Texas Instruments NS/CLM/1L1/B Reference Guide - Page 89

tCdf() tCdf(lowBound,upBound,df) ⇒ number if lowBound and upBound are numbers, list if lowBound and upBound are lists Computes the Student-t distribution probability between lowBound and upBound for the specified degrees of freedom df. For p(X  upBound), set lowBound = .9E999. Then TInterval TInterval List[,Freq[,CLevel]] (Data list input) TInterval v,Sx,n[,CLevel] (Summary stats input) Computes a t confidence interval. A summary of results is stored in the stat.results variable. (See page 76.) Output variable Description stat.CLower, stat.CUpper Confidence interval for an unknown population mean. stat.x Sample mean of the data sequence from the normal random distribution. stat.ME Margin of error. stat.df Degrees of freedom. stat.sx Sample standard deviation. stat.n Length of the data sequence with sample mean. TInterval_2Samp TInterval_2Samp List1,List2[,Freq1[,Freq2[,CLevel[,Pooled]]]] (Data list input) TInterval_2Samp v1,Sx1,n1,v2,Sx2,n2[,CLevel[,Pooled]] (Summary stats input) Computes a two-sample t confidence interval. A summary of results is stored in the stat.results variable. (See page 76.) Pooled=1 pools variances; Pooled=0 does not pool variances. Output variable Description stat.CLower, stat.CUpper Confidence interval containing confidence level probability of distribution. stat.x1-x2 Sample means of the data sequences from the normal random distribution. stat.ME Margin of error. TI-Nspire™ Reference Guide Catalog > See If, page 35. Catalog > Catalog > 83