Introduction to Psychology Psychologists do more than just wonder about human behavior: they conduct research to understand exactly why people think, feel, and behave the way they do. Like other scientist, psychologists use the scientific method, a standardized way to conduct research. A scientific approach is used in order to avoid bias or distortion of information. After collecting data, psychologists organize and analyze their observations , make inferences about the reliability and significance of their data and develop testable hypotheses and theories.
Psychological research has an enormous impact on all facets of our lives, from how parents choose to discipline their children to how companies package and advertise their products to how governments choose to punish or rehabilitate criminals. Understanding how psychologists do research is vital to understanding psychology itself. Psychological Research Scientist use the following terms to describe their research: – Variables: the events, characteristics, behaviors or conditions that researchers measure and study. – Subject or Participant: an individual person or animal a researcher studies. Sample: a collection of subjects researchers study. Researchers use samples because they can not study the entire population. – Population: the collection of people or animals from which researchers draw a sample. Researchers study the sample and generalize their results to the population. The Purpose of Research Psychologists have three main goals when doing research: – to find ways to measure and describe behavior. – to understand why, when, and how events occur. – to apply this knowledge to solving real-world problems. The Scientific Method Psychologists use the scientific method to conduct their research.
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The scientific method is a standardized way of making observation, gathering data, forming theories, testing predictions, and interpreting results. Researchers make observations in order to describe and measure behavior. After observing certain events repeatedly, researchers come up with a theory that explains these observations. A theory is an explanation that organizes separate pieces of information in a coherent way. Researchers generally develop a theory only after they have collected a lot of evidence and made sure their research results can be reproduced by others.
Example: A psychologist observes that some college sophomores date a lot, while others do not. He observes that some sophomores have blonde hair, while others have brown hair: he also observes that in most sophomore couples at least one person has brown hair. In addition, he notices that most of his brown-haired friends date regularly, but his blonde friends don’t date much at all. He explains these observations by theorizing that brown haired sophomores are more likely to date than those that have blonde hair.
Based on this theory he develops a hypothesis that more brow-haired sophomores than blonde-haired sophomores will make dates with people they meet at a party. He then conducts an experiment to test his hypothesis. In this experiment, he has twenty people go to a party, ten with blonde hair and ten with brown hair. He makes observations and gathers data by watching what happens at the party and counting how many people with each hair color actually make dates. If, contrary to his hypothesis, the blonde-haired people make more dates, he’ll have to think about why this occurred and revise his theory and hypothesis.
If the data he collects from further experiments still do not support the hypothesis, he’ll have to reject this theory. Making Research Scientific Psychological research , like research in other fields, must meet certain criteria in order to be considered scientific. Research must be: – replicable – falsifiable – precise – parsimonious Research Must be Replicable Research is replicable when researchers can repeat it and get the same results. When psychologists report what they have found through their research, they also describe in detail how they made their discoveries.
This way other psychologists can repeat the research to see if they can replicate the findings. After psychologists do their research and make sure it’s replicable, they develop a theory and translate the theory into a precise hypothesis. A hypothesis is a testable prediction of what will happen given a certain set of conditions. Psychologists test a hypothesis by using a specific research method, such as naturalistic observation, a case study, a survey, or an experiment. If the test does not confirm the hypothesis, the psychologist revises or rejects the original theory. How Psychologists Do Scientific Research . Form Hypothesis 2. Make Observations 3. Refine Theory 4. Develop Theory A Good Theory: A good theory must do two things: organize many observations in a logical way and allow researchers to come up with clear predictions to check the theory. Research Must Be Falsifiable A good theory or hypothesis also must be falsifiable, which means it must be stated in a way that makes it possible to reject it. In other words, we have to be able to prove a theory or hypothesis wrong. Theories or hypothesis need to be falsifiable because all researchers can succumb to the confirmation bias.
Researchers who display confirmation bias looks for and excepts evidence that supports what they want to believe and ignore or reject evidence that refutes their beliefs. Example: Some people theorize that the Loch Ness monster not only exists, but has become intelligent enough to elude detection by hiding in undiscovered, undetectable, underwater caves. This theory is not falsifiable. Researchers can never find these undiscovered caves or these monsters that supposedly hides in them, and they have no way to prove this theory wrong. Research Must Be Precise
By stating hypotheses precisely, psychologists ensure that they can replicate their own and others’ research. To make hypotheses more precise, psychologists use operational definitions to define the variables they study. Operational definitions state exactly how a variable will be measured. Example: A psychologist conducts an experiment to find out whether toddlers are happier in warm weather or cold weather. She needs to have an operational definition of happiness so that she can measure precisely “how happy the toddles are”. She might operationally define happiness as “the number of smiles per hour. “
Researchers Must Be Parsimonious The principle of parsimony, also called Occam’s razor, maintains that researchers should apply the simplest explanation possible to any set of observations. For instance, psychologists try to explain results by using well-accepted theories instead of elaborate new hypotheses. Parsimony prevents psychologists from inventing and pursuing outlandish theories. Parsimony- means “being thrifty or stingy”. A person who values parsimony will apply the thriftiest or most logically economical explanation for a set of phenomena. Example: Suppose a student consistently falls asleep in her statistics class.
