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**Myers PSYCHOLOGY Seventh Edition in Modules**

Research Strategies: How Psychologists Ask and Answer Questions James A. McCubbin, Ph.D. Clemson University Worth Publishers

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Observation The simplest scientific technique is observation. It is systematic. This means that you watch for specific behaviors and record what you see. For example you might be asked to document the color of the cars that go by your house between the hours of 5 pm and 7 pm. An example would be that you are asked to watch or observe two dogs playing in your backyard and write down what you see. The information that you collect is called data.

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Data Collection There are many ways that data can be collected. Data might be collected with a video recording device, by administering a questionnaire or using a checklist. The important thing is that it has to be collected so that other scientists who wish to repeat the observations can do so. No experiment is conducted with this method. The researcher does not attempt to change the environment during the data collection phase. The data are analyzed, and researchers look for interesting or important patterns. This technique can be used in studies of children.

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Types of Observation There are three types of observation – naturalistic observation, controlled observation and clinical observation.

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**Naturalistic Observation**

Naturalistic observation is observational research that takes place in a natural or everyday setting such as a school. Usually there is an effort to minimize the observer’s impact by carrying out observations secretly or from a hidden vantage point

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Examples Observing and recording the behaviour of students in the cafeteria Observing and recording the behaviour of geese in the field Observing and recording the behaviour of children at recess in the playground

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**Controlled Observation**

Controlled observation occurs when observational research is carried out under carefully arranged conditions. Each subject is exposed to the same situation to see differences between individual reactions.

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Examples Observing and recording the behaviour of students in the cafeteria when someone is crying or not crying Observing and recording the behaviour of geese in the field when a horn is blaring and is not blaring Observing and recording the behaviour of children at recess in the playground when there is an adult supervisor present and not present

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Clinical Observation Clinical observation consists of observations made by a skilled clinician interacting with a patient or client. The clinician takes notes on the interaction, usually immediately after the interview or meeting with the client.

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Bias Your observations may be influenced by what you want to discover. This is called researcher bias. Bias occurs whenever any factor unfairly increases the likelihood that the researcher will reach a particular conclusion. Researchers try to avoid bias. In our example, you might watch students using MP3 players and compare them with students not using MP3 players. Your observations may be influenced because you and the principal might observe students using MP3 players while studying and come to completely opposite conclusions. The principal who wants MP3 players banned, notices that students spend time mouthing the words to the songs that they are listening to instead of studying. You, on the other hand, see that the students who have MP3 players are not distracted by the other students in the library. Everyone notices only the behaviors that support their own ideas.

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**The Need for Psychological Science**

Critical Thinking thinking that does not blindly accept arguments and conclusions examines assumptions discerns hidden values evaluates evidence assesses conclusions One way to reduce researcher bias is to use critical thinking. This is thinking that does not blindly accept arguments and conclusions. In our example you could compare the grades of students who use MP3 players while studying with the grades of students who don’t use MP3 players. Or, you could have observers count specific behaviours, like how many times a student has a conversation with another student in a ten minute period, or how many pages a students reads in ten minutes. One of the flaws in this method is that turning pages doesn’t mean that studying is going on. The Amazing Randi—Skeptic

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Participant Bias Researchers must also watch out for participant bias. This it the tendency for research participants to respond in a certain way because they know they are being observed or they believe they know what the researcher wants. Maybe the students in our example will act differently when they know someone is watching them. They might study harder.

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Case Studies Researchers who study individuals in depth are using the case study method. This method is prone to bias. Sometimes a case study is all that can be done. For example, the only way to get information on the effects of child abuse is to find people who have reported abuse and study that person or group of people. Since no two cases are ever exactly alike, there is always some doubt as to the real effects.

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**Description Case Study**

observation technique in which one person is studied in depth in the hope of revealing universal principals In our example we could do an in-depth study of just one student in the library who uses an MP3 player. The results of this study would be unrepresentative. This means that you wouldn’t be able to make the same conclusions about everyone who uses an MP3 player while studying. Is language uniquely human?

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**Correlational Studies**

There are many times when it’s useful to know if two things or variables are related. The research technique that is used is the correlational study. In our example the two variables are whether or not a student uses an MP3 player, and how effective their studying is.

