Lec5notes

EDFN 1090(1092) - LEC.5 > CORRELATIONS HOW ARE THINGS RELATED? you.(Chapter 16,17,18) Fill in this table before you work through the lesson. You may also use the glossary to help orrelalion Refers to the extent to which two variables are related across a group of participants Divect (or poeitive) Those who score high on one variable tend to score high on the other, and those who score low on one variable tend to score low on the other e\a Hmr\s\nig) wverse lory nctjmwQ ve ladian<h V') Those who score high on one variable tend to score low on the other Yeavson Y Statistic for describing the relationship between two variables, ranges from —1.00 to 1.00 (Symbol r, also known as Pearson product moment correlation coefficient, Pearson correlation coefficient, or the product- moment correlation coefficient) llustrates correlation between two variables (also known as a scatter diagram) fin'\'flarnm 'o adminivder YR somL test ywice Yo o~ G ?flf}i(!?flh*s w|\b\ou+ *rjnp'o 'o Cha 57009 fi\e 'pl\rh'n'\nmn"'s bebtween adpne: "z: 5 test vel '-ab'-\\h:\, o€ Yhe test, i('——r" iS hWign, bhe hes4 resHs are conSichent and e rest s said ro ne lll-flb"-- oe K icient of Aoy mithedvon 13 viekul in uhwga\nd&r\g wow wawveh af i vhKnoww v awv yaviable s explamed by ~ GV'O'"\QY VOV!.Ab'-(_ or vthAbLQS,

EDFN 1080(1092) ~ LEC.5 Correlation Concept: Correlation measures how two varlables co-vary on a scaleof -1~ | | |o] = no correlation | 01-03| =lowrelationship | 0.4-0.5| =moderate relationship | 0.6-0.9| = highrelationship [r.0] = perfect relationship Strength: The closer it is to the lower the weaker the relationship Direction: Positive and negative « Positive correlation — as numbers in one variable goes UP, the numbers in the other variable also goes (or DOWN and DOWN). Examples: e Shorter people have smaller shoe sizes e The more money she saves, the more financially secure she feels. e As the temperature goes up, ice cream sales also go up e As attendance at school drops, so does achievement More examples ' 05 dhe temperatvvt 9oed up the sales of swwweny 40¢S 0p. o Negative correlation — as numbers in one variable goes UP, the numbers in the other variable also goes[EI] (or the inverse: DOWN and then UP) Examples ; If it is darker outside, more light is needed inside. If a car decreases speed, travel time to a destination increases. st The older a man gets, the less hair that he has. The more one works, the less free time one has. More examples o9 RW\'cym\\flt 30.('\, AOwvs ) e sales of <\hovdts 0 eed> down.

EDFN 1090(1092) - LEC.5 Find strength, direction, and r: X Strength: Week, Moderate, Strong X Direction: Positive (+) or negative (-) X Correlation coefficientr: 9. -9 -7 -5 3 0 - 4 vl IL': Lk sanpzaandil 0o ga 7{ 3L - — . [ ® L 4 > L] gFfe"chi_ —Strona strength: _weak Strength: S\t ohg rection: _+_, r= Direction: _+_, r= Direction: = ,r=- o b ! a L- b ° \4\ » #j ol ® o ™~ P\\' o 5 \.i b e ° \ & o) € K - » . - . = L] ° E:::ZU?'::':_ '_'m\_fi_ 5 Strength: strong Strength: weark '——' ——— Direction: = , r= Direction: __ ,r= — Interpretation Correlation DOES NOT mean covsplion e We don't say, Variable X causes Variable Y. e We do say, Variable X and Variable Y are related and we do not know whether X causes Y or Y cause X. Types of correlations ® *pearson Correlation r (used for numerical data) ® Spearman Rho (used for one or both ordinal data) ® Point- biserial (used for one dichotomous [binary] variables) ® Phi(used for two dichotomous variables)