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Systém má modulární stavbu. V multilicenci pro Masarykovu univerzitu jsou k dispozici moduly: Basic Statistics/Tables, Multiple Regression, ANOVA, Nonparametrics, Distribution Fitting, Advanced Linear / Nonlinear Models, Multivariate Explorartory Techniques, Industrial Statistics & Six Sigma. Velké množství informací o systému STATISTICA lze najít na webové stránce spolenosti StatSoft, která je jejím distributorem v eské republice (www.statsoft.cz). Z této stránky vede rovnž odkaz na elektronickou uebnici statistiky. STATISTICA 6 má nkolik typ oken: spreadsheet (datové okno, má píponu sta, jeho obsah však lze exportovat i v jiných formátech). Do datového okna lze naítat datové soubory nejrznjších typ (nap. z tabulkových procesor, databázové soubory, ASCII soubory). workbook (má píponu stw). Do workbooku ukládají výstupy, tj. tabulky a grafy. Skládá se ze dvou oken, v levém okn je znázornna stromová struktura výstup, v pravém jsou samotné výstupy. V levém okn se lze pohybovat myší nebo kurzorem, mazat, pesouvat, editovat apod. Výstupy mohou sloužit jako vstupy pro další analýzy a grafy. report (má píponu str, lze ho uložit i ve formátu rtf, txt i htm). Pokud požadujeme, aby se výstupy ukládaly nejen do workbooku, ale i do reportu, postupujeme takto: Tools Options Output Manager zaškrtneme Also send to Report Window OK. Report se podobn jako workbook skládá ze dvou oken. Do reportu mžeme vkládat vlastní text, vysvtlující komentáe, poznámky apod. Tabulky a grafy lze v reportu i workbooku dále upravovat. okno graf (pípona stg, lze ho uložit i jako bmp, jpg, png a wmf). Získá se tak, že ve workbooku klikneme pravým tlaítkem na graf a vybereme Clone Graph. programovací okno (pípona svb). Slouží pro zápis program v jazyku STATISTICA Visual Basic. Mezi jednotlivými typy oken se pepínáme pomocí položky Window v hlavním menu.

!" # $"%&! "#$"%""&'(%&)) "'% * +", () -"./0/1./1203 )"' 43 564& 3$57 67 47"# ("", +$568 7)37 & 97& '7 ""3487: 7:(. : * ; <=> =? 5=@? / > =)3?,= &?,7&?, =9 ""3?,='A;"3+6 > ""3+5= / >@ B 2"C 5 $%& " )#,# >)"" 3 ", ( 9 56"3 *.,7D,.,E/ =F G, =A;=< 56A;=. $A3 :H,#: ",+ +3( Category výborn: velmi dobe: dobe neprospl: Missing Frequency table: X: známka z matematiky (zn Cumulative Percent Cumulative Percent 7 7 35,00000 35,0000 3 10 15,00000 50,0000 2 12 10,00000 60,0000 8 20 40,00000 100,0000 0 20 0,00000 100,0000 Category výborn: velmi dobe: dobe neprospl: Missing Frequency table: Y: známka z anglitiny (znam Cumulative Percent Cumulative Percent 4 4 20,00000 20,0000 4 8 20,00000 40,0000 7 15 35,00000 75,0000 5 20 25,00000 100,0000 0 20 0,00000 100,0000 ' <& "),# 56 * I"#=J =< 56=A;7"?C=0, = D H 2A; <& ) ),# 56 * I"#=-I"#=% 2#=< 56=A;=0, =% / >%, $ / >< (=A;

