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Class Notes for Essentials of Statistics for the Behavioral Sciences , 2nd Edition

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    | C H A P T E R ON E | An Introduction to Statistics and Research Design NOTE TO INSTRUCTORS Thi s chapte r i s essentia l t o understandin g concept s use d repeatedly throughout the text. Therefore, instructors should spend extra time on this material to ensure a smooth transition to future chapters. In particular, emphasize the differences between inferential and descriptive statistics, independent and dependent variables, and the different kinds of variables (e.g., nominal vs. interval), all of which students will need to understand when working with the exercises and examples in the text. These founda - tional concepts need to be discussed and reviewed to give students every advantage in mastering statistics. To best illustrate the meanings and appli - cations of these concepts, use a number of everyday examples. You’ll find that the discussion questions and class exercises have been designed to help you in this process. OUTLINE OF RESOURCES I. The Two Branches of Statistics ■ Discussion Question 1 - 1 (p. 2) ■ Classroom Activity 1 - 1: Statistical Jeopardy (p. 2) II. How to Transform Observations into Variables ■ Discussion Question 1 - 2 (p. 5) ■ Classroom Activity 1 - 2: A Stroop Task (p. 5) III. Variables a nd Research ■ Discussion Question 1 - 3 (p. 6) ■ Discussion Question 1 - 4 (p. 6) IV. Introduction to Hypothesis Testing ■ Discussion Question 1 - 5 (p. 7) ■ Discussion Question 1 - 6 (p. 7) ■ Classroom Activity 1 - 3: Newspaper Experiment (p. 8) ■ Classroom Activity 1 - 4: Article Examination (p. 8) 1

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    2 CHAPTER 1 AN INTRODUCTION TO STATISTICS AND RESEARCH DESIGN ■ ■ Classroom Activity 1 - 5: In the Media (p. 8) ■ Additional Reading (p. 8) ■ Online Resource (p. 9) V. Handouts and Transparency Masters ■ Handout 1 - 1: Newspap er Experiment (p. 10) ■ Handout 1 - 2: Article Examination (p. 11) ■ Handout 1 - 3: In the Media (p. 12) ■ Transparency Master 1 - 1: Statistical Jeopardy Scoreboard (p. 13) ■ Transparency Master 1 - 2: Statistical Jeopardy: Answers (p. 14) CHAPTER GUIDE I. The Two Branches of Statistics 1. The two branches of statistics are descriptive statistics and inferential statistics. Descriptive statistics organize, summarize, and communicate a group of numerical observations, whereas inferential statistics use sample data to make general estimates about the larger population. 2. When discussing inferential statistics, we must distinguish between a sample and a population. A sample is a set of observations drawn from a population of interest that should be representative of that population of interest. In contrast, a population refers to all possible observations about which we’d like to know something. Samples are more commonly used because it is generally difficult to obtain data from an entire population. In other words, using data from a popu - lation often would take too much time and money or might be too vast to obtain based on the research question. > Discussion Question 1 - 1 What is the difference between a sample and a pop ulation? Why do you think that using a sample is more common when using inferential statistics? Your students’ answers should include: ■ A population includes all possible observations, whereas samples include sets of observations drawn from the popu lation of interest. ■ Usin g a sampl e i s mor e commo n wit h inferentia l statistic s becaus e of th e tim e neede d t o gathe r th e dat a an d t o complet e th e study , th e fund - in g consideration s o f th e study , an d th e usefulnes s o f th e stud y onc e it i s completed . Classroom Activity 1 - 1 Statistical Jeopardy This activity will help your students to master the basic statistical defini - tions. It also makes good use of classroom response system (“Clicker”) technology in your lecture. (For more information, visit www.iclicker.com.)

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    CHAPTER 1 AN INTRODUCTION TO STATISTICS AND RESEARCH DESIGN 3 ■ Instructions ■ Just as on the popular game show, the answer is provided to the contes - tants (students), who must then provide the question that directly corre - sponds to the answer. Their response must be in the form of a question. ■ Transparencies: You may display the game on an overhead projector by photocopying them onto acetate. Or you may use PowerPoint by scan - ning them into your computer. ■ How to play: Two options: Option 1: Have your students pick which question they want to try to answer; or , depending on the size of your class, you may prefer to have your students work in teams and for the teams to choose which questions to answer. Use Transparency Master 1 - 2 only to read off the “answers” to the student or group, and display Transparency Master 1 - 1 to the stu - dents. Both transparencies can be found at the end of this chapter. Your students can respond with their i>clicker remotes if you use i>clicker in your classroom. Option 2: You can be in charge of assigning “answers” to students. If ke eping score, to be fair, assign the answers according to seating arrange - ments, such as by row. Use Transparency Master 1 - 2 both to display to the students as well as to read the answers to the students. ■ On the transparency master, check off the completed items for the stu - dents as the game progresses. ■ You can designate a scorekeeper if you are playing in teams; otherwise have the students keep track of their scores.

