class: center, middle, inverse, title-slide .title[ # MULTIVARIJATNE STATISTIČKE METODE ] .subtitle[ ## Predavanje 3: Deskriptivna statistika ] .author[ ### Luka Sikic, PhD ] .institute[ ### Fakultet hrvatskih studija ] .date[ ### (Osvježeno: 2023-03-13) ] --- name: toc <style type="text/css"> @media print { .has-continuation { display: block !important; } } remark-slide-content { font-size: 22px; padding: 20px 80px 20px 80px; } .remark-code, .remark-inline-code { background: #f0f0f0; } .remark-code { font-size: 16px; } .mid. remark-code { /*Change made here*/ font-size: 60% !important; } .tiny .remark-code { /*Change made here*/ font-size: 40% !important; } </style> # Pregled predavanja <br> <br> <br> 1. [Podatci](#podatci) 2. [Mjere centralne tendencije](#mct) 3. [Mjere varijabilnosti](#mv) 4. [Varijable i podatkovni okviri](#vpo) 5. [Standardizirane vrijednosti](#sv) 6. [Korelacija](#kor) --- class: inverse, center, middle name: podatci # PODATCI <html><div style='float:left'></div><hr color='#EB811B' size=1px width=796px></html> (Sve kreće od podataka) --- # Učitaj i pregledaj podatke ```r # Učitaj paket library(lsr) # Učitaj podatke u radni prostor load("./Podatci/aflsmall.Rdata") who() # Pregledaj učitane podatke ``` ``` ## -- Name -- -- Class -- -- Size -- ## afl.finalists factor 400 ## afl.margins numeric 176 ``` ```r # Pregledaj podatke print(afl.margins[1:11]) ``` ``` ## [1] 56 31 56 8 32 14 36 56 19 1 3 ``` ```r print(afl.finalists[1:5]) ``` ``` ## [1] Hawthorn Melbourne Carlton Melbourne Hawthorn ## 17 Levels: Adelaide Brisbane Carlton Collingwood Essendon Fitzroy ... Western Bulldogs ``` --- # Grafički pregled podataka <div class="figure" style="text-align: center"> <img src="03_PONAVLJANJEDESKRIPTIVNA_files/figure-html/histogram1-1.png" alt="Histogram pobjedničkih bodova iz AFL 2010 lige američkog nogometa." /> <p class="caption">Histogram pobjedničkih bodova iz AFL 2010 lige američkog nogometa.</p> </div> --- class: inverse, center, middle name: mct # MJERE CENTRALNE TENDENCIJE <html><div style='float:left'></div><hr color='#EB811B' size=1px width=796px></html> (Zlatna sredina) --- # Najčešće korištene mjere <br> <br> <br> <br> - Aritmetička sredina <br> <br> - Medijan <br> <br> - Mod --- # Aritmetička sredina <br> <br> #### Matematička definicija `$$\bar{X} = \frac{X_1 + X_2 + ... + X_{N-1} + X_N}{N}$$` #### Operator za sumiranje $$ \sum_{i=1}^5 X_i $$ #### Skraćeni zapis $$ \bar{X} = \frac{1}{N} \sum_{i=1}^N X_i $$ --- # Aritmetička sredina <br> <br> #### Izračun rukom $$ \frac{56 + 31 + 56 + 8 + 32}{5} = \frac{183}{5} = 36.60 $$ #### Kalkulator ```r (56 + 31 + 56 + 8 + 32) / 5 ``` ``` ## [1] 36.6 ``` #### Funkcija ```r sum( afl.margins[1:5]) / 5 ``` ``` ## [1] 36.6 ``` --- # Medijan <br> <br> #### Neparni niz $$ 8, 31, \mathbf{32}, 56, 56 $$ #### Parni niz $$ 8, 14, \mathbf{31}, \mathbf{32}, 56, 56 $$ ```r # Izračunaj medijan putem funkcije median( x = afl.margins ) # Cijeli podatkovni skup ``` ``` ## [1] 30.5 ``` --- # Mod ```r # Pogledaj frekvenciju podataka table(afl.finalists) ``` ``` ## afl.finalists ## Adelaide Brisbane Carlton Collingwood ## 26 25 26 28 ## Essendon Fitzroy Fremantle Geelong ## 32 