6540 Study Guide - Final Guide: Venn Diagram, Odds Ratio, Summary Statistics

• School: University of Canberra
• Department: University of Canberra
• Course: 6540
• Professor: Dr Sumaira Qureshi

Document Summary

Sampling distribution (gpa question): mean = 3. 4, standard deviation = 0. 35, sample size = 25. Let x be the gpa of incoming freshman ((cid:1850)~(cid:4666)(cid:885). (cid:886),(cid:882). (cid:885)(cid:887)(cid:4667) population distribution. Random samples = 25, let x be the mean gpa of incoming freshman; (cid:1850)~((cid:885). (cid:886),(cid:4666)(cid:882). (cid:885)(cid:887), (cid:884)(cid:887)(cid:4667)) = ((cid:1850)~(cid:4666)(cid:885). (cid:886),(cid:882). (cid:882)(cid:889)(cid:4667) sampling distribution. Assumptions/conditions: the students are randomly assigned to seminars (cid:1006). It is reaso(cid:374)a(cid:271)le to thi(cid:374)k that gpa"s for ra(cid:374)do(cid:373)ly. Selected students are mutually independent: the 25 students certainly represents less than. 10% of the population of students: the distribution of gpas is roughly normal, so. Since the conditions are met, the clt tells us that. We can model the sampling distribution of the mean. Gpa with a normal model, with u(ybar)=3. 4 and. P(x>3. 61) = (100%-99. 7%)/2= 0. 15% of high school gpa is over 3. 61. Step 1: descriptive statistics, mean = estimate, confidence level 95% = margin. satisfy conditions for inference. Lb = estimate (cid:373)argi(cid:374), ub = esti(cid:373)ate + (cid:373)argi(cid:374).