<& ",# 56 * H" : "3+5%,B= - 72 : & )K? 2 "+#" @ %8B 2< " 9 Sloupkový diagram. 8 Sloupkový diagram. 8 7 7 6 6 5 5 4 4 3 3 2 2 1 1 0 výborn velmi dobe dobe neprospl známka z matematiky 0 výborn velmi dobe dobe neprospl známka z anglitiny Výseový graf. Výseový graf. neprospl; 25% výborn; 20% neprospl; 40% výborn; 35% velmi dobe; 20% dobe; 10% velmi dobe; 15% dobe; 35% známka z matematiky známka z anglitiny 9 Polygon absolutních etností. 7,5 Polygon absolutních etností. 8 7,0 7 6,5 6 6,0 5 5,5 4 5,0 3 4,5 2 4,0 1 výborn velmi dobe: dobe neprospl: známka z matematiky 3,5 výborn velmi dobe: dobe neprospl: známka z anglitiny L <& C ",+C, 5 * %&3# 0,.#H /" 2 6> M7> " C= & 0A"= %8D= /" N, <& C C, 5

* %&3# 0, 6>M7> " C= %I = K = %8D=/" @ 120 Empirick á distribuní funkce. 45% Graf etnostní funkce. 100 40% 35% 80 30% 60 40 20 0 Percent of obs 25% 20% 15% 10% 5% -20 0 výborn velmi dobe dobe nevyhovující 5 známka z matematiky 0% výborn velmi dobe dobe neprospl známka z matematiky O 4+# " : $" : (!9" * ": $" : ( *.,7D,.,E/ =F G, =A;=< 56A;=.,2 =.,2=1,, =.",C,, 4PA; < & ": Category výborn: velmi dobe: dobe neprospl: Missing Category výborn: velmi dobe: dobe neprospl: Missing Frequency table: X: známka z matematiky Cumulative Percent Cumulative Percent 5 5 50,00000 50,0000 2 7 20,00000 70,0000 1 8 10,00000 80,0000 2 10 20,00000 100,0000 0 10 0,00000 100,0000 Frequency table: Y: známka z anglitiny Cumulative Percent Cumulative Percent 4 4 40,00000 40,0000 2 6 20,00000 60,0000 1 7 10,00000 70,0000 3 10 30,00000 100,0000 0 10 0,00000 100,0000

<& ": Category výborn: velmi dobe: dobe neprospl: Missing Category velmi dobe: dobe neprospl: Missing Frequency table: X: známka z matematiky Cumulative Percent Cumulative Percent 2 2 20,00000 20,0000 1 3 10,00000 30,0000 1 4 10,00000 40,0000 6 10 60,00000 100,0000 0 10 0,00000 100,0000 Frequency table: Y: známka z anglitiny Cumulative Percent Cumulative Percent 2 2 20,00000 20,0000 6 8 60,00000 80,0000 2 10 20,00000 100,0000 0 10 0,00000 100,0000 Q? ",, )) <&,# 56 C C, *.,7D,.,E/ =/ =A;=.,, =0= A;=.",C 7@5@6A;. <& C C, 8?2/ N =9- # = 0>., =K K=K$+:" " 0>6(= I"#@=/" =." =A;IC ",% C< H <& ",3&3"3),#,# 56 *?2/ N =A"7 ", 2" %, C,,$ "%, CH,( ;,# Summary Frequency Table (znamky) Marked cells have counts > 10 (Marginal summaries are not marked) X Y Y výborn velmi dobe Y dobe Y neprospl Row Totals výborn 4 1 2 0 7 velmi dobe 0 2 1 0 3 dobe 0 0 1 1 2 neprospl 0 1 3 4 8 All Grps 4 4 7 5 20

Simultánní etnostní funkce. ; ",3&3"3),#,# Column Percent Row Percent Column Percent Row Percent Column Percent Row Percent Column Percent Row Percent Summary Frequency Table (znamky) Marked cells have counts > 10 (Marginal summaries are not marked) X Y Y Y Y Row výborn velmi dobe dobe neprospl Totals výborn 4 1 2 0 7 100,00% 25,00% 28,57% 0,00% 57,14% 14,29% 28,57% 0,00% velmi dobe 0 2 1 0 3 0,00% 50,00% 14,29% 0,00% 0,00% 66,67% 33,33% 0,00% dobe 0 0 1 1 2 0,00% 0,00% 14,29% 20,00% 0,00% 0,00% 50,00% 50,00% neprospl 0 1 3 4 8 0,00% 25,00% 42,86% 80,00% 0,00% 12,50% 37,50% 50,00%