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    4 CHAPTER 1 AN INTRODUCTION TO STATISTICS AND RESEARCH DESIGN ■ STATISTICAL JEOPARDY: RESPONSES (QUESTIONS) TO THE ANSWERS (These are responses the students should provide.) Statistics Basics 100 Sample 200 Population 300 Descriptive 400 Inferential Variables 100 Variable 200 Continuous variable 300 Nominal 400 Interval Experimental Design 100 Random Assignment 200 Correlational 300 Within - groups design 400 Confounding variable

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    CHAPTER 1 AN INTRODUCTION TO STATISTICS AND RESEARCH DESIGN 5 ■ II. How to Transform Observations into Variables 1. Regardles s o f whethe r w e ar e usin g descriptiv e o r inferentia l statis - tics , w e wil l nee d t o transfor m ou r dat a int o variable s o r observa - tion s o f physical , attitudinal , an d behaviora l characteristic s tha t can tak e o n differen t values. 2. When we create variables from our data, they can be either discrete (only specific values and no other values can exist between these num - bers) or continuous (can take a range of values where an infinite num - ber of potential values exist). a. Discrete variables can take two forms. Nominal variables use cat - egories or names for their values. Ordinal variables refer to values that are ranked. b. Continuous variables can also take two forms. Interval variables take numerical form, and the distance between pairs of consecu - tive numbers is assumed to be equal. Interval variables do not have a meaningful zero point. In contrast, ratio variables work just like interval variables except that they do have a meaningful zero point. c. Many statistical progams treat ratio and interval variables similarly and refer to them both as scale variables or variables that meet the criteria for an interval or ratio variabl e. > Discussion Question 1 - 2 What are some everyday examples of nominal, ordinal, interval, and ratio variables? Your students’ answers may include: ■ For nominals: Any group of objects or people likely to be studied, such as men and women, or vari ous physical characteristics such as height, age, weight, or hair color. ■ For ordinals: Any group that has ranking, such as from the tallest person to the shortest person. ■ For intervals: A group of objects that are spaced the same distance apart, such as oranges lined up an equal distance from each other, or half - steps in a chromatic musical scale; and in time - measured tests, the time it takes participants to react to certain stimuli. ■ For ratios: The scores of a group of sprinters or the amount of time it takes persons in a group to react to a request. Classroom Activity 1 - 2 A Stroop Task The research on levels of processing indicates that we learn better when the information we are trying to acquire has meaning to us. In order to make data analysis meaningful and learn statistics, have your students complete the Stroop experiments at the following link: http://www.snre.umich.edu/eplab/demos/st0/stroopdesc.html.

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    6 CHAPTER 1 AN INTRODUCTION TO STATISTICS AND RESEARCH DESIGN ■ (Note : Thi s experimen t require s tha t you r computer s ar e running Shockwave.) Have your students collect their individual time data for each of the three tasks: word, color, color not word. Have your students note their errors for each of these measures. Collect the data and enter it into SPSS (Statistical Package for the Social Sciences) as a group. Run the basic descriptive statistics on each vari - able. This data set can be used later in the course as well, when discussing correlated t tests or repeated - measures analysis. You can also gather group - ing information (e.g., gender or those who read more than 10 hours per week versus those who read less) to use for t tests and analysis of variance. III. Variables and Research 1. Levels are the discrete values or conditions that variables can take on. 2. There are three main types of variables used in research. Independent variables must have at least two levels that we either manipulate or observe in order to determine the effects on the dependent vari - able, which is the outcome variable that we are measuring and that we hypothesize to be related to or aroused by changes in the independent variable. A good mnemonic is that the dependen t variabl e depend s o n the independen t variables . A s researcher s w e wan t t o minimiz e th e presence o f th e monkey - wrenchin g confounding variables, which are variables that systematically vary with the independent variables so that we can - not determine which variable is at work. > Discussion Question 1 - 3 What would be an example of some confounding variables in an experiment whose aim is to test the effectiveness of an investigational medication to treat depression? Your students’ answers may include: ■ For confounding variables: Other required medications that the partici - pants were taking at the time of the experiment and variations in diet and exercise among participants. 3. Whenever we make observations, we want to make sure that our instru - ments are both reliable, or consistent, and valid, or accurate; in other words, that they measure what they are intended to measure. > Discussion Question 1 - 4 Imagine a scale that reads “5.0 pounds” each time you place a 10 - pound bag of potatoes on it. Is this scale reliable? Is this scale valid? Why or why not? You r students’ answers should include: ■ The scale is reliable because, each time, it consistently weighs the pota - toes at the same weight, 5.0 pounds. ■ The scale is not valid because the potatoes do not weigh in at their actual weight.