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**(positive or negative)**

Correlation Correlation Coefficient a statistical measure of the extent to which two factors vary together, and thus how well either factor predicts the other Indicates direction of relationship (positive or negative) Correlation coefficient r = +.37 Indicates strength of relationship (0.00 to 1.00)

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**Correlation Scatterplot**

a graphed cluster of dots, each of which represents the values of two variables the slope of the points suggests the direction of the relationship the amount of scatter suggests the strength of the correlation little scatter indicates high correlation also called a scattergram or scatter diagram

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**Scatterplots, showing patterns of correlations**

Perfect positive correlation (+1.00) No relationship (0.00) Perfect negative correlation (-1.00) Scatterplots, showing patterns of correlations

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**Height and Temperament of 20 Men**

Correlation Height and Temperament of 20 Men 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 80 63 61 79 74 69 62 75 77 60 64 76 71 66 73 70 68 90 42 81 39 48 72 57 30 84 Subject Height in Inches Temperament

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**Scatterplot of Height and Temperament**

Correlation 95 90 85 80 75 70 65 60 55 50 45 40 35 30 25 Temperament scores Height in inches Scatterplot of Height and Temperament

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**Correlation Three Possible Cause-Effect Relationships or or**

could cause (1) Low self-esteem Depression or (2) Depression could cause Low self-esteem Correlations can be either positive or negative. A positive correlation exists between two things if one variable increases or decreases and the other one does the same. If effectiveness of studying increases when students use MP3 players and decreases when they don’t use MP3 players then the two variables are positively correlated. A negative correlation exists between two things if one variable increases or decreases and the other variable does the opposite. If effectiveness of studying decreases when students use MP3 players and increases when they do not use MP3 players, the variables are negatively correlated. If there is no correlation it means that knowing something about one variable tells you nothing about the other variable. In our example, this would mean that there is no relationship between studying effectiveness and using an MP3 player while studying in the library. It is very important to remember that the discovery of a correlation does not prove that a cause-and-effect relationship exists. Correlational research results can tell you that certain variables are related, but not why they are related. or Low self-esteem (3) Distressing events or biological predisposition could cause and Depression

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**Illusory Correlation Illusory Correlation**

the perception of a relationship where none exists Conceive Do not conceive Adopt Do not adopt disconfirming evidence confirming

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**Other forms of data collection**

One of the easiest forms of data collection is administering a questionnaire. This is very similar to taking a poll. Professionals usually conduct surveys and polls, while amateurs administer questionnaires. In our example students could fill out a short questionnaire about the effect of using MP3 players while studying in the library.

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**Description Survey False Consensus Effect**

technique for ascertaining the self-reported attitudes or behaviors of people usually by questioning a representative, random sample of people False Consensus Effect tendency to overestimate the extent to which others share our beliefs and behaviors

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**The Need for Psychological Science**

Hindsight Bias we tend to believe, after learning an outcome, that we would have foreseen it the “I-knew-it-all-along” phenomenon Overconfidence we tend to think we know more than we do

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**Description Population Random Sample**

all the cases in a group, from which samples may be drawn for a study Random Sample a sample that fairly represents a population because each member has an equal chance of inclusion A population is the group from which a sample is taken for the study. The population in our example could be every student who uses the library to study in. Random sample From a population a random sample is used in a study because you couldn’t possibly collect data on everyone in the population. This group must represent the population. Each member must have an equal chance of being included in the study. The sample should not be too small in number. There are many ways to randomly select members. Some examples are drawing names out of a hat, choosing every 5th name from a list, giving everyone a number and then choosing the members. In our example to get a random sample, every member of the population must have an equal chance of being selected. If the population is the students who study in the library at your school, you could draw a random sample by selecting every 10th name from a list of students who say that they study in the library at the school.

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**Longitudinal and Cross-sectional studies**

Longitudinal studies follow the same group of individuals over many years. Cross-sectional studies compare people of different ages at one time. These studies are techniques of particular use to developmental psychologists, who study how individuals change throughout the lifespan. You could keep track of a group of students who study in the library throughout their lifetime to determine the long-term effects of using an MP3 player while studying. You could study different age group students whose use the library for studying.

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**The Need for Psychological Science**

Psychologists, like all scientists, use the scientific method to construct theories that organize observations and imply testable hypotheses In order to establish cause-and-effect the experimental method is the only method that allows us to draw conclusions about this type of relationships.

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**The Need for Psychological Science**

Theory an explanation using an integrated set of principles that organizes and predicts observations Hypothesis a testable prediction often implied by a theory In designing an experiment, the first thing we would do is to generate a hypothesis – a testable prediction of the experiment’s outcome. The hypothesis in our example would be that “Using an MP3 player influences concentration while studying in the library”.