-" # $"%& O, # ", " ", 7 $"%""&L(-) '% * +", ()?3 '%3)56& 3R ",SR " S %56": +", %. " " " &,,# QK >,##3 &, *.,=D,.,E/ =-,",7< 56= KT>=.$%5 99>O #&,,# $9LU$LQU$LQU"6 L >VW &, $LQU$QWU$QWU( Descriptive Statistics (o Minimum Maximum X 33,00000 160,0000 Y 52,00000 189,0000 5 "#&,# 9# " #&,# Q6 "#&,# L# " #&,# W 2 &, 58 $9LU$LQU$QWU$WU$9U$9LU$LQU "68 $LQU$QWU$WU$9U$9LU$LQU$QWU 9 <& # "5"6 * I"#=J =< 5="?C=0, = D =.",CD =LQW9LQA;=60>M % # > "" C 30A"3 + C

27% Histogram. 27% Histogram. 23% 23% 20% 20% 17% 17% 13% 13% 10% 10% 7% 7% 3% 3% 0% 50 70 90 110 130 150 170 mez plasticity 0% 70 90 110 130 150 170 190 mez pevnosti ' % * X#"3),#56"&),#&,,# * 1 =0< ==0C 6=A;="& N5N6? N5=-=N, 7" "",#Q $%=" " 5U95YPL(% " A; 0,"6 L <& C + ",+ ",+C, "5 * <& F G, "N5%& "&": & 2 " 2 %, +? 2 %, = I"#=I"#CD,-=2I"#CD,2=@ % $< (=A; Kategorie 0 1 2 3 4 5 6 7 ChD Kategorie 0 1 2 3 4 5 6 7 ChD Tabulka etností:rx (ocel) etnost Kumulativní Rel.etnost Kumulativní etnost rel.etnost 0,0000 8 8 13,33333 13,3333 4 12 6,66667 20,0000 13 25 21,66667 41,6667 15 40 25,00000 66,6667 9 49 15,00000 81,6667 7 56 11,66667 93,3333 4 60 6,66667 100,0000 0 60 0,00000 100,0000 Tabulka etností:ry (ocel) etnost Kumulativní Rel.etnost Kumulativní etnost rel.etnost 0,0000 5 5 8,33333 8,3333 10 15 16,66667 25,0000 14 29 23,33333 48,3333 13 42 21,66667 70,0000 9 51 15,00000 85,0000 6 57 10,00000 95,0000 3 60 5,00000 100,0000 0 60 0,00000 100,0000

120 Intervalová empirická distribuní funkce. 120 Intervalová empirická distribuní funkce. 100 100 80 80 60 60 40 40 20 20 0 0-20 30 50 70 90 110 130 150 170 190 mez plasticity -20 50 70 90 110 130 150 170 190 210 mez pevnosti O.,# $,# ",3&3 "3),#,# (3),#&,,# "$56( * <!Q+ ","3)N5N6 ;,#,# Total Percent Total Percent Total Percent Total Percent Total Percent Total Percent Total Percent Total Percent Summary Frequency Table (ocel) Table: RX(7) x RY(7) RX RY RY RY RY RY RY RY Row (50,70> (70,90> (90,110>(110,130> (130,150>(150,170> (170,190> Totals (30,50> 5 3 0 0 0 0 0 8 8,33% 5,00% 0,00% 0,00% 0,00% 0,00% 0,00% 13,33% (50,70> 0 3 1 0 0 0 0 4 0,00% 5,00% 1,67% 0,00% 0,00% 0,00% 0,00% 6,67% (70,90> 0 4 7 1 1 0 0 13 0,00% 6,67% 11,67% 1,67% 1,67% 0,00% 0,00% 21,67% (90,110> 0 0 6 8 1 0 0 15 0,00% 0,00% 10,00% 13,33% 1,67% 0,00% 0,00% 25,00% 110,130> 0 0 0 4 5 0 0 9 0,00% 0,00% 0,00% 6,67% 8,33% 0,00% 0,00% 15,00% (130,150> 0 0 0 0 2 5 0 7 0,00% 0,00% 0,00% 0,00% 3,33% 8,33% 0,00% 11,67% (150,170> 0 0 0 0 0 1 3 4 0,00% 0,00% 0,00% 0,00% 0,00% 1,67% 5,00% 6,67% All Grps 5 10 14 13 9 6 3 60 8,33% 16,67% 23,33% 21,67% 15,00% 10,00% 5,00%