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    CHAPTER 1 AN INTRODUCTION TO STATISTICS AND RESEARCH DESIGN 7 ■ IV. Introduction to Hypothesis Testing 1. In hypothesis testing, we draw conclusions about whether or not a particular relation between variables is supported by the evidence. 2. Before we can do any hypothesis testing, we need to make sure that we have developed operational definitions for our variables. In other words, we must specify operations or procedures used to measure or manipulate a variable. 3. One way to test a hypothesis is to perform a correlational study. A cor - relation is an association between two or more variables. 4. An experiment is a study in which participants are randomly assigned to a condition or level of one or more independent variables. 5. When conducting an experiment, we can use random assignment so that every participant has an equal opportunity to be assigned to any condition. Random assignment allows us to control for confounding variables. > Discussion Question 1 - 5 Why would we want to use random assignment in an experiment? What would this accomplish? Your student s’ answers should include: ■ Random assignment controls the effects of biases or confounds by dis - tributing them among each condition, or group, in a study. It creates an initial equality between groups and allows a fair, unbiased test of the hyp othesis. 6. Experiment s ca n tak e tw o forms : between - group s o r within - groups researc h design . I n a between - group s design , participant s experienc e only on e leve l o f th e independen t variable . I n contrast , i n a within - groups design , participant s experienc e al l level s o f th e independen t variable. 7. We cannot use random assignment in all designs. When participants cannot be randomly assigned to all conditions, our design must become correlational . > Discussion Question 1 - 6 What would be an example of a with in - groups design? What would be an example of between - groups design? Your students’ answers may include: ■ Within - group s design : A dru g stud y wher e th e participants ’ reaction s t o a dru g ar e teste d befor e an d afte r th e administerin g o f th e drug. ■ Between - groups design: Two groups of participants where one group receives the drug and another group receives a placebo. ■ Within - groups design: Have participants take surveys measuring their attitudes toward police before and after they se e two movies: movie A that depicts the police positively and movie B that depict the police negatively.

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    8 CHAPTER 1 AN INTRODUCTION TO STATISTICS AND RESEARCH DESIGN ■ ■ Between - groups design: Have two different groups of participants watch either movie A or movie B. Classroom Activity 1 - 3 Newspaper Experiment Design an experiment to examine how regularly reading a newspaper would affect participants’ vocabulary levels. Generate and answer some basic ques - tions. See Handout 1 - 1 at the end of this chapter for examples of questions to ask. This exercise will reinforce learning through students’ application of the knowledge gained from Chapter 1. Classroom Activity 1 - 4 Article Examination As budding psychology researchers, students must have exposure to the psychological literature and gain practice reading, understanding, and cri - tiquing articles. This exercise is designed to encourage such intellectual development and to help students integrate the knowledge gained from reading this chapter. Have students read the following article: Bushman, B.J. (2005). Violence and sex in television programs do not sell products in advertisements. Psychological Science, 16, 702 – 708. (To view or purchase this article, go to your local library or visit Blackwell Publishing online at http:// www.blackwellpublishing.com.) Briefly, participants watch television programs with either violence or sexual content, both violence and sexual content, or no violence or sexual content. While watching the program, participants were exposed to 12 ads. Exposure to either violence or sexual content in programming negatively affected participants’ attitudes and behavior for the product. See Handout 1 - 2 at the end of this chapter. Classroom Activity 1 - 5 In the Media Newspapers are a great resource for exploring how research is relayed to the larger population. For this exercise, either obtain recent science news articles or ask students to obtain them instead. Find newspaper articles on the same subjects. Based on the description of the research in the science journals, have students try to identify different concepts from the chapter. See Handout 1 - 3 at the end of this chapter for questions to ask the class. Additional Reading Upton, G., & Cook, I. (2006). A Dictionary of Statistics. Oxford: Oxford University Press. This is a straightforward, easy - to - understand, yet comprehensive dic - tionary that is also suitable for students.

