Handout 1-8 What conclusion does the article imply?

Handout 1-8 What conclusion does the article imply?
Homosexuals and heterosexuals differ on a biological level and that homosexuality is caused by genetics. Point to the statements such as “suggests a biological phenomena” and “we’ve always believed that being gay or lesbian is not a matter of choice,” “it might explain why homosexuality is present in most human populations.” Is the conclusion warranted? No, it is a correlation. Alternative interpretations = 1) brain cell size  sexuality; 2) sexuality  brain cell size; 3) distressing event  sexuality and brain cell size. Do not confuse correlation with causation. Is the title an accurate summary of the study described? No because it implies all gay men (even though it only tested some). All suggests that all cells are different in gay men, but the study refers only to brain cell nuclei. The title also suggests that the gay men are the different ones, but the article reports gay men’s brain cell nuclei to be similar in size to those of women. Thus, the different ones are actually the heterosexual men. Can this study prove being gay or lesbian is not a matter of choice? The study cannot prove that it is not a matter of choice. Other variables may contribute. Biased sample. Discuss the nature of scientific experimentation and the inappropriateness of the term prove in science.

Steps in the Scientific Method
Scientific method - Set of rules and procedures on how to study, observe, or conduct experiments Formulate a research question How does self-esteem affect academic achievement? Develop Theory (set of tentative explanations of behavior and mental processes) Children with high self-esteem tend to have high academic achievement 3. Form Hypothesis (assertion or prediction for a behavior stated as a testable proposition, usually in the form of an if-then statement) If a child has high self-esteem, than he/she will be academically more gifted than a child with low self-esteem can be verified or falsified examine relationships between variables – specific factors that are manipulated and measured in research. operational definitions – a statement of specific procedures - - are used to define variables High self-esteem can be operationally defined as what a self esteem test measures. Academic achievement can be operationally defined as one’s GPA score

Population + Sample Population Sample Figure out population and sample
Population- Larger collection of people about which we want to generalize Sample - collection of subjects used in a study Random Sampling - every member of the population being studied should have an equal chance of being selected for the study Population – DHS psychology students Sample – 50 randomly sample students from the Psych classes

Samples Critical Thinking
At the end of the first two weeks of the baseball season, newspapers start publishing the top ten batting averages. The leader after the first two weeks normally has a batting average of .450 or higher. Yet no major league baseball player has ever finished the season with a better than .450 average. What do you think is the most likely explanation for the fact that batting averages are higher early in the season? One time at bat has a much greater effect on one’s average early in the season than at the end. For example, if someone bats twice after two weeks and gets one hit, his average is .500, but it may not be a true indication of how well he bats. The more frequently he bats, the clearer the true information as to how well a batter hits.  The answer represents an understanding that averages based on more cases are more reliable (that is, less variable) than averages based on but a few cases.

Samples Critical Thinking
David L., a senior in HS on the East Coast, was planning to go to college. He had compiled an excellent record in HS and had been admitted to his two top choices: a small liberal arts college and an Ivy League university. The two schools were about equal in prestige and were equally costly. Both were located in attractive cities, about equally distant from his hometown. David had several older friends who were attending both schools. They were all excellent students like himself and had interests similar to his. The friends at the liberal arts college all reported that they liked the place very much and that they found it very stimulating. The friends at the Ivy League university reported that they had many complaints on both personal and social grounds and on educational grounds. David initially thought he would go to the smaller college. However, he decided to visit both schools himself for a day. He did not like what he saw at the private liberal arts college. The people he met seemed cold and unpleasant; a professor seemed abrupt and uninterested in him. However, he did like what he saw at the Ivy League university. The people he met seemed vital, enthusiastic, and pleasant. The two professors he met took a personal interest in him and he came away with a very pleasant feeling about the campus. Please say which school you think David should go to and why. David just saw the Ivy League university for one day. His friends’ reports are based on an entire year. So he should take his friends’ word for it. Chances are that the liberal arts college is better.  The answer represents an understanding that averages based on more cases are more reliable (that is, less variable) than averages based on but a few cases.

