SWP 538 Lecture Notes - Lecture 10: Nonparametric Statistics, Parametric Statistics, Statistical Inference

• School: Ryerson University
• Department: Social Work
• Course: SWP 538
• Professor: Notisha Massaquoi

Document Summary

Inferential statistics: statistical procedures that examine associations between variables and use significance tests and other measures to make inferences about the collected quantitative data. There are two types of inferential statistics parametric and nonparametric. Nonparametric statistics are used when the data departs from the criteria established for parametric statistics. Reading statistical notation r = correlation p = probability value. < = less than (cid:1095) = less tha(cid:374) o(cid:396) e(cid:395)ual to. > = greater than (cid:1096) = g(cid:396)eate(cid:396) tha(cid:374) or equal to t score = hypothesis test result (t-test) F score = hypothesis test result (anova) x2 = chi-square. This analysis assumes that both the independent and dependent variables are measured at the interval or ratio level. Also called bivariate analysis or simple regression. The(cid:396)e a(cid:396)e se(cid:448)e(cid:396)al othe(cid:396) (cid:271)i(cid:448)a(cid:396)iate asso(cid:272)iatio(cid:374)s, i(cid:374)(cid:272)ludi(cid:374)g eta, ga(cid:373)(cid:373)a, la(cid:373)(cid:271)da, ke(cid:374)dall"s tau, a(cid:374)d pea(cid:396)(cid:373)a(cid:374)"s (cid:396)ho. Ho(cid:449)e(cid:448)e(cid:396), the pea(cid:396)so(cid:374)"s (cid:272)o(cid:396)(cid:396)elatio(cid:374) is so (cid:272)o(cid:373)(cid:373)o(cid:374)ly used that it is associated with the word correlation.