Formulas and Functions
Table Of Contents
- Formulas and Functions
- Contents
- Preface: Welcome to iWork Formulas & Functions
- Chapter 1: Using Formulas in Tables
- The Elements of Formulas
- Performing Instant Calculations in Numbers
- Using Predefined Quick Formulas
- Creating Your Own Formulas
- Removing Formulas
- Referring to Cells in Formulas
- Using Operators in Formulas
- The String Operator and the Wildcards
- Copying or Moving Formulas and Their Computed Values
- Viewing All Formulas in a Spreadsheet
- Finding and Replacing Formula Elements
- Chapter 2: Overview of the iWork Functions
- Chapter 3: Date and Time Functions
- Chapter 4: Duration Functions
- Chapter 5: Engineering Functions
- Chapter 6: Financial Functions
- Chapter 7: Logical and Information Functions
- Chapter 8: Numeric Functions
- Chapter 9: Reference Functions
- Chapter 10: Statistical Functions
- Listing of Statistical Functions
- AVEDEV
- AVERAGE
- AVERAGEA
- AVERAGEIF
- AVERAGEIFS
- BETADIST
- BETAINV
- BINOMDIST
- CHIDIST
- CHIINV
- CHITEST
- CONFIDENCE
- CORREL
- COUNT
- COUNTA
- COUNTBLANK
- COUNTIF
- COUNTIFS
- COVAR
- CRITBINOM
- DEVSQ
- EXPONDIST
- FDIST
- FINV
- FORECAST
- FREQUENCY
- GAMMADIST
- GAMMAINV
- GAMMALN
- GEOMEAN
- HARMEAN
- INTERCEPT
- LARGE
- LINEST
- Additional Statistics
- LOGINV
- LOGNORMDIST
- MAX
- MAXA
- MEDIAN
- MIN
- MINA
- MODE
- NEGBINOMDIST
- NORMDIST
- NORMINV
- NORMSDIST
- NORMSINV
- PERCENTILE
- PERCENTRANK
- PERMUT
- POISSON
- PROB
- QUARTILE
- RANK
- SLOPE
- SMALL
- STANDARDIZE
- STDEV
- STDEVA
- STDEVP
- STDEVPA
- TDIST
- TINV
- TTEST
- VAR
- VARA
- VARP
- VARPA
- ZTEST
- Chapter 11: Text Functions
- Chapter 12: Trigonometric Functions
- Chapter 13: Additional Examples and Topics
- Index
Chapter 10 Statistical Functions 267
Additional Statistics
This section discusses the additional statistics that can be returned by the LINEST
function.
LINEST can include additional statistical information in the array returned by the
function. For purposes of the following discussion, assume that there are ve sets of
known x values, in addition to the known y values. Assume further that the known
x values are in ve table rows or ve table columns. Based on these assumptions,
the array returned by LINEST would be as follows (where the number following an x
indicates which set of x values the item refers to):
Row/Column 1 2 3 4 5 6
1 slope x5 slope x4 slope x3 slope x2 slope x1 b (y intercept)
2 std-err x1 std-err x2 std-err x3 std-err x4 std-err x5 std-err b
3 coecient-det std-err y
4 F-stat degrees-of-
freedom
5 reg-ss reside-ss
Argumentdenitions
slope x: The slope of the line related to this set of known x values. The values are
returned in reverse order; that is, if there are ve known x value sets, the value for the
fth set is rst in the returned array.
b: The y intercept for the known x values.
std-err x: The standard error for the coecient associated with this set of known x
values. The values are returned in order; that is, if there are ve known x value sets, the
value for the rst set is returned rst in the array. This is the opposite of the way the
slope values are returned.
std-err b: The standard error associated with the y-intercept value (b).
coecient-det:The coecient of determination. This statistic compares estimated and
actual y values. If it is 1, there is no dierence between the estimated y value and the
actual y value. This is known as perfect correlation. If the coecient of determination is
0, there is no correlation and the given regression equation is not helpful in predicting
a y value.
std-err y: The standard error associated with the y value estimate.
F-stat: The F observed value. The F observed value can be used to help determine
whether the observed relationship between the dependent and independent
variables occurs by chance.
degrees-of-freedom: The degrees of freedom. Use the degrees of freedom statistic to
help determine a condence level.