0 6 39 ## Hawthorn Melbourne North Melbourne Port Adelaide ## 27 28 28 17 ## Richmond St Kilda Sydney West Coast ## 6 24 26 38 ## Western Bulldogs ## 24 ``` ```r # Izračunaj modalnu vrijednost modeOf( x = afl.finalists ) ``` ``` ## [1] "Geelong" ``` --- # Mod <br> <br> ```r # Izračunaj modalnu frekvenciju maxFreq(x = afl.finalists) ``` ``` ## [1] 39 ``` ```r # Izaračun za afl.margins podatke modeOf(afl.margins) # Mod ``` ``` ## [1] 3 ``` ```r maxFreq(afl.margins) # Modalna frekvencija ``` ``` ## [1] 8 ``` --- class: inverse, center, middle name: mv # MJERE VARIJABILNOSTI <html><div style='float:left'></div><hr color='#EB811B' size=1px width=796px></html> (Raspršenost podataka) --- # Najčešće korištene mjere <br> <br> <br> <br> - Raspon/Min-Max <br> <br> - Kvartili <br> <br> - Varijanca <br> <br> - Standardna devijacija --- # Raspon (Min-Max) <br> <br> ```r # Maksimalna vrijednost max(afl.margins) ``` ``` ## [1] 116 ``` ```r # Minimalna vrijednost min(afl.margins) ``` ``` ## [1] 0 ``` ```r # Raspon podataka range(afl.margins) ``` ``` ## [1] 0 116 ``` --- # Kvartili ```r # Izračunaj pedeseti (50i) kvartil/percentil quantile(x = afl.margins, probs = .5) ``` ``` ## 50% ## 30.5 ``` ```r # Izračunaj 25i i 75i kvartil/percentil quantile(afl.margins, probs = c(.25,.75)) ``` ``` ## 25% 75% ## 12.75 50.50 ``` ```r # Izračunaj interkvartilni raspon IQR(x = afl.margins) ``` ``` ## [1] 37.75 ``` --- # Varijanca <br> <br> #### Matematička definicija <br> <br> `$$\mbox{Var}(X) = \frac{1}{N} \sum_{i=1}^N \left( X_i - \bar{X} \right)^2$$` <br> <br> #### Alternativni zapis `$$\mbox{Var}(X) = \frac{\sum_{i=1}^N \left( X_i - \bar{X} \right)^2}{N}$$` --- # Varijanca <br> <br> Table: Ručni izračun varijance. | `\(i\)`| `\(X_i\)`| `\(X_i - \bar{X}\)`| `\((X_i - \bar{X})^2\)`| |---:|-----:|---------------:|-------------------:| | 1| 56| 19.4| 376.36| | 2| 31| -5.6| 31.36| | 3| 56| 19.4| 376.36| | 4| 8| -28.6| 817.96| | 5| 32| -4.6| 21.16| --- # Varijanca <br> <br> ```r # Kalkulator (376.36 + 31.36 + 376.36 + 817.96 + 21.16 ) / 5 ``` ``` ## [1] 324.64 ``` ```r # Izračunaj varijancu pomoću funkcija mean( (afl.margins - mean(afl.margins) )^2) ``` ``` ## [1] 675.9718 ``` ```r var( afl.margins ) # Skrati postupak ``` ``` ## [1] 679.8345 ``` --- # Standardna devijacija <br> <br> #### Matematička definicija <br> `$$s = \sqrt{ \frac{1}{N} \sum_{i=1}^N \left( X_i - \bar{X} \right)^2 }$$` <br> #### **Procjena** standardne devijacije `$$\hat\sigma = \sqrt{ \frac{1}{N-1} \sum_{i=1}^N \left( X_i - \bar{X} \right)^2 }$$` ```r # Izračunaj pomoću funkcije sd( afl.margins ) ``` ``` ## [1] 26.07364 ``` --- class: inverse, center, middle name: vpo # VARIJABLE I PODTAKOVNI OKVIRI <html><div style='float:left'></div><hr color='#EB811B' size=1px width=796px></html> (Deskriptivna statistika u praksi) --- # Deskriptivna statistika na varijabli <br> <br> ```r # Pregled numeričke varijable summary( object = afl.margins ) # Deskriptivna stat ``` ``` ## Min. 1st Qu. Median Mean 3rd Qu. Max. ## 0.00 12.75 30.50 35.30 50.50 116.00 ``` ```r # Pregled logičke varijable ekstremi <- afl.margins > 50 # Stvori log varijablu head(ekstremi,5) # Pogledaj podatke ``` ``` ## [1] TRUE