; &3",3"3),#,# Row Percent Row Percent Row Percent Row Percent Row Percent Row Percent Row Percent Column Percent Column Percent Column Percent Column Percent Column Percent Column Percent Column Percent Summary Frequency Table (ocel) Table: RX(7) x RY(7) RX RY 1 RY 2 RY 3 RY 4 RY 5 RY 6 RY 7 Row Totals 1 5 3 0 0 0 0 0 8 62,50% 37,50% 0,00% 0,00% 0,00% 0,00% 0,00% 2 0 3 1 0 0 0 0 4 0,00% 75,00% 25,00% 0,00% 0,00% 0,00% 0,00% 3 0 4 7 1 1 0 0 13 0,00% 30,77% 53,85% 7,69% 7,69% 0,00% 0,00% 4 0 0 6 8 1 0 0 15 0,00% 0,00% 40,00% 53,33% 6,67% 0,00% 0,00% 5 0 0 0 4 5 0 0 9 0,00% 0,00% 0,00% 44,44% 55,56% 0,00% 0,00% 6 0 0 0 0 2 5 0 7 0,00% 0,00% 0,00% 0,00% 28,57% 71,43% 0,00% 7 0 0 0 0 0 1 3 4 0,00% 0,00% 0,00% 0,00% 0,00% 25,00% 75,00% All Grps 5 10 14 13 9 6 3 60 Summary Frequency Table (ocel) Table: RX(7) x RY(7) RX RY 1 RY 2 RY 3 RY 4 RY 5 RY 6 RY 7 Row Totals 1 5 3 0 0 0 0 0 8 100,00% 30,00% 0,00% 0,00% 0,00% 0,00% 0,00% 2 0 3 1 0 0 0 0 4 0,00% 30,00% 7,14% 0,00% 0,00% 0,00% 0,00% 3 0 4 7 1 1 0 0 13 0,00% 40,00% 50,00% 7,69% 11,11% 0,00% 0,00% 4 0 0 6 8 1 0 0 15 0,00% 0,00% 42,86% 61,54% 11,11% 0,00% 0,00% 5 0 0 0 4 5 0 0 9 0,00% 0,00% 0,00% 30,77% 55,56% 0,00% 0,00% 6 0 0 0 0 2 5 0 7 0,00% 0,00% 0,00% 0,00% 22,22% 83,33% 0,00% 7 0 0 0 0 0 1 3 4 0,00% 0,00% 0,00% 0,00% 0,00% 16,67% 100,00% All Grps 5 10 14 13 9 6 3 60 Q <& "$N5N6( * <, 2/ N 9-# < 30>., $"N5"N6(3 K K=K

Stereogram: RY x RX V? 3) ) "$56( * I"#=., "=< 56=A;" @ C=A; 200 Dvourozmrný tekový diagram. 180 160 mez pevnosti 140 120 100 80 60 40 20 40 60 80 100 120 140 160 180 mez plasticity

