1. Non-experimental Correlational research u Determine whether 2 or more variables are associated, u If so, to establish direction and strength of relationships u Observe variables as they are, –can’t manipulate them

2. Causal - (Experimental) u one variable directly or indirectly influences another. Correlational - (Non-experimental) u Changes in one variable accompany changes in another. u A relationship exists. Don’t know if either variable actually influences the other.

3. Correlational research u If correlation -- relationship exists, u Predict from value of one variable, the probable value of the other variable. –Variable used to predict is predictor variable –Variable being predicted is criterion variable

4. Example: Test Score  Ten students took a Chemistry class and a Biology class together  Compared final exam scores in two classes J I H G F E D C B A 9894 9390 89 8388 8580 8378 8276 6972 6870 6562 BiologyChemistry

5.  Students who get higher score in the Chemistry class also get higher score in the Biology class

6. Positive Correlation u When scores of two variables move in same direction, these variables are positively (or directly) correlated u Positive correlation between between chemistry final score and biology score u When two variables are positively correlated, scatter plot shows a trend line that runs from lower-left to upper-right

7. Example: Test Score  The same students also took an Art class  Compared final exam scores in Chemistry and Art J I H G F E D C B A 7194 7390 7489 7588 7780 7778 76 7472 8070 9062 ArtChemistry

8. Example: Scatter Plot  Students who got higher score in Chemistry class got lower score in Art Class

9. Negative Correlation u When scores of two variables move together in the same direction, we say that these variables are negatively (or inversely) correlated u There is a negative correlation between between the chemistry final score and the art final score u When two variables are negatively correlated, the scatter plot shows a trend line that runs from upper-left to lower-right

10. Example: Test Score  The same ten students also took an English class together  Compare the English final score with the Chemistry final score J I H G F E D C B A 7694 8990 6089 7588 9080 78 7576 9072 6070 8562 EnglishChemistry

11. Score in Chemistry and Score in English are not related Test score

12. No Correlation u When the change in one variable does not affect the change in another variable, these variables have no correlation u No correlation between chemistry final score and English score u When two variables have no correlation, the scatter plot shows the dots scattered throughout the grids

13. Correlation (SSS) Sign Size Significance

14. SIGN u (0: No systematic relationship) Positive: As one variable gets bigger, so does the 2nd Negative: As one variable gets bigger, the 2 nd gets smaller

15. Correlation Co-efficient +10 NegativePositive Stronger Weaker Perfect None

16. Correlation Co-efficient u indicates how strongly and in which direction two variables are correlated with each other u A correlation co-efficient varies –1 to +1 u Indicated as r u r = +1: Perfect positive correlation If one variable increases by x%, other variable also increases by x% u r = - 1: Perfect negative correlation u r = 0: No correlation

17. Cannot say one variable causes the other in correlational research u The relationship between variables might be caused by an unobserved third variable -- “third variable problem” u Direction problem –Which came first? Which influences the other? (It may not have any influence on the other) –E.g., child’s level of aggression or amount of time watching violent TV?

18. Correlational research u When changes in one variable accompany changes in another, they covary -- a relationship exists. u Does not mean they influence the other. u Correlation does NOT imply causation (Non-experimental)

19. Correlational research u Men’s drive for thinness scores were positively correlated with weight gain. u / Greater concern about being thin was associated with more weight gain. (Heatherton et al, 1997) Can’t say concern for thinness causes men to gain wt. –POSSIBILITIES: »Concern about being thin causes weight gain »Weight gain causes concern about being thin »“X” (3rd variable) causes weight gain and concern about being thin.