Introduction to Statistics in Psychology PSY 201 Greg Francis PhD Department of Psychological Sciences Psychological Sciences Building Room 3174 765 494 6934 email gfrancis purdue edu http www psych purdue edu gfrancis Classes PSY201 index html Study Guide for Final Exam Exam Date Monday December 13 1 00 3 00 pm Exam 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 answer questions will be similar to the problems on the homework but usually smaller and the previous exams However some of the questions will be essay questions where you must describe a concept The multiple choice questions will be about topics and definitions in the class The exam counts for 15 of your class grade You will be expected to perform some calculations so bring a calculator If any tables will be necessary 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 is to at least write out step by step what you do to carry out a hypothesis test and to create a confidence interval for every statistic we have discussed The crib sheet must be hand written no photocopies I will be happy to look over your crib sheet before the exam to check for any mistakes Know all of the following information Generally you need to both know how to do various calculations and understand the concepts behind the calculations The former you can verify by doing practice problems The latter you can verify by creating a written description of what the calculations are doing If the written description makes sense then you probably understand the concept In general you need to be able to do the calculations discussed in lecture and on the homework assignments For conceptual issues you need to understand the concepts discussed in lecture and the readings will often provide material that will help you do that Lectures 7 9 1 Know the basic properties of the normal distribution e g general shape symmetry parameters that define it 2 Know the properties of the standard normal distribution Be familiar with the shape of the exact standard normal 3 Know how to determine the proportion of scores in a specified range using a normal distribution 1 4 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 distribution 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 probability of a sample mean from a random sample Why does the sample have to be random Lecture 18 1 Understand the logic of hypothesis testing Know the terms region of rejection and 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 testing controls Type I error Know the term level of significance and know what it 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 to look 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 the calculations 2 Understand the conceptual distinction between a one tailed and a two tailed test Know how to look up the critical value for each case 3 Understand the conclusions that can be drawn after a hypothesis test Be able to explain the probabilistic aspect of the conclusion 4 Understand the difference between statistical significance and practical importance Lecture 20 2 1 Understand why the t distribution is used instead of the normal distribution for hypothesis tests of the mean Understand the effect of degrees of freedom on the 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 X Lecture 21 1 Understand point estimates and interval estimates Be able to explain why an interval 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 the probabilistic nature of confidence Lecture 22 1 Understand the relationship between hypothesis testing and confidence intervals 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 formula for 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 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 distribution and the formula for standard error 3 Know how to build a confidence interval for a proportion use the formula for standard error based on little p and q Lecture 25 3 1 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 of variance is assumed Know the sampling distribution and the calculation of standard error In particular know how to pool the sample variances from the two 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 the conclusion 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 of variance is not assumed Know the formulas for standard error and degrees of freedom Lecture 27 1 Understand the distinction between a two sample case with independent and