.$%##%//0"1/ /2 $"%& %,+"3 # ()?3 "'% "3 #,#<) "! ",#%" $V( *.,=D,.,E/ =-,".,=A;7< 56 A;= K @H T"" G Z =. X Y Descriptive Statistics (znamky) Median Lower Upper Quartile Quartile Quartile Range 2,500000 1,000000 4,000000 3,000000 3,000000 2,000000 3,500000 1,500000?3 '% ", " "3,+"3 3#"<) "! ",#%" $9( *.,=D,.,E/ =-,".,=A;7< 56 A;= K.- <, =. <3 8N"3,#./0/1./12B : ",# ":./0/1./120,")" " ":E E$7( Descriptive Statistics (ocel) Mean Variance Std.Dev. X Y 95,8833 1070,240 32,71453 114,4000 1075,125 32,78911 9 [ & 3: "3" "": 3B> + +#)"3" "&,#: / &,"&8/&" ",# 'WOW""& 45 " "3"3 ),# 4 5,#&,#",# 9 5 9 ' L O Q V W L L L L L L L ' 9 'W 9 ' W <"3 "3$ ("$, ($ H ("$(" "3"3 ),#,#&,#",#? "+,#

* %&./0/1./1;6& &"3+"&"<", 5$:(,#",,#" %3+ " 5.;.;.;9<, -,"., < 5 " \,#" ": ",) ",,# 4 \ #.;.AA;= K <,. H ;=.- "5 ") =!'+RD+: S/+:! " \ #.;.;9 "$5H #.;( Descriptive Statistics Mean Variance Skewness Kurtosis X 5,000000 5,000000-0,000000-0,759500 "$5H #.;( Descriptive Statistics Mean Variance Skewness Kurtosis X 5,000000 5,000000-0,000000 1,291133 9"$5H #.;9( Descriptive Statistics (cischar) Mean Variance Skewness Kurtosis X 5,000000 5,000000-0,000000 5,000000 26 Sloupkový diagram. 60 Sloupkový diagram. 24 22 20 18 16 14 12 10 8 6 4 50 40 30 20 10 2 0 0 1 2 3 4 5 6 7 8 9 10 0 0 1 2 3 4 5 6 7 8 9 10 X váženo pes SK1 X váženo pes SK2

10 Sloupkový diagram. 9 8 7 6 5 4 3 2 1 0 0 1 2 3 4 5 6 7 8 9 10 X váženo pes SK3 1 ", 8<,#&"):"3" " "N: ""3"3 ),# +

34 $"%& %,+" * " ) ()?3 "'<"3." C, ",# "": ": 4+) " $." C, 3&3,# "3),#>" ", 8 n 6 2 r = 1 R Q S 2 ( n 1) ( i i ) n i= 1 N "&> 7" 3,##> > +]> Z "& ( * %.,=?",=2 =A;= < F 5., 6=A;=." N% 7. " :,,?",2.,2 =.",C,,4P %,# Pair of s Spearman Rank Order Correlations (zna MD pairwise deleted Marked correlations are significant at p < Valid Spearman t(n-2) p-level N X & Y 20 0,688442 4,027090 0,000791 %: $C4P( Pair of s R Spearman Rank Order Correlations (zna MD pairwise deleted Marked correlations are significant at p < Valid Spearman t(n-2) p-level N X & Y 10 0,373544 1,138990 0,287662 %: $C4P( Spearman Rank Order Correlations (zna MD pairwise deleted Marked correlations are significant at p < Valid Spearman t(n-2) p-level Pair of s N R X & Y 10 0,860314 4,773446 0,001402 R <3 )% # C, 8?3 ' ) # "3+566696'5'<"3 % C,, "3),#$56($56($569($5'6'(": ),#,"3),#