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**The Need for Psychological Science**

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**The Need for Psychological Science**

Operational Definition a statement of procedures (operations) used to define research variables Example: intelligence may be operationally defined as what an intelligence test measures Researchers often start with general expectations, but then put their variables in a more specific form that allows them to be precisely measured. In the language of research, they provide operational definitions of the variables. The operational definition of the variables is that “Students assigned to use MP3 players in the library will have lower average grades at the end of the semester than students banned from using MP3 players”. There are many different ways to operationally define the variables. It could be “Students who use their MP3 player each day in the library while studying read fewer pages in a one hour block of time than students who are banned from using their MP3 player”.

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**The Need for Psychological Science**

Replication repeating the essence of a research study to see whether the basic finding extends to other participants and circumstances usually with different participants in different situations

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Description

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**Experimentation Experiment**

an investigator manipulates one or more factors (independent variables) to observe their effect on some behavior or mental process (the dependent variable) by random assignment of participants the experiment controls other relevant factors Once we have agreed on the hypothesis and the operational definition of the variables we still need to identify the two variables in the experiment as either the independent variable or the dependent variable. The variable that should cause something to happen is the independent variable (IV). The IV is the presence or absence of MP3 players. The variable that should show the effect of the IV (or the outcome) is the dependent variable (DV). The DV is the student’s grade point average at the end of the semester.

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**Experimentation Experimental Condition Control Condition**

the condition of an experiment that exposes participants to the treatment, that is, to one version of the independent variable Control Condition the condition of an experiment that contrasts with the experimental treatment serves as a comparison for evaluating the effect of the treatment The way we make the independent variable vary (take on different values) is to set up groups of participants. Typical experiments have at least two groups, an experimental group and a control group (sometimes these are referred to as the experimental and control conditions). The participants in the experimental group are exposed to the treatment, that is, the independent variable. The participants in the control group are not exposed to the independent variable. The purpose of this group is to serve as a comparison for the experimental group. In our example 40 students are selected to participate in the experiment by selecting every 10th name on the list of students who use the library for studying. These names are then placed in a hat and the first 20 names are assigned to the experimental group and the next 20 to the control group.

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**Confounding Variables**

The individual differences among participants are the largest category of a special kind of variable known as confounding variables. These are variables other than the IV that could produce a change in the DV. Confounding variables must be controlled for. You must eliminate as many of these as possible before you get your sample so that your results are accurate. Confounding variables in our example could include differences in IQ scores, the amount of sleep students get, the numbers of personal problems students have, and who the teacher was for a specific subject.

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Control Experimenters use a variety of techniques to minimize the effects of confounding variables. The researcher must account for the following: individual differences among participants environmental differences such as lighting, noise and temperature Did both groups study at the same time of day? Were the room temperature and lighting conditions the same for both groups?

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**Experimentation Random Assignment**

assigning participants to experimental and control conditions by chance minimizes pre-existing differences between those assigned to the different groups

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**Experimentation Independent Variable Dependent Variable**

the experimental factor that is manipulated the variable whose effect is being studied Dependent Variable the experimental factor that may change in response to manipulations of the independent variable in psychology it is usually a behavior or mental process

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Expectation Effects Expectation effects include making sure that participants are not aware of the hypothesis of the experiment. If they were, their expectations could influence the outcome. Did the experimental group expect to do better? Did the researchers expect the experimental group to do better?

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Procedures To control for such effects, experimenters use three different procedures the single blind procedure, the double blind procedure and the placebo.

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**Single Blind Procedure**

Experimenters often use a blind or masked procedure, which means that they don’t tell participants what the hypothesis is until after the data are collected.

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**Double blind Procedure**

In this procedure the people collecting the data don’t know the expected outcome of the research or which participants are in which group and the participants don’t know if they are in the experimental group or the control group.

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Placebo Experimenters use this special kind of control in all drug studies. It involves a non-active substance or condition that is administered instead of the drug.

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Review We are conducting an experiment to test the hypothesis that students assigned to use their MP3 player each day in the library while studying will have lower average grades at the end of the semester than students banned from using their MP3 player. The IV is the presence or absence of the MP3 player. The DV is the average grades at the end of the semester. Students were randomly selected from the entire population of students who use the library to study. We randomly assigned students to either the experimental group (using the MP3 player) or the control group (not using the MP3 player). All environmental conditions are as similar as possible.

