I am pleased to announce Release 5.10 of the Real Statistics Resource Pack for Excel 2007 users.
This release contains a subset of the new features provided by Release 6.0.2. Going forward, new releases of the Real Statistics Resource Pack for Excel 2007 environments will contain bug fixes and some minor enhancements.
The following is a summary of the new features in Release 5.10.
Multinomial Logistic Regression Enhancement
The output from the MLogitRSquare and MLogitTest functions now includes the number of iterations completed. This is important when the Multiple Logistic Regression data analysis tool is forced to terminate before the maximum number of specified iterations is reached. Previously an error was generated. (Thanks to Dillon for identifying the problem that inspired this enhancement)
D’Agostino-Pearson Test for Normality
The following new array functions have been added:
SKEWPTEST(R1, lab): population version of the skewness test; outputs a column array with the skewness of the data in R1, the test statistic and p-value
KURTPTEST(R1, lab): population version of the kurtosis test; outputs a column array with the kurtosis of the data in R1, the test statistic and p-value
If lab = TRUE (default FALSE), then an extra column of labels is added to the output.
These function provide the population version of the existing SKEWTEST and KURTTEST functions. The following existing functions that are used to perform the D’Agostino-Pearson test have been enhanced to provide both the sample and population versions of the test (with the population version used as the default option):
DAGOSTINO(R1, pop) = chi-square statistic for the D’Agostino-Pearson test
DPTEST(R1, pop) = p-value of the D’Agostino-Pearson test
If pop = TRUE (default) then the population version of the test is used; otherwise the sample version of the test is used.
The population version of the D’Agostino-Pearson test is now used in the Descriptive Statistics and Normality data analysis tool (when the Shapiro-Wilk option is chosen). (Thanks to Andrew for pointing out that there is an alternative way of calculating the D’Agostino-Pearson test).
Random Numbers with a Seed
The existing Real Statistics random number generator function RANDOM has been enhanced so that a seed can be used. The new version of this function now takes the following form:
RANDOM(a, b, FALSE, seed) = random number between a and b; i.e a non-volatile version of a + (b − a) * RAND()
RANDOM(a, b, TRUE, seed) = random integer between a and b, inclusive; i.e. a non-volatile version of RANDBETWEEN(a, b)
If a is omitted it defaults to 0, if b is omitted it defaults to 1 and if the third argument is omitted it defaults to FALSE.
If seed ≤ 0 or omitted then no seed is used, while if it is a positive value, then this value is used as a seed. A seed can be used to generate a repeatable sequence of pseudo-random values.
Cliff’s Delta
The following function has been added to calculate Cliff’s Delta (non-parametric) effect size for two samples. (Thanks to Erik for requesting this enhancement)
CLIFF_DELTA(R1, R2) = Cliff’s delta for the samples in R1 and R2
Prime Numbers
The following functions concerning prime numbers have been added. Here, n is any positive integer up to 231-1 = 2,147,483,647.
PrimeCount(n, start) = the number of prime numbers between start and n (inclusive)
IsPrime(n) = TRUE if n is a prime number
NextPrime(n) = next prime number after n
PriorPrime(n) = largest prime number smaller than n
NthPrime(n) = the nth prime number
PrimeList(start, size) = a column array with size number of prime numbers starting with the first prime ≥ start
Factors(n) = a column array containing the prime factors of n (with repetitions if necessary)
While these functions are not needed for statistical analysis, they can be useful in other contexts.
Bitwise Functions
The BIT_AND, BIT_OR, BIT_XOR, BIT_LSHIFT and BIT_RSHIFT functions have been added with functionality similar to the standard Excel functions BIT_AND, BIT_OR, BIT_XOR, BIT_LSHIFT and BIT_RSHIFT that were introduced with Excel 2013.
Bug Fixes
- Fixed a bug in the One Sample Runs Test data analysis tool and RUNSTEST function which presents itself in some rare circumstances when numbers are treated as characters. (Thanks to Christian for identifying this error)
- Fixed a bug in the Latin Squares Design data analysis tool when there are replications in calculating the value of SS_Replications. (Thanks to Karen for identifying this error)
- Fixed a bug in the calculation of the p-value for the coefficients in Poisson regression. In fact, a z-statistic is now used instead of the Wald statistic in calculating the p-value. This change is made to the Poisson Regression data analysis tool and the PoissonCoeff function. (Thanks to GAD for helping to identify this bug)
- Fixed a bug in the Multiple ANOVA option of the MANOVA data analysis tool which neglected to calculate a Bonferroni correction (Thanks to Joel for identifying this error)
- Fixed a bug in the ARIMA data analysis tool that occurs in earlier versions of Excel, but not in Excel 2016, when the time series data values are large. If a user encounters this type of problem in the future, the user can scale the data values down by dividing all values by a large number (e.g. 10,000). (Thanks to Kevin for helping to bring this problem to my attention)