3) ) % "3),# #% C, #3 ^ *.,=D.,E/ =2, =A;=A 5 6=A;=.82 >=?%,7K % 2 =0, E"=-., "=A;=F5.,6=A; 0,", "3),# X Y1 Correlations (korkoe X Y1 1,000000 0,816421 0,816421 1,000000 X Y2 Correlations (korkoe X Y2 1,000000 0,816237 0,816237 1,000000 X Y3 Correlations (korkoe X Y3 1,000000 0,816287 0,816287 1,000000 X4 Y4 Correlations (korkoe X4 Y4 1,000000 0,816521 0,816521 1,000000 Y1 Y3 Dvourozmrný tekový diagram r = 0,81642 12 11 10 9 8 7 6 5 4 3 2 4 6 8 10 12 14 16 X Dvourozmrný tekový diagram r = 0,81629 14 13 12 11 10 9 8 7 6 5 2 4 6 8 10 12 14 16 X Y2 Y4 Dvourozmrný tekový diagram r = 0,81624 10 9 8 7 6 5 4 3 2 2 4 6 8 10 12 14 16 X Dvourozmrný tekový diagram r = 0,81652 13 12 11 10 9 8 7 6 5 4 6 8 10 12 14 16 18 20 X4 9?3./0/1./1;6'<"3,% C,, ", " % ) ",#%" $9( * %.,7K" N 7< 1 " 5- " 6=A;=A;=N E"7",=-,",= 2, % # C, 2 2, <3 8;,./0/1./12B : ",#":./0/1./12B,")", ":E E$7(

X Y Correlations (ocel) X Y 1,000000 0,934548 0,934548 1,000000 X Y Covariances (ocel) X Y 1070,240 1002,471 1002,471 1075,125 ' C, "& " ", >, # " 7 ",? "&3+# +# * <, K" N < 1 " 5- " 6= A;=.8N < )", C, ",D & +1, " C, ",D& +5 >, " N %)" " +# N E"E",%, " 587A;< )", # # %,? "&8?K" N =N E"E ",=% C =., "=D, =56=A; [)"8-3+# +# "&:, -., " F@ A; Statistic Multiple R Multiple R2 Adjusted R2 F(1,58) p Std.Err. of Estimate Summary Value 0,9345 0,8734 0,8712 400,0641 0,0000 11,7677 X Intercept Predicted -95,0%CL +95,0%CL Predicting Values for (ocel) variable: Y B-Weight Value B-Weight * Value 0,936679 110,0000 103,0346 24,5881 127,6228 124,3063 130,9392 N=60 Intercept X Regression Summary for Dependent : Y (ocel) R=,93454811 R2=,87338017 Adjusted R2=,87119707 F(1,58)=400,06 p<0,0000 Std.Error of estimate: 11,768 Beta Std.Err. B Std.Err. t(58) p-level of Beta of B 24,58814 4,740272 5,18707 0,000003 0,934548 0,046724 0,93668 0,046830 20,00160 0,000000

200 Regresní pímka me ze pevnosti na mez plasticity. Y = 24,5881+0,9367*x 180 160 mez pevnosti 140 120 100 80 60 40 20 40 60 80 100 120 140 160 180 mez plasticity L #3),#+" &,# $"3>() ;!: $"3(-8 (1,35), (1,52), (3,81), (3,105), (5,100), (6,125), (7, 120) -3 C,<,& 8 P_ `_ >P_ `_ a>p_ `_ >P_ `_ E>< ) " >, #),#") & * -)"3)56"b "3+.ZN/5@AI51?<5 J"3+.ZN/5 : @? " PG$>($0, ""3+(N )" : "3+ # "35".ZN/5@AI5,1?<5 K "35 Statistic Multiple R Multiple R2 Adjusted R2 F(1,5) p Std.Err. of Estimate Summary Statistics; DV: Y (stroje) Value 0,91004 0,82817 0,79381 24,09909 0,00444 15,48711 X Intercept Predicted -95,0%CL +95,0%CL Predicting Values for (stroje) variable: Y B-Weight Value B-Weight * Value 13,14957 4,000000 52,5983 39,4444 92,0427 76,8676 107,2179 N=7 Intercept X Regression Summary for Dependent : Y (stroje) R=,91004028 R2=,82817331 Adjusted R2=,79380797 F(1,5)=24,099 p<,00444 Std.Error of estimate: 15,487 Beta Std.Err. B Std.Err. t(5) p-level of Beta of B 39,44444 11,54341 3,417054 0,018898 0,910040 0,185379 13,14957 2,67862 4,909082 0,004439