She theorizes that before each class, her professor secretly sprays her seat with a nerve gas that makes her very drowsy. If she had applied the principle of parsimony, she would not have come up with this theory. She can account for her sleepiness with a much simpler and more likely explanation: she finds statistics boring. Research Methods Psychologists use many different methods for conducting research. Each method has advantages and disadvantages that make it suitable for certain situations and unsuitable for others Descriptive or Correlational Research Methods
Case studies, survey’s, naturalistic observation, and laboratory observation are examples of descriptive correlational methods. Using these methods, researchers can describe different events, experiences, or behaviors and look for links between them. However, these methods do not enable researchers to determine causes of behavior. Remember: correlation is NOT the same as causation. Two factors may be related without causing the other to occur, often a third factor explains the correlation. Example: A psychologist uses the survey method to study the relationship between balding and length of marriage.
He finds that length of marriage correlates with baldness. However, he can’t infer from this, that being bald causes peo0ple to stay married longer. Instead a third factor explains the correlation: both balding and long marriages are associated with old age. Measuring Correlation A correlation coefficient measures the strength of the relationship between two variables. A correlation coefficient is always a number between -1 and +1. The sign (+ or -) of a correlation coefficient indicates the nature of the relationship between variables. A positive correlation (+) means that as one variable increases, the other does too.
A negative correlation (-) means that when a variable increases, the other one decreases. Example: The more hours a high school student works through the week, the fewer A’s he or she gets in class. The higher the correlation coefficient, the stronger the correlation. A +0. 9 or 9 or a -0. 9 indicates a very strong correlation; a +0. 1 or a -0. 1 indicates a very weak correlation. A correlation of 0 means that no relationship exists between two variables. Common correlational research methods include case studies, surveys, naturalistic observation, and laboratory observation. Case Studies
In a case study, a researchers studies a subject in depth. The researcher collects data about the subject through interviews, direct observation, psychological testing, or examination of documents and records about the subject. Surveys A survey is a way of getting information about a specific type of behavior, experience, or event. When using this method, researchers give people questionnaires or interview them to obtain information. When subjects fill out surveys about themselves, the data is called self-report data. Self-report data can be misleading because subjects may do any of the following: lie intentionally – give answers based on wishful thinking rather than truth – fail to understand the questions the survey asks – forget parts of the experience they need to describe Naturalistic Observation When using naturalistic observation, researchers collect information about subjects by observing them unobtrusively, without interfering with them in any way. Researchers create a record of events and note relationships among those events with naturalistic observation, researchers face the challenge of getting a clear view of events without becoming noticeable to the subjects.
Laboratory Observation As the name implies, researchers perform laboratory observation in a laboratory rather than in a natural setting. In laboratory observation, researchers can use sophisticated equipment to measure and record subjects’ behavior. They can use one-way mirrors or hidden recording devices to observe subjects more freely while remaining hidden themselves. Unlike observation in a natural setting, laboratory observation offers researchers some degree of control over the environment. Psychological Testing
Researchers use psychological testing to collect information about personality traits, emotional states, aptitudes, interests, abilities, values, or behaviors. Researchers usually standardize these tests, which means they create uniform procedures for giving and scoring them. When scoring a test, researchers often compare subjects’ scores to norms, which are established standards of performance on a test. A well-constructed standardized test can evaluate subjects better than self-report data. Reliability A test has good reliability if it produces the same result when researchers administer it to the same group of people at different times.
Researches determine a tests’ test-retest reliability by giving the test to a group of people and then giving the test again to the same group of people at a later time. A reliable test will produce approximately the same results on both occasions. Psychologists also use alternate-forms reliability to determine a test’s reliability. They measure alternate-forms reliability by giving one version of a test to a group of people and then giving another version of the same test to the same group of people. A reliable test will give roughly the same results no matter which version of the test is used. Validity
A test is valid if it actually measures the quality it claims to measure. There are two types of validity: – Content validity is a test’s ability to measure all the important aspects of the characteristic being measured. An intelligence test wouldn’t have good content validity if it measured only verbal intelligence, since nonverbal intelligence is an important part of overall intelligence. – Criterion validity is fulfilled when a test not only measures a trait but also predicts another criterion of that trait. For example, one criterion of scholastic aptitude is academic performance in college.
