PSY 311Exam # 1 Study Guide Lectures: 4-8 9-10UtilitarianismJeremy Bentham and John Stuart Mill: Determine benefits and risks, If benefits outweigh risks, itis ethicalRights : Immanuel Kant: Moral rights are universal principals applied to every person equally and impartiallyInformed Consent: When do we need it?: Rule of thumb: If getting consent does not hurt the integrity of the research, then it should be obtained, Typically mandatory for situations where theperson’s environment is changed for the purpose of the study (but there are exceptions), Who is allowed to provide it?, Competent adults over 18 can provide own consent, Substitute consent (e.g., parent, caregiver) is needed otherwise, Assent (verbal or if possible, written) is also needed, if applicable, even if participant cannot provide consentChapter 4Standard deviation X-µ =0 , (x-µ)² = SS , ²= ss/n or ss/n-1 for sample ,  = ²Z=(x-µ)/ , X=µ+Z , =(X-µ)/z , µ=x-zChapter 6Standardizing a distribution 1. Turn scores into z scores 2. (new mean)+(new )(z)Sampling distribution: a distribution of sample means Normal distribution: if original population is normal , if sample size is >30 Standard error of M: a large sample should be more accurate than a small sample (law of large numbers) , m = /n , as sample size increase , the size of the standard error decrease , Z=M-µ/mChapter 8Hypothesis testing : 1. State the hypotheses 2. Determine the critical region3. Calculate the test statistic 4. Make a decision 5. Report the statistic in APA style Chapter 9T test T= (M-µ)/smEffect size: cohens d = (m-µ)/s if D is: 0.2 (small effect), 0.5 (medium effect) , 0.8 (large effect) r²= t²/ (t²+df): .01 and .09 (small effect) , .09 and .25 (medium effect) , > .25 (large effect) Confidence intervals µ= M + or – t(sm)Chapter 10Hypotheses H0: μ1 – μ2 = 0 H1: μ1 – μ2 ≠ 0 Estimated Standard Error• We make the assumption that the population variance (σ2) in both groups are the same• As we DO NOT know σ2, we need to estimate it using the sample variance from BOTH groups (pooled variance)Sp2 = (SS1 + SS2) / (df1 + df2)• Two-sample estimated standard errors(M1 – M2) = √[(Sp2 / n1) + (Sp2 / n2)]• Standard difference by chance between M1 and M2• t = [(M1 – M2) – (μ1 – μ2)] / s(M1 – M2)Effect Sizesd = (M1 – M2) / √ Sp2r2 = t2 / (t2 + df)Confidence Intervals• µ1 - µ2 = (M1 – M2) ± t(sM1 – M2)• Recall that the null hypothesis states that µ1 - µ2 = 0– Thus, we accept null hypothesis if 0 is in the confidence