Introduction to Statistics in Psychology: PSY 201Greg Francis, PhDDepartment of Psychological SciencesPsychological Sciences Building, Room 3174, (765) 494-6934email: [email protected]://www.psych.purdue.edu/∼gfrancis/Classes/PSY201/index.htmlStudy Guide for Final ExamExam Date: Monday, December 13, 1:00-3:00 pmExam Location: Peirce 277 (same as regular class room)The exam will consist of 10 multiple choice questions and 9 short answer questions.Your worst score on the short answer questions will be dropped. The short-answerquestions will be similar to the problems on the homework (but usually smaller) andthe previous exams. However, some of the questions will be essay questions whereyou must describe a concept. The multiple choice questions will be about topics anddefinitions in the class. The exam counts for 15% of your class grade. You will beexpected to perform some calculations, so bring a calculator. If any tables will benecessary, I will provide them.I will not provide an equation sheet with the exam. Instead, you should create a“crib sheet” consisting of one piece of paper (both sides can be used). My advice isto (at least) write-out, step-by-step, what you do to carry out a hypothesis test andto create a confidence interval for every statistic we have discussed. The crib sheetmust be hand written (no photocopies). I will be happy to look over your crib sheetbefore the exam to check for any mistakes.Know all of the following information. Generally you need to both know how to dovarious calculations and understand the concepts behind the calculations. The formeryou can verify by doing practice problems. The latter you can verify by creating awritten description of what the calculations are doing. If the written descriptionmakes sense, then you probably understand the concept.In general, you need to be able to do the calculations discussed in lecture andon the homework assignments. For conceptual issues, you need to understand theconcepts discussed in lecture, and the readings will often provide material that willhelp you do that.Lectures 7–9.1. Know the basic properties of the normal distribution (e.g., general shape, sym-metry, parameters that define it,...).2. Know the properties of the standard normal distribution. Be familiar with theshape of the exact standard normal.3. Know how to determine the proportion of scores in a specified range using anormal distribution.14. Know how to determine percentiles in a normal distribution.5. Know how to determine percentile ranks in a normal distribution.6. Understand and know how to use the Standard Normal Table to find percentiles,percentile ranks, and proportions. The table will be provided on the exam.Lectures 15 – 17.1. Know what a sampling distribution is.2. Understand what the central limit theorem tells us about the sampling distri-bution of the mean.3. Understand what standard error refers to and how to compute it.4. Understand the connection between a sampling distribution and the probabilityof a sample mean from a random sample. Why does the sample have to berandom?Lecture 18.1. Understand the logic of hypothesis testing. Know the terms region of rejectionand critical value. Be able to explain (and draw pictures about) these terms.2. Understand Type I and Type II error. Be able to explain how hypothesis testingcontrols Type I error. Know the term level of significance (α) and know whatit means.3. Understand the importance of using random samples in hypothesis testing.4. Understand the role of the critical value and the test statistic. Know how tolook up the critical value and calculate the test statistic.Lecture 19.1. Be able to go through the four steps of hypothesis testing and carry out all thecalculations.2. Understand the conceptual distinction between a one-tailed and a two-tailedtest. Know how to look up the critical value for each case.3. Understand the conclusions that can be drawn after a hypothesis test. Be ableto explain the probabilistic aspect of the conclusion.4. Understand the difference between statistical significance and practical impor-tance.Lecture 20.21. Understand why the t-distribution is used instead of the normal distribution forhypothesis tests of the mean. Understand the effect of degrees of freedom onthe t-distribution.2. Know how to look up the critical value from the t distribution table.3. Know how to calculate the estimate of standard error.4. Understand how different terms affect the size of standard error of the mean,σX.Lecture 21.1. Understand point estimates and interval estimates. Be able to explain why aninterval estimate is generally better than a point estimate.2. Know how to build a confidence interval for a mean.3. Understand what the level of confidence corresponds to. Be able to explain theprobabilistic nature of confidence.Lecture 22.1. Understand the relationship between hypothesis testing and confidence inter-vals.2. Know the variables that will affect the size of a confidence interval.3. Understand what is meant by statistical precision.Lecture 23.1. Understand the need for the Fisher z transform when testing correlations.2. Know the sampling distribution of Fisher z transform scores and the formulafor standard error of zr.3. Know how to run hypothesis tests for correlations using the Fisher z transform.4. Know how to run a hypothesis test for the special case with H0: ρ = 0.Lecture 24.1. Know how to build a confidence interval using Fisher z transform scores.2. Know how to run hypothesis tests for proportions. Know the sampling distri-bution and the formula for standard error.3. Know how to build a confidence interval for a proportion (use the formula forstandard error based on little p and q).Lecture 25.31. Understand the distinction between a one-sample test and a two-sample test.2. Be able to run a two-sample hypothesis test for means, when homogeneity ofvariance is assumed. Know the sampling distribution and the calculation ofstandard error. In particular, know how to pool the sample variances from thetwo samples (using any of the formulas). Know the degrees of freedom.Lecture 26.1. Be able to test for homogeneity of variance. Know the sampling distribution,the test statistic (F -ratio) and how to get each of these terms. Know what theconclusion of the test means about running a hypothesis test for means.2. Be able to run a two-sample hypothesis test for means when homogeneity ofvariance is not assumed. Know the formulas for standard error and