Page 30 - Microsoft Office Excel 2003 Programming Inside Out
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Part 1:  Preliminaries
                                        Microsoft Office Excel 2003 Programming Inside Out

                             Table 1-1.  Improved Statistical Functions
                             BINOMDIST	       Determines the probability that a set number of true/false trials,
                                              where each trial has a consistent chance of generating a true or false
                                              result, will result in exactly a specified number of successes (for
             Chapter 1
                                              example, exactly five out of ten coin flips will end up heads).
                             CHIINV           Finds a value that best fits a result in a chi-squared distribution.
                             CONFIDENCE	      Returns a value you can use to construct a confidence interval for a
                                              population mean.
                             CRITBINOM	       Determines when the number of failures in a series of true/false trials
                                              exceeds a criterion (for example, more than 5 percent of light bulbs in
                                              a production run fail to light).
                             DSTDEV	          Estimates the standard deviation of values in a column by considering
                                              only those values that meet a criterion.
                             DSTDEVP 	        Calculates the standard deviation of values in a column based on
                                              every value in the column.
                             DVAR	            Estimates the variance of values in a column or list by considering only
                                              those values that meet a criterion.
                             DVARP	           Calculates the variance of values in a column or list based on every
                                              value in the column.
                             FINV	            Returns the value that would generate a target result from an
                                              F-test (a test of variability between two data sets).
                             FORECAST         Calculates future values based on an existing time series of values.
                             GAMMAINV	        Returns the value that would generate a given result from a gamma-
                                              distributed (that is, skewed) data set.
                             GROWTH           Predicts the exponential growth of a data series.
                             HYPGEOMDIST	     Returns the probability of selecting an exact number of a single type of
                                              item from a mixed set of objects. For example, a jar holds 20 marbles,
                                              6 of which are red. If you choose three marbles, what is the probability
                                              you will pick exactly one red marble?
                             INTERCEPT        Calculates the point at which a line will intersect the y-axis.
                             LINEST	          Generates a line that best fits a data set by generating a two-
                                              dimensional array of values to describe the line.
                             LOGEST	          Generates a curve that best fits a data set by generating a two-
                                              dimensional array of values to describe the curve.
                             LOGINV           Returns the inverse logarithm of a value in a distribution.
                             LOGNORMDIST 	    Returns the number of standard deviations a value is away from the
                                              mean in a lognormal distribution.
                             NEGBINOMDIST	    Returns the probability that there will be a given number of failures
                                              before a given number of successes in a binomial distribution.


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