Number for which you want to perform the calculation.

Lambda Numeric Required. The lambda variable.

Cumulative Boolean Required. Logical value that determines the form of the function. If cumulative is TRUE, the function returns the cumulative answer.

Otherwise, it does not return the cumulative answer.

FD IST

Returns the F probability distribution. The F probability distribution is typically used to develop hypothesis tests. Use the FDist function to calculate the one-sided probability of the likelihood that two variances are different.

This function belongs to the Statistical category.

Syntax

FDist(X, DegreesOfFreedomNum, DegreesOfFreedomDenom)

Return Value

Numeric

Examples

You want to find out if female students are more diverse in their response to a particular question than male students. The standard deviation for female respondents equals 6 and standard deviation for male respondents equals 4. The value of the X argument is 2.25 (X=6*6/4*4). The numerator degrees of freedom is 39 and the denominator degrees of freedom is 64. The following expression returns 0.0019 as the F probability distribution:

FDist(2.25, 39, 64)

Argument Datatype Description

X Numeric Required. Number for which you want to perform the calculation.

Must be greater than or equal to 0.

DegreesOfFreedomNum Numeric Required. Whole number representing the numerator degrees of freedom numerator. Must be between 1 and 10,000, inclusive.

DegreesOfFreedomDenom Numeric Required. Whole number representing the denominator degrees of freedom. Must be between 1 and 10,000, inclusive.

FInv 115

FI NV

Returns the inverse of the probability associated with a F distribution. The Probability argument passed to the FInv function is the probability associated with the F distribution.

The F probability distribution is typically used to develop hypothesis tests.

This function belongs to the Statistical category.

Syntax

FInv(Probability, DegreesOfFreedomNum, DegreesOfFreedomDenom)

Return Value

Numeric

Examples

You are conducting a hypothesis test to determine the degree of variability in two data sets.

The numerator degrees of freedom is 39 and the denominator degrees of freedom is 64. The probability associated with the hypothesis test is 0.0019. The following expression returns 2.25 as the inverse of the probability associated with the F distribution:

FInv(0.0019, 39, 64)

Argument Datatype Description

Probability Numeric Required. Probability associated with the distribution. Must be between 0 and 1, inclusive.

DegreesOfFreedomNum Numeric Required. Whole number representing the numerator degrees of freedom numerator. Must be between 1 and 10,000, inclusive.

DegreesOfFreedomDenom Numeric Required. Whole number representing the denominator degrees of freedom. Must be between 1 and 10,000, inclusive.

FV

Returns the future value of an investment, where you make periodic, constant payments and the investment earns a constant interest rate. The Rate argument represents the interest rate earned in each period. PresentValue is the current value of the investment. If you omit the PresentValue argument, the FV function assumes it to be 0.

This function belongs to the Financial category.

Syntax

FV(Rate, NumberPeriods, Payment [, PresentValue, PaymentAtBeginning, CurrencyDecimals])

Return Value

Numeric

Examples

You deposit $2,000 into an account that earns 9 percent annual interest compounded monthly (monthly interest of 9%/12, or 0.75%). You plan to deposit $250 at the beginning of every month for the next 12 months. The following expression returns $5,337.96 as the amount that will be in the account at the end of 12 months:

FV(0.0075, 12, -250, -2000, TRUE)

Notes

To calculate interest rate earned in each period, divide the annual rate by the number of payments made in an year.

The payment value and present value are negative because these are amounts that you pay.

Argument Datatype Description

Rate Numeric Required. Interest rate, expressed as a decimal number. Divide the percent rate by 100 to express it as a decimal number. Must be greater than or equal to 0.

NumberPeriods Numeric Required. Number of periods or payments. Must be greater than 0.

Payment Numeric Required. Payment amount due.

PresentValue Numeric Optional. Current value of an asset or liability.

PaymentAtBeginning Boolean Optional. Timing of the payment. Enter TRUE if payment is at the beginning of period. Enter FALSE if payment is at the end of period.

Default is FALSE.

CurrencyDecimals Numeric Optional. Currency places to the right of the decimal point. Default is 2.

Must be between 0 and 3, inclusive.

Factorial 117

F ACTORIAL

Returns the factorial (n!) of a number, where n! equals 1*2*3*...*n. Use this function in mathematical calculations. If the number you pass to the function is not an integer, PowerAnalyzer truncates the number.

This function belongs to the Mathematical category.

Syntax

Factorial(NumericValue)

Return Value

Numeric

Examples

The following expression returns the factorial of the values of the Numbers metric:

Factorial({Numbers}) Numbers Return Value --- 6 720 1 1 5 120 2.2 2

Argument Datatype Description

NumericValue Numeric Required. Numeric value you want to pass to the function. Must be greater than or equal to 0.

F IND

Finds a text string (Find argument) within another text string (String argument), and returns the number of the starting position of the Find argument text within the String argument text. By default, PowerAnalyzer searches the string from beginning to end. You can have the Find string search from end to beginning by passing TRUE to the FromEnd argument. If the Find text does not exist within the String text, PowerAnalyzer returns NULL.