FALSE TRUE FALSE FALSE ``` ```r summary(ekstremi) # Deskriptivna stat ``` ``` ## Mode FALSE TRUE ## logical 132 44 ``` --- # Deskriptivna statistika na varijabli ```r # Pregled faktorske varijable summary(object = afl.finalists) # Deskriptivna stat ``` ``` ## Adelaide Brisbane Carlton Collingwood ## 26 25 26 28 ## Essendon Fitzroy Fremantle Geelong ## 32 0 6 39 ## Hawthorn Melbourne North Melbourne Port Adelaide ## 27 28 28 17 ## Richmond St Kilda Sydney West Coast ## 6 24 26 38 ## Western Bulldogs ## 24 ``` ```r # Pregled tekstualne varijable txt <- as.character( afl.finalists ) # Stvori txt var summary( object = txt ) # Deskriptivna stat ``` ``` ## Length Class Mode ## 400 character character ``` --- # Drugi podatci ```r rm(list = ls()) # Očisti radni prostor load("./PODATCI/clinicaltrial.Rdata") # Učitaj podatke who(TRUE) # Pregled podataka ``` ``` ## -- Name -- -- Class -- -- Size -- ## clin.trial data.frame 18 x 3 ## $drug factor 18 ## $therapy factor 18 ## $mood.gain numeric 18 ``` ```r head(clin.trial, 5) #Pregled podataka ``` ``` ## drug therapy mood.gain ## 1 placebo no.therapy 0.5 ## 2 placebo no.therapy 0.3 ## 3 placebo no.therapy 0.1 ## 4 anxifree no.therapy 0.6 ## 5 anxifree no.therapy 0.4 ``` --- # Deskriptivna statistika na podatkovnom okviru ```r # Deksriptivna statistika na podatkovnom okviru summary(clin.trial) # Desktiptivna stat ``` ``` ## drug therapy mood.gain ## placebo :6 no.therapy:9 Min. :0.1000 ## anxifree:6 CBT :9 1st Qu.:0.4250 ## joyzepam:6 Median :0.8500 ## Mean :0.8833 ## 3rd Qu.:1.3000 ## Max. :1.8000 ``` --- # Deskriptivna statistika na podatkovnom okviru .tiny[ ```r # Deksriptivna statistika na podatkovnom okviru Hmisc::describe(clin.trial) # Desktiptivna stat/ druga funkcija ``` ``` ## clin.trial ## ## 3 Variables 18 Observations ## -------------------------------------------------------------------------------- ## drug ## n missing distinct ## 18 0 3 ## ## Value placebo anxifree joyzepam ## Frequency 6 6 6 ## Proportion 0.333 0.333 0.333 ## -------------------------------------------------------------------------------- ## therapy ## n missing distinct ## 18 0 2 ## ## Value no.therapy CBT ## Frequency 9 9 ## Proportion 0.5 0.5 ## -------------------------------------------------------------------------------- ## mood.gain ## n missing distinct Info Mean Gmd .05 .10 ## 18 0 17 0.996 0.8833 0.6281 0.185 0.270 ## .25 .50 .75 .90 .95 ## 0.425 0.850 1.300 1.490 1.715 ## ## lowest : 0.1 0.2 0.3 0.3 0.4, highest: 1.3 1.4 1.4 1.7 1.8 ## ## Value 0.1 0.2 0.3 0.4 0.5 0.6 0.8 0.9 1.1 1.2 1.3 ## Frequency 1 1 2 1 1 2 1 1 1 1 2 ## Proportion 0.056 0.056 0.111 0.056 0.056 0.111 0.056 0.056 0.056 0.056 0.111 ## ## Value 1.4 1.7 1.8 ## Frequency 2 1 1 ## Proportion 0.111 0.056 0.056 ## -------------------------------------------------------------------------------- ``` ] --- # Deskriptivna statistika na podatkovnom okviru .tiny[ ```r # Pregledaj grupirano prema terapiji by(data = clin.trial, # Izvor podataka INDICES = clin.trial$therapy, # Odredi grupiranje FUN = summary) # Odredi funkciju ``` ``` ## clin.trial$therapy: no.therapy ## drug therapy mood.gain ## placebo :3 no.therapy:9 Min. :0.1000 ## anxifree:3 