Research Design Population Sample Sample Population Sampling Bias
Collection of subjects (Ss) used in a study, part of the population Random Sample – everyone in the population being studied has an equal chance of being included in the study Stratified Sample – identified subgroups in the population are represented proportionately in the sample. EX: 12% of the American population is African American. A stratified sample would thus be 12% African American. The larger the sample, the more likely it will represent a cross section of the entire population Population Larger collection of people about which we want to generalize Sample Population Sampling Bias When the sample is not representative of the larger population. EX: Study on voters – survey done over the phone. Biased sample b/c lower economic groups may not own telephones

Research Methods Carry out Observation
Descriptive Methods (naturalistic observations, case studies, surveys) – used it to collect and describe data Correlational Study – use it to reveal how closely two things vary together and thus how well the presence of one variable predicts the presence of another variable. Key Point: Correlational study cannot prove cause and effect!!! The relationships between the two variables can be a result of many factors If relationship is strong enough, than…. Experiment – manipulate independent and dependent variable to prove cause and effect

Analyze the Data + Report Findings
Analyze the data and draw conclusions. Based on results you might have to refine theory. Report findings precisely enough to permit replication and revision of theory Replication = the experiment can be repeated and would yield constant results even when done with a different group of people or by a different person Depending on results, start back at step #1

Types of Descriptive Studies
Type of Study Description Advantages Disadvantages Case Study An observation technique in which one person, group, or situation is studied in depth in the hope of revealing universal principles (often combines observations, interviews, tests, and analyses of written records) Useful in studying rare or complex phenomena Can mislead us - any given individual may be atypical and lead to false conclusions Survey Questionnaires or special interviews administered to a large, random group of people to ascertain their self-reported attitudes or behaviors that cannot be directly observed Enable researchers to describe the characteristics of a relatively small sample (a few hundred people) and then generalize that information to a larger population, quickly collect Easily biased (tend to hang around people like us) A small return rate means that the sample is not representative Wording of questions can have major effects on the opinions respondents express (framing – the way an issue is posed can significantly affect decisions and judgments) Not in-depth, not answered truthfully Naturalistic Observation Method of gathering descriptive information, involves watching behaviors of interest, without interfering, as they occur in their natural environments. Obtain data about a truly natural behavior rather than a behavior that is in reaction to contrived experimental situation If participants realize they are being observed, their behavior becomes unnatural Difficult and time-consuming Controls are lacking Difficult to generalize the results of the research Scientific objectivity is lost if experimenters interact with participants.

Correlation Coefficient = r
Correlational Study – use it to reveal how closely two things vary together and thus how well the presence of one variable predicts the presence of another variable. Key Point: Correlational study cannot prove cause and effect!!! The relationships between the two variables can be a result of many factors Positive correlation - Two variables change in the same direction, as x increases so does y. (max +1.00) Negative correlation - As one variable goes up, the other goes down and visa versa. Inverse relationship, as x increases y decreases. (min –1.00) Or not related! (~ 0.0) The higher the absolute value of r, the stronger the relationship Perfect correlation r = + or – 1.00 EX: r = +.37 “+” r “-” indicates direction of relationship .37 indicates strength of relationship (0.00 to 1.00) Perfect positive correlation (+1.00) No relationship (0.00) Perfect negative correlation (-1.00)

Correlation Coefficient
Indicates direction of relationship (+ or -) Correlation coefficient r = +0.65 Indicates strength of relationship (0.00 to 1.00)

Correlation CANNOT Prove Causation
Three Possible Cause-Effect Relationships could cause High achievement (1) High self-esteem or (2) High achievement could cause High self-esteem or High self-esteem (3) Supportive parents or biological predisposition could cause and High achievement

Experimental Variables
Independent Variable (IV) Condition or Event that the experimenter varies. Hypothesized to cause an effect on another variable. Given to experimental group Dependent Variable (DV) Variable thought to be affected by the IV. What you measure. Alcohol Level Performance

Experiments Random Assignment Control Condition Experimental IV
Everything the same as experimental group, except don’t get IV. Maybe get placebo Random Assignment Experimental Condition IV Random assignment - every subject in the study should have an equal chance of being placed in either the experimental or control group (even/odd; draw straws)  Minimizes pre-existing differences between those assigned to the different groups (age, attitudes, etc). Any later differences between people in the experimental or control conditions must be the result of the treatment.

