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 Exam 1Exam Date: September 27, 2010 (during the regular class period)The exam will consist of 10-15 short-answer questions that will usually be similarto the problems on the homework (but usually smaller). However, some of the ques-tions will be essay questions where you must describe a concept. You will be expectedto perform some calculations, so bring a calculator. If any tables will be necessary, Iwill provide them. Any equations you might need on the exam will be provided, butyou need to know how to use the equations.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.The TA will hold an outside of class review session in preparation for the firstexam on Sunday 26 September 6:00 - 9:00 pm in LILY Room G401.(1) Lecture 2.1. Know the symbolic description of variables and the notation for addition, rulesof squaring,... (basic algebra).2. Know the distinctions between populations and samples and between dependentand independent variables.3. Know the properties and limitations of the scales of measurement. Know ex-amples of each. Be able to identify a variable’s scale of measurement (whenappropriate).(2) Lectures 3–4.1. Know how to interpret data from a table describing a frequency distribution.2. Know how to build a frequency table from raw data.13. Know how to work with exact limits, class intervals, and similar concepts.4. Know how to find frequency, frequency percentage, cumulative frequency, cu-mulative frequency percentage.5. Know the meaning of the terms positive skew, negative skew, symmetry, kur-tosis. Understand their significance.(3) Lectures 5–6.1. Know how to calculate percentile rank and percentiles from a frequency dis-tribution table. (The equations will be given, but you must know how to usethem.)2. Know how to find/calculate the mode, median (both methods), and mean.Know how they are generally affected by the shape of distribution. Know thedifferences between these measure of central tendency.3. Understand in what sense the different measures of central tendency are the“middle” of a distribution of scores.4. Know the properties of the mean. Know how to compute the mean from com-bined groups.5. Know how to calculate variance and standard deviation. Understand what isbeing calculated with these measures.6. Know the influence of outliers (extreme scores) on measures of central tendencyand variability.7. Know how to compute z scores (also called standard scores). Know the prop-erties of z scores. Know why you would want to compute z scores.8. Know how to compute transformed standard scores. Understand why you wouldwant to in some cases.(4) 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.4. Know how to determine percentiles in a normal distribution.5. Know how to determine percentile ranks in a normal distribution.26. 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.(5) Lectures 10–12.1. Understand the basic idea of correlation and correlation coefficients.2. Know the relationship between scattergrams and correlation.3. Know how to compute the Pearson r. (The equations will be given, but youmust know how to use them.)4. Know the factors that might affect the size of r: linearity, homogeneity, groupsize. Understand their significance.5. Understand how to interpret r values (rule of thumb, proportion of variance).6. Know how to calculate the Spearman ρ. (The equation will be given, but youmust know how to use it.)7. Understand the relationship between ρ and r.8. Understand the relationship between correlation and causality.3You may find the following equations useful. These equations will be available onthe exam.PX= ll + np − cffi!(w)P RX=(cf + (fi)(X − ll)/wn)(100)Mdn = ll + n(0.50) − cffi!(w)X =Pni=1XinX =PiniXiPinis2=Pi(Xi− X)2n − 1s2=PiX2i− [(PiXi)2/n]n − 1σ2=PiX2i− [(PiXi)2/n]nz =X − XsX = sz + Xrxy=Pzxzyn − 1rxy=PxiyiqPx2iPy2irxy=nPiXiYi−PiXiPiYirhnPiX2i− (PiXi)2ihnPiY2i− (PiYi)2irxy=sxysxsyr2=s2As2Yρ = 1 −6Pid2in(n2−