This function belongs to the String category.

Syntax

Find(String, Find [, FromEnd])

Return Value

Numeric

Examples

The following expression returns the number of the starting position of the text "on" within the value of the Product Status attribute:

Find({Product Status}, "on")

You can use the Substring function within the PowerAnalyzer Find function to generate results similar to Excel. For example, in Excel you can specify the position to start the search:

Find("For", "DressesForYou", 8)

In PowerAnalyzer, use the following expression to return the same result as above:

Find(Substring("DressesForYou", 8), "For") + 7

Argument Datatype Description

String String Required. String value you want to pass to the function.

Find String Required. String to find within other string.

FromEnd Boolean Optional. Starting position of the search. Default is FALSE. Enter TRUE to start the search from the end of the string.

Fisher 119

F ISHER

Returns the Fisher transformation for a given value. Fisher returns a value that is an approximately normally distributed value rather than a skewed one. You can use the Fisher transformation to test hypothesis on the correlation coefficient.

This function belongs to the Statistical category.

Syntax

Fisher(X)

Return Value

Numeric

Examples

The following function returns 0.73 as the Fisher transformation for 0.62:

Fisher(0.62)

Argument Datatype Description

X Numeric Required. Number for which you want to perform the calculation.

F ISHER I NV

Returns the statistical inverse of the Fisher transformation. You can use this function when determining the relationship between ranges or arrays of data.

This function belongs to the Statistical category.

Syntax

FisherInv(X)

Return Value

Numeric

Examples

The following function returns 0.62 as the inverse of Fisher transformation:

FisherInv(0.73)

Argument Datatype Description

X Numeric Required. Number for which you want to perform the calculation.

Floor 121

F LOOR

Returns the value rounded down to the specified number of digits, towards positive infinity.

The PowerAnalyzer Floor function differs from the Microsoft Excel Floor function. In the PowerAnalyzer Floor function, Significance is the number of digits to the right of the decimal point. In the Excel Floor function, Significance is the multiple to which you want to round.

The PowerAnalyzer Floor function rounds a number towards positive infinity, whereas the Excel Floor function rounds a number away from zero.

This function belongs to the Rounding category.

Syntax

Floor(NumericValue [, Significance])

Return Value

Numeric

Examples

The following expression returns the number rounded down to the significance, towards positive infinity:

NumericValue Numeric Required. Numeric value you want to pass to the function. You can enter a numeric literal, numeric metric name, or numeric attribute name.

Significance Numeric Optional. Number of places to the right of decimal point. Negative value indicates number of places to the left of decimal point. Default is 0.

Notes

To generate the same result as the Excel Floor(value, significance) function, use the following expression:

RoundDown(value/significance) * significance

Forecast 123

F ORECAST

Predicts a future value based on existing values. You can use this function to determine future sales, inventory levels, or trends. You pass a single value and two sets of values (ListY and ListX) to the Forecast function. The single value is a ListX value. The function returns a predicted ListY value for the given ListX value. The function uses linear regression to predict the ListY value. Pass numeric metrics or attributes as the values for the ListY and ListX arguments. Use the Context argument to narrow the scope of the function to specific metric or attribute values. The Context1 argument corresponds to the ListY argument and the Context2 argument corresponds to the ListX argument.

This function belongs to the Aggregate category.

Syntax

Forecast(X, ListY, ListX [, Context1, Context2])

Return Value

Numeric

Examples

The following expression returns 4534.59 as the forecasted sales for the year 2004 for T-shirts, given that sales for the last year were $5000:

Forecast(5000, {2004 Sales}, {2003 Sales}, "{Prod Category}='Women'"},

"{Prod Category}='Women'"}) Prod Category 2004 Sales 2003 Sales ---

---Argument Datatype Description

X Numeric Required. Number for which you want to perform the calculation.

ListY Numeric List Required. Name of a metric or attribute representing known dependent values.

ListX Numeric List Required. Name of a metric or attribute representing known independent values.

Context1 String Optional. First filter for setting a scope for the function. Context allows you to narrow the calculation to a set of attribute or metric values. You must enclose the Context within quotation marks. The syntax for the Context argument depends on the function where you are using it.

Context2 String Optional. Second filter for setting a scope for the function. Default is the same as the value of Context1. Context allows you to narrow the calculation to a set of attribute or metric values. You must enclose the Context within quotation marks. The syntax for the Context argument depends on the function where you are using it.

Women 1500 2500 Women 5000 2250 Men 38088 10502 Women 6200 800 Women 750 150 Women 2000 750 Men 28195 6974

Notes

The two lists must have equal number of values. If there is a NULL in one list, the corresponding value in the other list is skipped. In this case, the function does not include either value in the calculation.

When you pass an optional argument, you must also pass all other optional arguments that occur before it in the function syntax.

In document DA_FunctionReference (Page 141-153)

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