Sources of Bias Observer-expectancy effect (Experimenter Bias)
researcher has expectations that influence measurements. EX: send subtle nonverbal signals, make mistakes in recording subjects’ responses. Subject-expectancy effect subject knows design and tries to produce expected result. demand characteristics – any cues in a study that suggest to subjects the purpose of the study or what the researcher hopes to find. Volunteer bias People who offer or volunteer to participate in research studies differ from people who do not (more interested in research than non-volunteers, have more spare time, more willing to disclose intimate information, etc) Placebo effects Placebo is a physical or psychological treatment that contains no active ingredient but produces an effect on the dependent variable because the person receiving it believes it will. Prevent bias by blinding!! minimize expectancy by removing knowledge about experimental conditions

Experimenter Flaws Extraneous Variable
Anything other than the IV that may influence the DV. Differences in subject variables (age, gender, race, ethnicity, cultural background, socioeconomic status, IQ, health, etc) and situation-relevant variables (test conditions, experimenter behavior, timing, etc) Confounding of Variables When two variables (an extraneous variable and IV) are linked such that it is difficult to sort out their specific effects on the DV Prevent it by Random Assignment!! Good experiment can be replicated – the experiment can be repeated with a different group of people and would yield constant results

Experimental Design: Placebo
Placebo Effects – placebo is a physical or psychological treatment that contains no active ingredient but produces an effect on the dependent variable because the person receiving it believes it will.

Review What is the purpose of correlational research?
The correlation between the physical weight and the reading ability of elementary school students is What does this mean? If those who watch a lot of TV violence are also particularly likely to behave aggressively, this would NOT necessarily indicate that watching TV violence influences aggressive behavior. Why? Which is a stronger correlational relationship, +.34 or -.85? Karen dreamed that a handsome young man she had met the previous day asked her for a date. When he actually did call for a date several days later, Karen concluded that dreams accurately predict future events. Her belief best illustrates what?

Ethical Guidelines in Psychological Research
Psych departments have review panels (Institutional Review Board) to screen all proposals for research. Proposals have to conform to APA Ethics Code Accurately report results Right to privacy - studies are conducted to ensure confidentiality information will not be made available to anyone who is not directly involved in the study data is coded and reported in group form rather than individual responses. Use code #s instead of individual names whenever possible. Informed consent use of deception – not possible or desirable to always tell the truth about purpose of experiment up front (want to eliminate subject expectancy effect) always have to debrief subjects after study – subjects should be told about the purpose of the research, the hypotheses being tested, the nature of the results or anticipated results, and the implications of those results for the science of psychology immediately or soon after participation.

Ethical Guidelines in Psychological Research
Minimize subject discomfort subjects can withdraw any time and have to sign consent Prevent any long-term negative effects Subjects should not be put at risk, except in cases where there is no other way to conduct research and research results offer promise to advance knowledge Voluntary Participation - people cannot be coerced into participating in research. Right to Service - treatment might have beneficial effects, so persons in no-treatment control group may be upset

Animal Experimentation
Review boards (Animal Care and Use Committee) establish Animal Care Guidelines: Specify the proper care and maintenance of animals, including the adequacy of space requirements, maintenance of good health, and supervision by qualified personnel. Researchers are required to make every effort to minimize the pain and discomfort of animal subjects and to seek alternative methods for their research if possible. Similar processes often underlie animal and human behavior (how humans see, exhibit emotion, become obese, etc), so the justification for discomfort or harm a research procedure may produce is that the results will be applicable to humans