140 Regresní pímka. y=39,4444+13,1496*x 120 Y = náklady na údržbu 100 80 60 40 20 0 1 2 3 4 5 6 7 8 K, X = stáí stroje Statistic Multiple R Multiple R2 Adjusted R2 F(1,5) p Std.Err. of Estimate Summary Statistics; DV: Y (stroje) Value 0,93924 0,88217 0,85860 37,43261 0,00169 12,82508 SQRTX Intercept Predicted -95,0%CL +95,0%CL Predicting Values for (stroje) variable: Y B-Weight Value B-Weight * Value 48,55972 2,000000 97,1194-0,4774 96,6421 83,6962 109,5880 N=7 Intercept SQRTX Regression Summary for Dependent : Y (stroje) R=,93923698 R2=,88216611 Adjusted R2=,85859933 F(1,5)=37,433 p<,00169 Std.Error of estimate: 12,825 Beta Std.Err. B Std.Err. t(5) p-level of Beta of B -0,47736 15,29638-0,031207 0,976312 0,939237 0,153515 48,55972 7,93690 6,118220 0,001691 140 Regresní pímka. Y = -0,47736+48,55972*sqrt(x) 120 100 Y 80 60 40 20 0,8 1,0 1,2 1,4 1,6 1,8 2,0 2,2 2,4 2,6 2,8 SQRTX

K "&, # Statistic Multiple R Multiple R2 Adjusted R2 F(1,5) p Std.Err. of Estimate Summary Value 0,94282 0,88891 0,86670 40,01016 0,00146 12,45245 INVX Intercept Predicted -95,0%CL +95,0%CL Predicting Values for (stroje) variable: Y B-Weight Value B-Weight * Value -84,4832 0,250000-21,1208 126,6192 105,4984 91,5231 119,4738 N=7 Intercept INVX Regression Summary for Dependent : Y (stroje) R=,94282234 R2=,88891396 Adjusted R2=,86669676 F(1,5)=40,010 p<,00146 Std.Error of estimate: 12,452 Beta Std.Err. B Std.Err. t(5) p-level of Beta of B 126,6192 7,67327 16,50134 0,000015-0,942822 0,149054-84,4832 13,35627-6,32536 0,001456 140 Regresní pímka. y=126,6192-84,4832/x 120 100 Y 80 60 40 20 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,0 1,1 K INVX Statistic Multiple R Multiple R2 Adjusted R2 F(1,5) p Std.Err. of Estimate Summary Statistics; DV: Y (stroje) Value 0,95349 0,90915 0,89097 50,03321 0,00087 11,26153 LOGX Intercept Predicted -95,0%CL +95,0%CL Predicting Values for (stroje) variable: Y B-Weight Value B-Weight * Value 93,23472 0,602060 56,1329 44,6457 100,7786 88,9325 112,6247 N=7 Intercept LOGX Regression Summary for Dependent : Y (stroje) R=,95349135 R2=,90914576 Adjusted R2=,89097491 F(1,5)=50,033 p<,00087 Std.Error of estimate: 11,262 Beta Std.Err. B Std.Err. t(5) p-level of Beta of B 44,64571 7,49541 5,956407 0,001907 0,953491 0,134799 93,23472 13,18100 7,073415 0,000874

140 Regresní pímka. y=44,6457+93,2347*log(x) 120 100 Y 80 60 40 20-0,1 0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 LOGX? # >, <),#& 8 140 týdenní náklady na údržbu (v K) 120 100 80 60 40 20 0 1 2 3 4 5 6 7 8 stáí stroje v letech y yodh1 yodh2 yodh3 yodh4