CBT :0 1st Qu.:0.3000 ## joyzepam:3 Median :0.5000 ## Mean :0.7222 ## 3rd Qu.:1.3000 ## Max. :1.7000 ## ------------------------------------------------------------ ## clin.trial$therapy: CBT ## drug therapy mood.gain ## placebo :3 no.therapy:0 Min. :0.300 ## anxifree:3 CBT :9 1st Qu.:0.800 ## joyzepam:3 Median :1.100 ## Mean :1.044 ## 3rd Qu.:1.300 ## Max. :1.800 ``` ] --- # Deskriptivna statistika na podatkovnom okviru ```r # Pregledaj grupirano prema razlici u raspoloženju aggregate(mood.gain ~ drug + therapy, # Prikaz data = clin.trial, # Podatci FUN = mean) # AS ``` ``` ## drug therapy mood.gain ## 1 placebo no.therapy 0.300000 ## 2 anxifree no.therapy 0.400000 ## 3 joyzepam no.therapy 1.466667 ## 4 placebo CBT 0.600000 ## 5 anxifree CBT 1.033333 ## 6 joyzepam CBT 1.500000 ``` --- # Deskriptivna statistika na podatkovnom okviru ```r # Pregledaj grupirano prema razlici u raspoloženju aggregate(mood.gain ~ drug + therapy, # Prikaz clin.trial, # Podatci sd) # Standardna devijacija ``` ``` ## drug therapy mood.gain ## 1 placebo no.therapy 0.2000000 ## 2 anxifree no.therapy 0.2000000 ## 3 joyzepam no.therapy 0.2081666 ## 4 placebo CBT 0.3000000 ## 5 anxifree CBT 0.2081666 ## 6 joyzepam CBT 0.2645751 ``` --- class: inverse, center, middle name: sv # STANDARDIZIRANE VRIJEDNOSTI <html><div style='float:left'></div><hr color='#EB811B' size=1px width=796px></html> (Usporedba kruški i jabuka) --- # Standardizirane vrijednosti #### Matematička definicija <br> `$$\mbox{standardna vrijednost} = \frac{\mbox{vrijednost opservacije} - \mbox{prosjek}}{\mbox{standardna devijacija}}$$` <br> `$$z_i = \frac{X_i - \bar{X}}{\hat\sigma}$$` <br> `$$z = \frac{35 - 17}{5} = 3.6$$` ```r # Vidi dio u distribuciji pnorm( 3.6 ) ``` ``` ## [1] 0.9998409 ``` --- class: inverse, center, middle name: kor # KORELACIJA <html><div style='float:left'></div><hr color='#EB811B' size=1px width=796px></html> (Međusobni odnos dvije ili više varjabli) --- # Podatci ```r rm(list = ls()) # Očisti radni prostor # Učitaj podatke load("./PODATCI/parenthood.Rdata") who(TRUE) # Pregled podataka ``` ``` ## -- Name -- -- Class -- -- Size -- ## parenthood data.frame 100 x 4 ## $dan.sleep numeric 100 ## $baby.sleep numeric 100 ## $dan.grump numeric 100 ## $day integer 100 ``` ```r # Pregledaj podatke head(parenthood, 7) # Prvih 7 redova ``` ``` ## dan.sleep baby.sleep dan.grump day ## 1 7.59 10.18 56 1 ## 2 7.91 11.66 60 2 ## 3 5.14 7.92 82 3 ## 4 7.71 9.61 55 4 ## 5 6.68 9.75 67 5 ## 6 5.99 5.04 72 6 ## 7 8.19 10.45 53 7 ``` --- # Podatci .tiny[ ```r # Pogledaj deskriptivnu statistiku Hmisc::describe(parenthood) ``` ``` ## parenthood ## ## 4 Variables 100 Observations ## -------------------------------------------------------------------------------- ## dan.sleep ## n missing distinct Info Mean Gmd .05 .10 ## 100 0 90 1 6.965 1.164 5.138 5.434 ## .25 .50 .75 .90 .95 ## 6.292 7.030 7.740 8.172 8.473 ## ## lowest : 4.84 4.86 4.91 4.98 5.09, highest: 8.47 8.52 8.66 8.72 9.00 ## -------------------------------------------------------------------------------- ## baby.sleep ## n missing distinct Info Mean Gmd .05 .10 ## 100 0 88 1 8.049 2.381 4.698 5.591 ## .25 .50 .75 .90 .95 ## 6.425 7.950 9.635 11.083 11.612 ## ## lowest : 3.25 3.46 4.17 4.18 4.66, highest: 11.66 11.68 11.75 11.78 12.07 ## -------------------------------------------------------------------------------- ## dan.grump ## n missing distinct Info Mean Gmd .05 .10 ## 100 0 37 0.998 63.71 11.33 50.0 52.9 ## .25 .50 .75 .90 .95 ## 57.0 62.0 71.0 78.1 82.0 ## ## lowest : 41 44 46 48 50, highest: 80 82 86 89 91 ## -------------------------------------------------------------------------------- ## day ## n missing distinct Info Mean Gmd .05 .10 ## 100 0 100 1 50.5 33.67 5.95 10.90 ## .25 .50 .75 .90 .95 ## 25.75 50.50 75.25 90.10 95.05 ## ## lowest : 1 2 3 4 5, highest: 96 97 98 99 100 ## -------------------------------------------------------------------------------- ``` ] --- # Podatci <div class="figure" style="text-align: center"> <img src="03_PONAVLJANJEDESKRIPTIVNA_files/figure-html/parenthood-1.png" alt="Grafički prikaz varijabli u podatkovnom skupu." /> <p class="caption">Grafički prikaz varijabli u podatkovnom skupu.</p> </div> --- # Korelacija <div class="figure" style="text-align: center"> <img src="03_PONAVLJANJEDESKRIPTIVNA_files/figure-html/scatterparent1a-1.png" alt="Dijagram rasipanja za varijable `Sati spavanja/roditelj` i `Raspoloženje`." /> <p class="caption">Dijagram rasipanja za varijable `Sati spavanja/roditelj` i `Raspoloženje`.</p> </div> --- # Korelacija <div class="figure" style="text-align: center"> <img src="03_PONAVLJANJEDESKRIPTIVNA_files/figure-html/scatterparent1b-1.png" alt="Dijagram rasipanja za varijable `Sati spavanja/dijete` i `Raspoloženje`." /> <p class="caption">Dijagram rasipanja za varijable `Sati spavanja/dijete` i `Raspoloženje`.</p> </div> --- # Korelacija <div class="figure" style="text-align: center"> <img src="03_PONAVLJANJEDESKRIPTIVNA_files/figure-html/scatterparent2-1.png" alt="Dijagram rasipanja za varijable `Sati spavanja/dijete` i `Sati spavanja/roditelj`." /> <p class="caption">Dijagram rasipanja za varijable `Sati spavanja/dijete` i `Sati spavanja/roditelj`.</p> </div> --- # Kovarijanca <br> <br> #### Matematička definicija `$$\mbox{Cov}(X,Y) = \frac{1}{N-1} \sum_{i=1}^N \left( X_i - \bar{X} \right) \left( Y_i - \bar{Y} \right)$$` <br> <br> #### Pearsonov korelacijski koeficijent (standardizacija kovarijance) `$$r_{XY} = \frac{\mbox{Cov}(X,Y)}{ \hat{\sigma}_X \ \hat{\sigma}_Y}$$` --- # Smjer i intenzitet korelacije <div class="figure" style="text-align: center"> <img src="03_PONAVLJANJEDESKRIPTIVNA_files/figure-html/corr-1.png" alt="Različiti smjer i intenzitet korelacije." /> <p class="caption">Različiti smjer i intenzitet korelacije.</p> </div> --- # Izračun korelacije u R <br> <br> ```r # Izračunaj korelaciju između spavanja i raspoloženja cor(x = parenthood$dan.sleep, y = parenthood$dan.grump) ``` ``` ## [1] -0.903384 ``` ```r # Izračunaj korelacijsku tablicu cor(x = parenthood) ``` ``` ## dan.sleep baby.sleep dan.grump day ## dan.sleep 1.00000000 0.62794934 -0.90338404 -0.09840768 ## baby.sleep 0.62794934 1.00000000 -0.56596373 -0.01043394 ## dan.grump -0.90338404 -0.56596373 1.00000000 0.07647926 ## day -0.09840768 -0.01043394 0.07647926 1.00000000 ``` --- # Interpretacija