Tom the Dancing Bug Cartoon reinforces the point that we value animals according to their perceived similarity to us. Speciesism – prejudice toward the interests of one’s own species and against the interests of another species. Arguments against research using animals: Just as differences in intelligence, race, and gender are not valid criteria to exploit other humans, a creature’s species is equally irrelevant All sentient animals have the capacity to suffer, and thus are the subject of equal moral consideration. Research with animals is permissible only if we would also consider using human subjects for the same experiments Like humans, animals have the right to be treated with respect and the right not to be harmed.

Animal Research Proposals: Case 1
Approve or Reject? Why? Forces consideration of whether injury to another species closely related to human is justified if the results will be applicable to human beings. Review Board would most likely say YES  similar processes often underlie animal and human behavior, so the justification for discomfort or harm a research procedure may produce is considered acceptable if the results will be applicable to humans

Approve or Reject? Why? Prompts consideration about the use of animals when there is no direct human application Review Board would most likely say YES  pure research in scientific progress is important. Need to make sure animal discomfort is minimized and no other method of research is available

Approve or Reject? Why? Involves the question of whether pound animals should be used in research Review Board would most likely say NO many states have banned the use of such animals for biomedical research of for student surgeries in veterinary schools

Approve or Reject? Why? Prompts consideration about using animals in student laboratories. Review Board would most likely say NO animal welfare groups argue that this is particularly unnecessary when videotapes and computer simulations are adequate substitutes

Statistics Descriptive Statistics Inferential Statistics
Use of mathematics to organize, summarize and interpret numerical data. Statistical analysis is used to determine whether any relationships or differences among the variables are significant, quantifies the exact strength of the association. Descriptive Statistics Statistical Significance Used to describe, organize & summarize data to make it more understandable Used to interpret data & draw conclusions. “What can we infer about the pop from data gathered from the sample?” Central Tendency Variability Correlation Inferential Statistics

Median Mean ∑ X/N = X Mode
Descriptive Statistics: Measures of Central Tendency (summarizes data set by providing a representative number) Median Score that falls in the center of a distribution of scores. When there is an even number of scores in a data set, the median is halfway between the two middle numbers. Best indicator of central tendency when there is a skew. The median is unaffected by extreme scores. Mean ∑ X/N = X Average of scores in a distribution. Even one extreme score can change the mean radically, possibly making it less representative of the data. Most significant because additional statistical manipulations can be performed on it. Mode Most frequently occurring score in a distribution.

Skewed Distribution An asymmetrical distribution of scores, such as a curve with a bump on the left and tail to the right or most scores are bunched to the left or right of the mean The mean is the largest The mode or median are smaller than the mean The mean is a less useful measure; while the median is more useful 90 475 710 70 Mode Median Mean One Family Income per family in thousands of dollars

Descriptive Statistics: Measures of Variability
Indicate the dispersion or spread in a data set. How much the scores in a set of data vary from: a. Each Other b. the Mean Tell you if the scores are very different from one another or if they cluster around the mean. Range The difference between the highest and lowest score in a set of data. Extreme scores can radically affect the range of a data set. Standard Deviation Reflects the average distance between every score and the mean. Tell You how different the scores are from the mean. Tells you whether scores are packed together or dispersed. Standard Deviation Variability

Easy Example of Standard Deviation
Memorize formula X = mean X = individual score in data set ∑ = sum/add N = number of scores in data set Sample Problem Find the standard deviation of the following data set (2, 4, 4, 6) Find the mean of data set: ( )/4 = 4 = X Subtract each individual score in data set from mean (X – X) and square it (2 – 4) = (-2) = 4 (4 – 4) = (0) = 0 (6 – 4) = (2) = 4 Add each squared score: ( ) = 8 Divide summed scores by N (which is 3 in this example, since there are 4 scores in the data set): 8/2 SD = 2

Inferential Statistics
While descriptive statistics summarize a data set, we often want to go beyond the data: Is the world at large like my sample? Are my descriptive statistics misleading? Inferential statistics give probability that the sample is like the world at large. Allow psychologists to infer what the data mean. Assess how likely it is that group differences or correlations would exist in the population rather than occurring only due to variables associated with the chosen sample.