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    CHAPTER 1 AN INTRODUCTION TO STATISTICS AND RESEARCH DESIGN 9 ■ Online Resource Statistics Education Research Journal is a free online journal that publishes twice per year. The mission of the journal is to improve the teaching and learning for statistics. http://iase - web.org/Publications.php?p=SERJ

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    10 CHAPTER 1 AN INTRODUCTION TO STATISTICS AND RESEARCH DESIGN ■ HANDOUT 1 - 1: NEWSPAPER EXPERIMENT Directions: Design an experiment to examine how reading a newspaper regularly would affect participants’ vocabulary levels. 1. What is the procedure? What is the actual design of your study? 2. What is/are the independent variable(s)? 3. What is the dependent variable? 4. What are possible confounding variables? 5. Is this a between - groups or within - groups design? How do you know?

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    CHAPTER 1 AN INTRODUCTION TO STATISTICS AND RESEARCH DESIGN 11 ■ HANDOUT 1 - 2: ARTICLE EXAMINATION Directions: Read the article, Bushman, B.J. (2005). Violence and sex in television programs do not sell products in advertisements. Psychological Science , 16, 702 – 708. Answer each of the ques - tions below. 1. Summarize the procedure and results of the study. 2. What is/are the independent variable(s)? 3. What are some of the dependent variables that were measured? 4. What confounding variables did the researchers control for? 5. Is this a between - groups or within - groups design? How do you know?

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    12 CHAPTER 1 AN INTRODUCTION TO STATISTICS AND RESEARCH DESIGN ■ HANDOUT 1 - 3: IN THE MEDIA Directions: Using a newspaper article, try to identify the following concepts described in the chap - ter. 1. Summarize the research that was conducted by the researcher(s). What did the researcher(s) actually do? What were the findings? 2. What kind of study is this? 3. Can you identify any potential confounding variables in this particular design? 4. Was the author successful in communicating the main points of the research con - ducted? How could it have been improved? 5. If possible, find the primary source of this research (i.e., the study published in a scien - tific journal rather than summarized in a newspaper). Does the primary source match the main points of the newspaper article? Were there elements left out of the newspa - per article? Why might the two sources be different?

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    CHAPTER 1 AN INTRODUCTION TO STATISTICS AND RESEARCH DESIGN 13 ■ TRANSPARENCY MASTER 1 - 1 Statistical Jeopardy Scoreboard Statistics Basics Variables Experimental Design 100 100 100 200 200 200 300 300 300 400 400 400 Nolan/Heinzen: Statistics for the Behavioral Sciences, 2e © 2014, 2011 by Worth Publishers

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    14 CHAPTER 1 AN INTRODUCTION TO STATISTICS AND RESEARCH DESIGN ■ TRANSPARENCY MASTER 1 - 2 Statistical Jeopardy: Answers Statistics Basics Variables Experimental Design 100: A set of some observations 100: Any observation that can take on different values 100: Every participant has an equal chance to be assigned to any group 200: All possible observations in a study 200: A variable that can take on a full range of values (including decimals) 200: When looking for an asso - ciation between two or more variables 300: Numbers that are orga - nized and that summarize information 300: A variable that has catego - ries but no rankings 300: A variable that systemati - cally varies with the inde - pendent variable 400: Numbers (estimates) that hopefully can be general - ized back to the popula - tion 400: A variable with equal - distant values but no true zero 400: Participant experiences all the levels of the indepen - dent variable Nolan/Heinzen: Statistics for the Behavioral Sciences, 2e © 2014, 2011 by Worth Publishers

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    | C H A P T E R T W O | Frequency Distributions NOTE TO INSTRUCTORS In this chapter, instructors should emphasize the importance of visually representing data. The chapter describes the different ways of organizing the data in terms of a frequency distribution. The various shapes of distri - butions are also presented. Students often forget the importance of visually representing the data that they work with. As a result, it would be useful to show students how valuable visual representation can be by demonstrating how frequency distributions can be used to aid in getting a quick “snapshot” of data that are collected. OUTLINE OF RESOURCES I. Frequency Distributions ■ Discussion Question 2 - 1 (p. 16) ■ Discussion Question 2 - 2 (p. 17) ■ Discussion Question 2 - 3 (p. 17) ■ Discussion Question 2 - 4 (p. 18) II. Shapes of Distributions ■ Discussion Question 2 - 5 (p. 18) ■ Classroom Activity 2 - 1: Exploring Shapes of Distribution (p. 18) ■ Online Resources (p. 19) ■ Additional Reading (p. 19) III. Handouts ■ Handout 2 - 1: Exploring Shapes of Distribution (p. 20) 15

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