korelacije Table: Okvirne smjernice za interpretaciju korelacije. |Korelacija |Snaga |Smjer | |:------------|:-------------|:---------| |-1.0 to -0.9 |Izrazito jaka |Negativna | |-0.9 to -0.7 |Jaka |Negativna | |-0.7 to -0.4 |Umjerena |Negativna | |-0.4 to -0.2 |Slaba |Negativna | |-0.2 to 0 |Zanemariva |Negativna | |0 to 0.2 |Zanemariva |Pozitivna | |0.2 to 0.4 |Slaba |Pozitivna | |0.4 to 0.7 |Umjerena |Pozitivna | |0.7 to 0.9 |Jaka |Pozitivna | |0.9 to 1.0 |Izrazito jaka |Pozitivna | --- # Podatci ```r rm(list=ls()) # Očisti radni prostor load("./PODATCI/effort.Rdata") # Učitaj podatke lsr::who(TRUE) # Pregledaj podatke ``` ``` ## -- Name -- -- Class -- -- Size -- ## effort data.frame 10 x 2 ## $hours numeric 10 ## $grade numeric 10 ``` ```r head(effort, 5) #Pregledaj podatke ``` ``` ## hours grade ## 1 2 13 ## 2 76 91 ## 3 40 79 ## 4 6 14 ## 5 16 21 ``` ```r cor(effort$hours, effort$grade) # Izračunaj korelaciju ``` ``` ## [1] 0.909402 ``` --- # Podatci .tiny[ ```r Hmisc::describe(effort) ``` ``` ## effort ## ## 2 Variables 10 Observations ## -------------------------------------------------------------------------------- ## hours ## n missing distinct Info Mean Gmd .05 .10 ## 10 0 10 1 36.8 30.76 3.80 5.60 ## .25 .50 .75 .90 .95 ## 18.75 34.00 55.75 68.80 72.40 ## ## lowest : 2 6 16 27 28, highest: 40 46 59 68 76 ## ## Value 2 6 16 27 28 40 46 59 68 76 ## Frequency 1 1 1 1 1 1 1 1 1 1 ## Proportion 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 ## -------------------------------------------------------------------------------- ## grade ## n missing distinct Info Mean Gmd .05 .10 ## 10 0 10 1 59.6 36.8 13.45 13.90 ## .25 .50 .75 .90 .95 ## 27.50 76.50 84.75 88.30 89.65 ## ## lowest : 13 14 21 47 74, highest: 79 84 85 88 91 ## ## Value 13 14 21 47 74 79 84 85 88 91 ## Frequency 1 1 1 1 1 1 1 1 1 1 ## Proportion 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 ## -------------------------------------------------------------------------------- ``` ] --- # Podatci <div class="figure" style="text-align: center"> <img src="03_PONAVLJANJEDESKRIPTIVNA_files/figure-html/rankcorrpic-1.png" alt="Odnos između sati studiranja i ocjene (svaka točka predstavlja jednog studenta)." /> <p class="caption">Odnos između sati studiranja i ocjene (svaka točka predstavlja jednog studenta).</p> </div> --- # Spearmanova korelacija ```r sati_studiranja <- rank( effort$hours ) # Rang sati ocjena <- rank( effort$grade ) # Rang ocjena ``` | | Rang sati rada | Rang visine ocjene | |-|---------------------|-----------------------| |student | 1 | 1 | 1 | |student | 2 | 10 |10 | |student | 3 | 6 | 6 | |student | 4 | 2 | 2 | |student | 5 | 3 | 3 | |student | 6 | 5 | 5 | |student | 7 | 4 | 4 | |student | 8 | 8 | 8 | |student | 9 | 7 | 7 | |student | 10 | 9| 9 --- # Spearmanova korelacija ```r cor(sati_studiranja,ocjena) # Izračunaj korelaciju ``` ``` ## [1] 1 ``` ```r # Dodaj argument "spearman" cor(effort$hours, effort$grade, method = "spearman") ``` ``` ## [1] 1 ``` --- class: inverse, center, middle # Hvala na pažnji <html><div style='float:left'></div><hr color='#EB811B' size=1px width=796px></html> (Nastavak: Inferencijalna statistika)