Hypnosis-Diri
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Cam mane dgn loss/profit tt?demo account pun x pe. 
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pnc :"> hehehe
cam mane dgn loss/profit tt?demo account pun x pe. :d
pnc pulak dah..ingatkan tt nak ajar kitorang teknik correlation ni tadi..sepatah haram tak paham..

Power jugak.tt boring duk saje2,tt try correlation utk buat prediction guna Anova atau regression plak.![]()

uih...kalo gtu leh try multiple regression...SEM amos ke pls ke....lagipun multipair...
sori tt...gurau2 jek nga masta hipnosis ni![]()
Den bukan reti pun bab2 forex ni.Dah tt minat buat correlation, tu yg den suggest tu.Sebenarnya spearman correlation yg tt buat x sesuai sbb spearman ni utk data ordinal yg guna likert scale contohnya mcm dari skala 1 hingga 5 dimana 1 menunjukkan Sangat tidak setuju dan 5 menunjukkan sangat setuju.Forex mana guna data ordinal.Sbb tu den tya performance tt.
Pearson Correlation
The Pearson correlation coefficient (r) measures the strength and direction of the relationship between two continuous variables. It can take values in the [-1, 1] range.
<0.3 = Weak
0.3 - 07 = Medium
0.7-1.0 = Strong
Spearman correlation
The Spearman correlation (ρ) measures the relationship between two ordinal variables, or between an ordinal and a continuous variable. We can also use it when our variables are continuous, but they fail to meet some conditions (they are not normally distributed or their relationship is not linear).
<0.3 = Weak
0.3 - 07 = Medium
0.7-1.0 = Strong
Partial correlation
The partial correlation is the correlation between two continuous variables, controlled for a set of external variables called “controlling variables”. We use this correlation when we want to remove the effect of the controlling variables.
Depending on the number of controlling variables we can have:
- first order partial correlation (one controlling variable)
- second order partial correlation (two controlling variables)
- third order partial correlation (three controlling variables) and so on.
The simple Pearson correlation (without controlling variables) is also called zero order correlation.