HSS 2381 Chapter Notes - Chapter 9: Type I And Type Ii Errors, Null Hypothesis, Simple Linear Regression

• School: University of Ottawa
• Department: Health Sciences
• Course: HSS 2381
• Professor: Eleanor Riesen

Document Summary

Pearson"s r: a descriptive index that summarizes magnitude and nature (direction) of a relationship between two variables in a sample, can also be used to make inferences about relationships in the population. Basic hypotheses: correlational hypotheses are about (rho), the population correlation coefficient, basic null hypothesis: rho is zero. The (cid:373)ea(cid:374) of a sa(cid:373)pli(cid:374)g dist(cid:396)i(cid:271)utio(cid:374) of the (cid:272)o(cid:396)(cid:396)elatio(cid:374) (cid:272)oeffi(cid:272)ie(cid:374)t is , the populatio(cid:374) (cid:272)oeffi(cid:272)ie(cid:374)t: whe(cid:374) the (cid:374)ull h(cid:455)pothesis is t(cid:396)ue (cid:894)(cid:449)he(cid:374) = . 00(cid:895): The theoretical sampling distribution is centered on . 00. Assumptions and requirements: pea(cid:396)so(cid:374)"s r is suitable for (a) interval- and ratio-level variables (b) detecting linear relationships, pea(cid:396)so(cid:374)"s r can be used inferentially: If the variables have an underlying distribution that is bivariate normal (scores on x normally distributed for each value of y) If values on both variables are homoscedastic (for each value of x, variability of y scores about the same)