Statistical Significance
Results are “statistically significant” when the probability that the findings are due to chance is very low. If the difference between two group means is statistically significant, a researcher would conclude that the difference most likely exists in the population of interest. If the difference is not statistically significant, a researcher would conclude that the difference occurred by chance – possibly because of an unrepresentative sample or the presence of confounding variables. “Very Low” means less than 5 chances in 100 or P < 0.05 level of significance

68.2 % 95.4 % 99.7 %

Sample Test Question For a language test with normally distributed scores, the mean was 70 and the standard deviation was 10. How are the scores distributed? Approximately what percentage of test takers scored 60 and above?

Answer to Sample Question
68% of students scored between 60 and 80. 84% of students scored 60 and above

Educational Cartoons + Intelligence
Correlational Study Population and sample? How collected? All preschoolers enrolled in preschools in Deerfield. Randomly sample 100 preschoolers from the population (enter names in computer, and computer randomly generates 100 names). How will you collect the data? Send a survey home to the parents of the 100 preschoolers asking them to report on how many hours of educational cartoons their child watches. Review the preschooler’s scores on their entrance exam to the preschool Compare the data from the parents’ surveys and the scores from the entrance exam by creating a scatterplot or determining the correlation coefficient. Variables? Operational Definitions? Hours of educational cartoons – Baby Einstein videos Scores from the entrance exam – a rating of above average or exemplary would indicate a high degree of intelligence Ethical Guidelines? Informed consent from parents, confidentiality, debriefing

Increase in IQ or Watching educational cartoons or Buy educational
Correlational Study Meaning of Results: The correlation coefficient “r” = Should Philip continue his research and design an experiment? Why or why not? Yes! There is a strong, positive relationship between educational cartoons and intelligence. However, we do not know which variable influences the other variable. It could be… could cause Increase in IQ (1) Educational cartoons or Watching educational cartoons (2) Smart children prefer or Buy educational cartoons (3) Socioeconomic background of parents have enough $ and Hire tutors to tutor their children

Experiment Population and sample? How collected? All preschoolers enrolled in preschools in Deerfield. Randomly sample 100 preschoolers from the population (enter names in computer, and computer randomly generates 100 names). Variables? IV/DV? Operational Definitions? IV = educational vs non-educational cartoons Educational cartoons = 1 hour of Baby Einstein’s every day for a month Non-educational cartoons = 1 hour of Sponge Bob every day for a month DV = intelligence scores on an IQ test Experimental and Control Group? How are subjects assigned? Experimental group = Group 1 of preschoolers that watch 1 hour of BE every day for a month Group 2 of preschoolers that watch 1 hour of Sponge Bob every day for a month Control group = Normal average daily T.V. Watching. Randomly assign 50 preschoolers to experimental group (2 Variables being given) and 50 to control group. Confounding Variables or Bias? Ways to Control? Double Blind to prevent bias and subject-expectancy effect Differences in intelligence to start with – prevented by random assignment. Differences in family involvement – prevented by random assignment

Ethical Guidelines? Protect confidentiality – data is coded Parents need to give consent Parents need to be debriefed after study is over Minimize subject discomfort and prevent negative long-term effects Meaning of Results: The mean of the experimental group was 83 and the mean of the control group was 79. If a statistical test finds that the statistical significance “p” < .05 for the difference between the means, what should Philip conclude? Why? Philip can conclude that there is less than 5 in 100 chances that the results were due to chance. Most likely the treatment (IV – educational cartoon) created the difference between the two groups.