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;/"%/# )%"%/#.," "!"3,# "3"!"3,# < % ),##,%, ":!"3,# / " ","./0/1./120!"3,#""$% " LL L( ( < #),#? 7#+# YLdU"":!"3)7: ",4!"3,#%"" ", C,!"3,#"" * F =? H=? C? C, =A;"3 "&?2@? " PN$(A;$F, N$( #+ ("3"& %A2B/-=N, 72 8 1, 1C?2UPL2 81, 1C?2YL? H< A;$%3 %A2B/!"3,#!"3,#(<" "3"3+%A2B/$!"3,#(% " "!"3,#"?: ",#"&"B=- =2 7F2 /2 A;4" "3+?2%A2B/" "3"3+%A2B/ %"" : "&"%& )) "3),#""&",#" #"?, 3) ) " Frequency table: POCET (Ezvc) Cumulative Percent Cumulative Category Percent 0 1005 1005 50,25000 50,2500 1 995 2000 49,75000 100,0000 Missing 0 2000 0,00000 100,0000 Frequency table: POCET (Ezvc) Cumulative Percent Cumulative Category Percent 0 510 510 51,00000 51,0000 1 490 1000 49,00000 100,0000 Missing 0 1000 0,00000 100,0000 Frequency table: POCET (Ezvc) Cumulative Percent Cumulative Category Percent 0 256 256 51,20000 51,2000 1 244 500 48,80000 100,0000 Missing 0 500 0,00000 100,0000

Frequency table: POCET (Ezvc) Cumulative Percent Cumulative Category Percent 0 100 100 50,00000 50,0000 1 100 200 50,00000 100,0000 Missing 0 200 0,00000 100,0000 Frequency table: POCET (Ezvc) Cumulative Percent Cumulative Category Percent 0 42 42 42,00000 42,0000 1 58 100 58,00000 100,0000 Missing 0 100 0,00000 100,0000 Frequency table: POCET (Ezvc) Cumulative Percent Cumulative Category Percent 0 23 23 46,00000 46,0000 1 27 50 54,00000 100,0000 Missing 0 50 0,00000 100,0000 Frequency table: POCET (Ezvc) Cumulative Percent Cumulative Category Percent 0 8 8 40,00000 40,0000 1 12 20 60,00000 100,0000 Missing 0 20 0,00000 100,0000 Frequency table: POCET (Ezvc) Cumulative Percent Cumulative Category Percent 0 6 6 60,00000 60,0000 1 4 10 40,00000 100,0000 Missing 0 10 0,00000 100,0000 Frequency table: POCET (Ezvc) Cumulative Percent Cumulative Category Percent 0 1 1 50,00000 50,0000 1 1 2 50,00000 100,0000 Missing 0 2 0,00000 100,0000 Frequency table: POCET (Ezvc) Cumulative Percent Cumulative Category Percent 0 4 4 80,00000 80,0000 1 1 5 20,00000 100,0000 Missing 0 5 0,00000 100,0000 L L L " 'WQL 'W 'VV L LV L' O ' L

0,65 0,60 0,55 0,50 0,45 Dvouroz mrný tekový diagram. Závislost relativní etnosti úspchu na potu pokus. p 0,40 0,35 0,30 0,25 0,20 0,15-200 0 200 400 600 800 1000 1200 1400 1600 1800 2000 2200 n

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Descriptive Statistics Mean Variance v1 0,497471 0,082374 v13 0,039656 1,009721 [ # 9P```=O ", 7 3:?$($"& 3& ""),#, +#+ 3( 0,)"39 P9WOLO" PWQ.& #5?$( B$5(P"-$5(P <?@ 1 %,./0/1./1;6" "& "/ "3", 8 6 ="!"3,#""P"),# ),#" "3"!"3,#ϑP96 >D$9(B$6 (P nϑp9-$6 (P nϑ 1 ϑ P ( ) A %# 19 30 Y100 30 40 30 P 20 Y 40 = P Φ 21 21 21 e$>( C, :?$( 10 21 ( ) Φ 0, 9773 100 = 11 21 () F =? H=? C? C, =A;? ", @? P1?$EG$(dd(71?$7EG$(dd(A;$F, 1?$>dd (" #C, 3>#: & #3,# ( (&%%# P 20 Y 40 = P 19 < Y100 40 = Φ 40 Φ 19 e$>( C, : D$9( ( ) ( ) ( ) ( ) 0, 978614 100 =

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