A scholastic aptitude test would have good criterion validity if it could predict college grade point averages. Overview Of Research Methods. Research Method; Surveys Advantages: – yields a lot of information – provides a good way to generate hypotheses – can provide information about many people since its cheap and easy to do Disadvantages: – provides information about behavior that can’t be observed directly. – relies on self-report data which can be misleading – doesn’t allow conclusions about cause-and-effect relationships. Research Method: Case study Advantages: provides a good way to generalize hypotheses – yields data that other methods can’t provide Disadvantages: – sometimes gives incomplete information – sometimes relies on self-report data, which can be misleading. – can be subjective and thus may yields bias results. – doesn’t allow conclusions about cause-and-effect relationships. Research Method: Observation Advantages: – can be useful for generating hypotheses – provides information about behavior in the natural environment Disadvantages: – sometimes yields biased results – may be difficult to do unobtrusively doesn’t allow conclusions about cause-and-effect relationships. Research Method: Laboratory Observation Advantages: -enables use of sophisticated equipment fro measuring and recording behavior. – can be useful for generating hypotheses Disadvantages: – sometimes yields biased results – carries the risk that observed behavior is different from natural behavior – doesn’t allow conclusions about cause-and-effect relationships Research Method: Test Advantages: – gives information about characteristics such as personality traits, emotional states, aptitudes, interests, abilities, values, and behaviors
Disadvantages: – requires good reliability and validity before it can be used – doesn’t allow conclusions about cause-and-effect relationships Research Method: Experiment Advantages: – identifies cause-and-effect relationships – distinguishes between placebo effects and real effects of a treatment or drug Disadvantages: – can be artificial, so results may not generate to real world situations Experiments Unlike correlation research methods or psychological tests, experiments can provide information about cause-and-effect relationships between variables.
In an experiment, a researcher manipulates or changes a particular variable under controlled conditions while observing resulting changes in another variable or variables. The researcher manipulates the independent variable and observes the independent variable. The dependent variable may be affected by changes in the independent variable. In other words, the dependent variable depends (or is thought to depend) on the independent variable. Experimental and Control Groups Typically, a researcher conducting an experiment divides subjects into an experimental group and a control group.
The subjects in both groups receive the same treatment, with one important difference: the researcher manipulates one part of the treatment in the experimental group but does not manipulate it in the control group. The variable that is manipulated is the independent variable. The researcher can then compare the experimental group to the control group to find out whether the manipulation of the independent variable affected the dependent variable. Often, subjects in the control group receive a placebo drug or treatment, while subjects in the experimental group receive the real drug or treatment.
This helps researchers to figure out what causes the observed effect: the real drug or treatment, or the subjects’ expectation that they will be affected. Example: Suppose a researcher wants to study the effect of drug A on subjects’ alertness. He divides 100 subjects into two groups of 50, an experimental group and a control group. He dissolves drug A in a saline solution and injects into all the subjects in the experimental group. He then gives all the control group subjects an injection of only saline solution. The independent subject in this case is drug A, which he administers only to the experimental group.
The control group receives the placebo: the injection of saline solution. The dependent variable is alertness, as measured by performance on a timed test. Any effect on alertness that appears in both the experimental and control groups could be due to the subjects’ expectations or to extraneous variables, such as pain from the injection. Extraneous Variables Ideally, subjects in the experimental and control groups would be identical in every way except for the variables being studied. In practice, however, this would be possible only if researchers could clone people.
So researchers try to make groups with subjects that are similar in all respects that could potentially influence the dependent variable. Variables other than the independent variable that could affect the dependent variable are called extraneous variables. One way to control extraneous variables is to use random assignment. When researchers use random assignment, they create experimental and control groups in a way that gives subjects an equal chance of being placed in either group. This guarentees the two groups’ similarity. Disadvantages of Experiments
The main disadvantage of experiments is that they usually don’t fully reflect the real world. In an experiment, researchers try to control variables in order to show clear casual links. However, to exert control in this way, researchers must simplify an event or a situation, which often makes the situation artificial. Another disadvantage of experiments is that they can’t be used to study everything. Sometimes researchers can’t control variables enough to use an experiment, or they find that doing an experiment would be unethical – that is, it would be painful or harmful in some way to the subjects being studied.