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**Reliability and Validity**

There are safeguards required for experiments to make sure that the research is both valid and reliable. Research is valid when it measures what the researcher set out to measure; it is accurate. Research is reliable when it can be replicated; it is consistent. If an experimental result can be obtained only once, we must conclude that it was caused by chance and not by the independent variable. This means that there is no apparent cause and effect relationship between the independent variable and the dependent variable.

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**Experimentation Comparison of Research Methods **

The following outlines the advantages and disadvantages of the various research methods that we covered in this lesson. Systematic Observation: The systematic study of behaviour in natural settings. Advantage: Behaviour is observed in the settings where it normally occurs. Disadvantage: Cannot be used to establish cause-and-effect relationships; often it is costly and difficult to perform. Case Study Method: The detailed study of a small number of persons. Advantage: Detailed information is gathered; individuals can be studied for long periods of time. Disadvantage: Ability to generalize results is uncertain; the objectivity of the researcher may be comprised. Surveys: A large number of persons are asked questions about their attitudes or views. Advantage: Large amounts of information can be acquired quickly; accurate predictions of large scale trends can sometimes be made. Disadvantage: Ability to generalize may be questionable unless persons surveyed are a representative sample of a larger population. Correlational Research: Where two or more variables are measured to determine if they are related in any way. Advantage: Large amounts of information can be gathered quickly; can be used in field as well as laboratory settings. Disadvantage: Difficult to establish cause-and-effect relationships. Experimentation: The presence or strength of one or more variables is varied. Advantage: Cause-and-effect relationships can be established; precise control can be exerted over other potentially confounding variables. Disadvantages: Results can be subject to several sources of bias; ability to generalize can be doubtful if the behaviour is observed under highly artificial conditions.

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**Review of Experimental Method**

1. Develop the hypothesis. 2. Create operational definitions for the independent and dependent variables. 3. Randomly select a sample of participants from the population. 4. Randomly assign the participants to the experimental and control groups. 5. Expose the experimental group, but not the control group, to the IV. If necessary, use a placebo with the control group to balance expectations. 6. Control for other confounding variables by using a double-blind procedure and treating both groups the same except for exposure to the IV. 7. Learn the impact of the IV by measuring the DV for both groups and use statistical analysis.

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Examples Read the following scenarios and determine if the method used is correlational, experimental or observational. 1. Professor Black is interested in understanding the relationship between self-esteem and anxiety in group situations. 2. Researchers at the University of Manitoba are interested in studying relationships among employees at Boeing Aircraft. These researchers decide to go and observe the interactions of coworkers in the factory. 3. Professor Guptah wishes to study the effects of food deprivation on learning in rats. 4. Dr. Cheung and her colleagues wish to study the aggressive behaviour of elementary school children by observing the children at play. 5. A group of researchers from a child advocacy group wishes to examine the relationship between exposure to televised violence and later aggressive behaviour in children by asking parents to report on how much television their child watches and what types of programs their child has watched. 1. Correlational 2. Observational 3. Experimental 4. Observational 5. Correlational

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Examples continued 6. Dr. Beauchamp wishes to investigate the effects of a new training program at McDonald’s on employees’ job performance. 7. A group of researchers wishes to study the organizational culture of successful schools. 8. Dr. Cortez is interested in the relationship between the different strategies that a therapist uses and how effective those strategies are. 9 A group of researchers is interested in the effects of caffeine drinks like Red Bull on test performance. 10. Dr. Courchene is interested in studying peer influence among high school students by recording their clothing choices, hairstyles. 6. Experimental 7. Observational Correlational 9. Experimental 10. Observational

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Use of Statistics Without a basic understanding of statistics you are at a serious disadvantage because statistical information is all around us. For example, you hear that 9 out of 10 dentists want you to use a particular toothpaste, you learn about the earned run averages of the Winnipeg Goldeyes, and you hear that blue is the most favorite color of M and M. The overall purpose of statistics is to make data more meaningful.

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**Frequency Distributions**

A frequency distribution is an ordered list of scores from highest to lowest or lowest to highest. The data can then be easily presented as a bar graph. In the MP3 player example you could list the average semester grades for all the MP3 player users and for the non users.