Statistical Breakdown of Intelligence
After researching about the intelligence of preschoolers, Philip was curious to find out how intelligent he and his friends were. He and his friends took an IQ test. The scores for the IQ test were normally distributed – the mean was 100 and the standard deviation was 15. Using this information, describe how the scores are distributed. Most scores (68%) are within 15 points of the mean (of 100). The typical (average, normal) IQ score falls between 85 and 115 Mean, median, and mode are the same or very close

The following are a list of four scores from the IQ test Philip’s friends took: 136, 95, 91, 90. If we wanted to know what the IQ of Philip’s friends is MOST like, which would be the best indicator? Mean or Median? Why? X = 103 Median = 93 Answer = Median. The mean is affected by extreme scores.

Philip then wanted to find out if he and his friends were smarter than his dad and his dad’s friends, so he gave the IQ test to his dad and his friends. Compare the two groups of scores: Philip’s group: 104, 102, 95, 91, 90, 83, 72 Philip’s dad’s group: 95, 93, 92, 91, 90, 89, 87 What can we determine about the two groups? How are they different? Similar? For each of the groups, the mean = 91 However, the range for Philip’s group = 32; while the range for dad’s group = 8. The standard deviation for Philip’s group = 10.23; while the standard deviation for Dad’s group = 2.45 The groups did not perform the same. The scores in Philip’s group are much more spread out than in the dad’s group. The scores for the dad’s group tend to cluster closer to the mean

The IQ test Philip used was recently re-normed. Why are IQ tests periodically updated? Changes in knowledge require tests to be re-normed People have gotten smarter (Flynn Effect) The numbers of questions answered accurately has increased over the years Changes that affect IQ test scores of groups (e.g. sociocultural or technological) Changes in educational practices or techniques (that affect knowledge) Keep material culturally relevant Re-norm to maintain validity or reliability

Flynn Effect In the past 60 years, intelligence scores have risen steadily by an average of 27 points. The following environmental changes have contributed to the change: Rise of science: Taught us that classifying the world using the categories of science is just as important as manipulating the world Freed logic from the concrete, allowing us to work on abstractions with no concrete referents. Increasing educational opportunities Reduction in family size Improvements in infant nutrition Changing communication technologies

Principles of Test Construction
For a psychological test to be acceptable it must fulfill the following three criteria: Standardization Standardizing a test involves pre-testing a representative sample of people and forming a normal distribution or bell curve (most scores fall near the average, and fewer and fewer scores lie near the extremes) to establish a basis for meaningful comparison. Reliability = a test is reliable when it yields consistent results Validity = a test is valid when it measures what it is designed to measure.

To establish reliability researchers establish different procedures:
Split-half Reliability: Dividing the test into two equal halves (odds and evens) and assessing how consistent the scores are. Alternate Forms Reliability: Using different forms of the test to measure consistency between them. Test-Retest Reliability: Using the same test on two occasions to measure consistency. A person’s score on a test at one point in time should be similar to the score obtained by same person on a similar test at a later point in time. Inter-Scoring Reliability: One scorer’s rating should be similar to another scorer’s rating OBJECTIVE 11| Explain what it means to say that a test is reliable.

Validity Reliability of a test does not ensure validity. Validity of a test refers to what the test is supposed to measure or predict. Content Validity: Refers to the extent a test measures a particular behavior or trait of interest. driving test that samples driving tasks Predictive (Criterion-Related) Validity: Refers to the success of a test in predicting a particular behavior or trait it is designed to predict. Assessed by computing the correlation between test scores and the criterion behavior. behavior (such as college grades) that a test (such as the SAT) is designed to predict OBJECTIVE 12| Explain what it means to say that a test is valid, and describe two types of validity.

Types of Tests: Aptitude vs. Achievement
Aptitude = A test designed to predict a person’s ability to learn a new skill (future performance.) College entrance exams like ACT and SAT Achievement = A test designed to reflect what you have already learned. Unit exams AP exam

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