Bias in Research Bias is the distortion of results by a variable. Common types of bias include sampling bias, subject bias, and experimenter bias. Sampling Bias Sampling bias occurs when the sample studied in an experiment does not correctly represent the population the researcher wants to draw conclusions about. Example: A psychologist wants to study the eating habits of a population of New Yorkers who have freckles and are between the ages of 18 and 45. She can’t possibly study all people with freckles in that age group, so she must study a sample of people with freckles.
However, she can generalize her results to the whole population of people with freckles only if her sample is representative of the population. If her sample includes only white, dark-haired males who are college juniors, her results won’t generalize well to the entire population she’s studying. Her sample will reflect sampling bias. Subject Bias Research subjects’ expectations can affect and change the subjects’ behavior, resulting in subject bias. Such a bias can manifest itself in two ways: – A placebo effect is the effect on a subject receiving a fake drug or treatment.
Placebo effects occur when subjects believe they are getting a real drug or treatment even though they are not. A single-blind experiment is an experiment in which the subjects’ don’t know whether they are receiving a real or fake drug treatment. Single-blind experiments help to reduce placebo effects. – The social desirability bias is the tendency of some research subjects to describe themselves in socially approved ways. It can affect self-report data or information people give about themselves in surveys. Experimenter Bias Experimenter bias occurs when researchers’ preferences or expectations influence the outcome of their research.
In these cases, researchers see what they want to see rather than what is actually there. A method called the double-blind procedure can help experimenters prevent this bias from occurring. In a double-blind procedure, neither the experimenter nor the subject knows which subjects come from the experimental group and which come from the control group. Ethical Considerations In the past, researchers performed all kinds of questionable experiments in the name of science. For example, in one famous experiment, psychologists Stanley Milgram led his subjects’ to believe that they were giving painful electric shocks to other people.
Many people consider this experiment unethical because it caused the subjects emotional discomfort. Today researchers must abide by basic ethical norms when conducting research. Most important, they must consider whether they might harm their human or animal subjects while doing research. Ethics – Ethics refers to a system of moral values or the way people distinguish right from wrong. The American Psychological Association (APA) requires all its members to adhere to its code of ethics, which applies to the treatment of both humans and animals. Research with Human Subjects
Researchers must get informed consent from their subjects before beginning research. Informed consent means that subjects must know enough about the research to decide whether to participate, and they must agree to participate voluntarily. Furthermore, researchers have an ethical obligation to prevent physical and mental harm to their subjects. If there is any risk of harm, they must warn subjects in advance. Researchers must also allow subjects to withdraw from a study at any time if they wish to stop participating. Finally, researchers have an obligation to protect the nonymity of their subjects. Some psychological research cannot be done when subjects are fully informed about the purpose of the research, because people sometimes behave differently when under observation. To study people’s normal behavior, researchers sometimes have to deceive subjects. Deception is considered ethical only if: – the study will give researchers some valuable insight. – it would be impossible to do the study without deception. – subjects can learn the truth about the study’s purpose and methods afterward. Research with Animal Subjects
Although most psychological research involves human subjects, some psychologists study animal subjects instead of or in addition to humans. Research with animal subjects has helped psychologists do the following: – learn facts about animal species. – find ways to solve human problems. – study issues that can’t be studied using human subjects for practical or ethical reasons. – refine theories about human behavior. – improve human welfare. Many people question the ethics of animal research because it can involve procedures such as deprivation, pain, surgery, and euthanasia.
Psychologists have ethical obligations to treat animal subjects humanly and to do research on animals only when the benefits of the research are clear. People who are against animal research maintain three arguments: – animals should have the same rights as humans – society should enact safeguards to protect the safety and welfare of animals – researchers should not put the well-being of humans above the well-being of animals Interpreting Data After psychologists develop a theory, form a hypothesis, make observations, and collect data, they end up with a lot of information, usually in the form of numerical data.
The term statistics refers to the analysis and interpretation of this numerical data. Psychologists use statistics to organize, summarize, and interpret the information they collect. Descriptive Statistics To organize and summarize their data, researchers need numbers to describe what happened. These numbers are called descriptive statistics. Researchers may use histograms or bar graphs to show the way data are distributed. Presenting data this way makes it easy to compare results, see trends in data, and evaluate results quickly. Example: Suppose a researcher want to find out how many hours students study for three different courses.