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**Measures of Central Tendency**

1. Mode The mode is the score that occurs most frequently in the distribution. It is not the best source of information because it is possible for the mode to not be even close to the center of the distribution. 2. Mean The mean is the most familiar measure of central tendency. It is commonly called the average. You calculate it by adding together all of the scores and then dividing by the number of scores that you added together. The mean can be misleading if there are some really high or really low scores. Median 3. The median shows us the middle of a distribution. Once you have put all the scores in order you find the middle scores. The extremely high scores and the extremely low scores will not have an impact on the middle score.

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Measures of Variation Even though it is important to know where the center of a distribution falls it is also important to know how different or varied the scores are from the mode, mean and median. Range The simplest measure of variation is the range. It is the difference between the highest score and the lowest score.

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Standard Deviation Standard deviation is a measure of the overall variation of a distribution of numbers. The smaller the standard deviation, the more closely the scores are to the mean. The higher the standard deviation the more spread out the scores are. Normal Distribution A lot of psychological data can be represented in a graph called a normal distribution, or bell-shaped curve. The right and left sides of the curve are identical. The highest point represents all three measure of central tendency: the mode, the mean, and the median.

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**Comparative Statistics**

The two major comparative statistics are percentage and percentile rank. Percentage compares a score to an imaginary score of 100. Percentile rank compares one score with other scores in an imaginary group of 100 individuals. It tells you where a particular score stands in that group and how many people had equal or lower scores.

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**Correlation Coefficient**

The correlation coefficient is a number that represents how strong a relationship is between two variables. The number has a value between -1 and +1. If the correlation coefficient (r) has a value of -1 then we have a perfect negative correlation. This means that every time one variable increases the other variable decreases by the same amount. If r=+1 then we have a perfect positive correlation. This means that every time one variable increases the other variable increases by the same amount. If r=0 then there is no correlation.

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Scatterplot Remember r values can be anywhere between -1 and +1. They are represented in a graph called a scatterplot. The data is mapped as dots on this type of graph.

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**Statistical Inference**

The statistics so far in this lesson are called descriptive statistics because they describe data in a way that makes them more meaningful. Another kind of statistics that is important for psychologists is called inferential statistics. This lets us make decisions or reach conclusions about a set of data. In our MP3 player example we collected grade average data from our two groups: the experimental group whose members used MP3 players while studying and the control group whose members did not use MP3 players while studying. Let’s assume that after we calculated the measures of central tendency (the mode, mean and median) we found that the MP3 player group did not perform quite as well as the non MP3 player group. The results showed a 4 point difference in the means of the grades between the two groups. The key question is whether or not the difference is statistically significant. In other words, does it represent a real difference, or it is due to chance.

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Three factors: 1. The difference between the two groups’ means. If the means are far apart, the result is more likely to be significant. 2. The number of participants. If each group has only a few people, the results are not as likely to be as significant as they would be if each group has a large number of randomly selected people in it. 3. The standard deviation of the two groups. If the scores of each group are mostly packed closely to each mean, then the results are significant.

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**Frequently Asked Questions about Psychology**

Why do psychologists study animals? Is it ethical to experiment on animals? Is it ethical to experiment on people?

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**Human Research Guidelines**

Informed consent – Participants must know that they are involved in research and give their consent. It is at this time that participants need to be told about any potential risks. Coercion - Participation must be voluntary. No one can be forced to be in a study. Participants have the right to refuse to participate or to withdraw at any time from the study. Anonymity/Confidentiality – Participants’ privacy must be protected. The researcher must never reveal their identities. Risk – Participants can’t be placed in any significant mental or physical risk. Debriefing – Participants must be told the purpose of the study and provided with ways to contact the researchers about the study results.

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**Animal Research Guidelines**

Clear scientific purpose – The research must answer a specific, important scientific question. Animals are chosen because they are best-suited. Humane treatment – The animals must be cared for and housed in a humane way. Legal possession of animals – The animals used in research must be purchased from legal companies. If wild animals are used they must be trapped in a humane manner. Minimum suffering - The experimental procedures must be designed to use the least amount of suffering possible.

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Why Use Animals? Psychologists use animals in research for several reasons. Some of these reasons are: Many psychologists are simply interested in animal behaviour. There are biological and behavioural similarities between animals and humans. By studying animals we can learn things that apply to humans. Because the life span of most animals is shorter than humans we can study genetic effects over generations faster than in humans. Researchers have more control over experiments with animals than with humans.

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Definition Slides Unit 1.2 Research Methods Terms.

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