Each course has 100 students. The researcher does a study of 10 students in each of the courses. In the survey he asks the students to write down the number of hours per week they spend studying for that course. The data looks like this: Course A Course B Course C Student hrs/week Student hrs/week Students hrs/week Joe -9Hannah – 5 Meena – 6 Peter -7Ben – 6 Sonia – 6 Zoey – 8Iggy – 6 Kim – 7 Ana – 8 Louise – 6 Mike – 5 Jose – 7Keesha- 7Jamie – 6 Lee – 9Lisa – 6llana – 6 Joshua – 8Mark- 5Lars – 5
Ravi – 9Ahmed- 5Nick – 20 Kristen – 8Jenny- 6Liz – 5 Loren – 1Erin- 6Kevin – 6 To get a better sense of what these data mean, the researcher can plot them on a bar graph. Histograms or bar graphs for the three courses might look like this: Joe Peter Zoey Ana Jose Lee Joshua Ravi Kristen Loren ? Hannah Ben Iggy Louis Keesha Lisa Mark Ahmed Jenny Erin ? Meeana Sonia Kim Mike Jamie Llana Lars Nick Liz Kevin Measuring Central Tendency Researchers summarize their data by calculating measures of central tendency, such as the mean, the median, and the mode.
The most commonly used measure of central tendency is the mean, which is the arithmetic average of the scores. However, the mean is not a good summary method to use when the data include a few extremely high or a few extremely low scores. A distribution with a few very high scored is called a positively skewed distribution. The mean of a positively skewed distribution will be deceptively low. When working with a skewed distribution, the median is a better measure of central tendency. The median is the middle score when all the scores are arranged in order from lowest to highest. Another measure of central tendency is the mode.
The mode is the most frequently occurring score in a distribution. Measuring Variation Measures of variation tell researchers how much the scores in a distribution differ. Examples of measures of variation include the range and the standard deviation. The range is the difference between the highest and the lowest score from the highest score. The standard deviation provides more information about the amount of variable in scores. It tells a researcher the degree to which scores vary around the mean of the data. Inferential Statistics After analyzing statistics, researchers make inferences about how reliable and significant their data are.
Example: The researcher’s study of the students in three classes showed differences in how long the students studied for each course. The mean number of hours for students in course A was about 8 hours, and for students in courses B and C, the average was about 6 hours. Does this mean course A requires the most hours of study? Were the differences the researcher observed in study time real or just due to chance? In other words, can he generalize from the samples of students he surveyed to the whole population of students? He needs to determine the reliability and significance of his statistics.
If researchers want to generalize confidently from a sample, the sample must fulfill two criteria: – it must be large and varied enough to be representative. – it must not have much variation in scores. Researchers can use inferential statistics to figure out the likelihood that an observed difference was just due to chance. If it’s unlikely that the difference was due to chance, then the observed difference could be considered statistically significant at the p; . 05 level (p less than or equal to point oh-five) However, statistical significance alone does not make a finding important.
Statistical significance simply means that a result is probably not due to chance. Quick Review Psychological Research – Researchers use the terms variable, subject, sample, and population when describing their research. – Psychologists do research to measure and describe behavior; to understand when, why, and how events occur; and to apply knowledge to real- world problems. The Scientific Method – Psychologists use the scientific method, which is a standardized way of making observations, gathering data, forming theories, testing predictions, and interpreting results. Research must be replicable, falsifiable, precise, and parsimonious. Research Methods – Psychologists use descriptive or correlational methods such as case studies, surveys, naturalistic observation, and laboratory observation to describe events, experiences, or behaviors and to look for links between them. – Researchers use tests to collect information about personality traits, emotional states, aptitudes, interests, abilities, values, or behaviors. – Tests must be reliable and valid. – Researchers use experiments to collect information about casual relationships between variables. In experiments, researchers include experimental and control groups. – Bias is the distortion of results by a variable. – Types of bias include sampling bias, subject bias, and experimenter bias. Ethical Considerations – Psychologists must consider ethical norms when doing research involving humans or animals. Interpreting Data – Researchers analyze and interpret the data they’ve collected by using descriptive statistics and organizing their information in histograms and bar graphs. – Researchers use inferential statistics to determine the likelihood that a result is due simply to chance. Statistical significance means that a result is probably not due to chance. Review Questions: 1) What are some features of good scientific research? Good scientific research must have precise hypotheses, replicability, falsifiable theories and hypotheses, and parsimonious explanations. 2) What is sampling bias? Sampling bias is a type of error that occurs when a sample isn’t representative of the population from which it’s drawn. 3) Why might it be problematic to rely only on self-report data when during research? Self-report data can be misleading.
People sometimes intentionally lie, give answers based on wishful thinking, don’t understand the questions asked, or don’t remember information. 4) Why is it problematic to draw cause-and-effect conclusions based on correlative data? We can not draw cause-and-effect conclusions about correlative data because one factor can be related to another factor without causing it. 5) What does it mean if a researcher claims that a particular result is statistically significant? If a result is statistically significant, it is probably not due to chance.