Experimental, correlational, and clinical are three major types of psychology research.
An experiment seeks to understand relations of cause and effect.
The experimenter changes a variable and measures how it changes another.
The investigator tries to keep all other variables constant so she can attribute any changes to the manipulation.
The independent variable is a manipulated variable.
What is measured is the dependent variable.
An experiment is designed to determine if violence on television causes aggression in viewers.
Two groups of children are placed in front of violent or non-violent television programs for an hour.
The program type can be manipulated by the experimenter.
The experimenter will record the number of times a child hits, kicks, or punches the doll after placing a large doll in front of each child.
The variable that is measured is the dependent variable.
The control variable is the doll's presence in both groups.
It is important that certain conditions are met in order to draw conclusions about the experiment.
A group of interest is identified by the researcher.
A representative sample of the population may be drawn because the population may be too large to study effectively.
The degree to which a sample reflects the diverse characteristics of the population is called representativeness.
Random sampling is used to ensure representativeness.
When sampling is addressed, subjects are assigned to either the experimental or control groups.
Random assignment is done to make sure that each group is the same.
The control group does not receive the independent variable but should be kept the same in all other respects as the experimental group.
Two groups allow for a comparison to be made.
During the 1948 U.S. Presidential Election, a survey was conducted by randomly calling households and asking them who they intended to vote for, Harry Truman or Thomas Dewey.
Dewey was projected to win.
Truman was re-elected as the results proved otherwise.
In 1948, households that had a telephone were generally wealthier.
Many people who voted for Truman did not have telephone numbers, so the random selection of telephone numbers was not a representative sample.
When people are selected in a physical space, the bias of selection occurs.
If you wanted to survey college students about their football team, you could stand on the quad and survey the first 100 people that walk by.
People who don't have class at that time are unlikely to be represented.
The people being studied have control over whether or not to participate in the study.
The results may be affected by a participant's decision to participate.
A survey on the internet might only ask responses from people who are highly motivated to complete the survey.
Pre-screening or advertising bias can occur in medical research if volunteers are screened or where advertising is placed.
For example, if a researcher wanted to prove that a certain treatment helps people to stop smoking, the act of advertising for people who want to quit might only provide a sample of people who are already highly motivated to quit.
The study population tends to be in better shape than the general population.
Even though the gym might have a diverse population, this is an instance in which those subjects might not accurately represent their neighborhoods.
Researchers use a single- or double-blind design to avoid inadvertently influencing the results.
The subjects don't know if they are in the control or experimental group.
The subjects and the researcher don't know who is in the two groups.
Double-blind studies are designed so that the experimenter doesn't accidentally change the responses of the subject, such as using a different tone of voice with members of the control group than with the experimental group.
The data can be analyzed later if a third party has the appropriate records.
In some double-blind experiments, the control group is given a placebo, a seemingly therapeutic object or procedure, which causes them to believe they are in the experimental group, but actually contain none of the tested material.
Longitudinal studies and cross-sectional studies are two types of research that can be set up as correlational or experimental designs.
Cross-sectional studies are designed to test a wide array of subjects from different background to increase generalizability, and longitudinal studies are designed to study the long-term effects of diet and exercise on heart disease.
Correlational research involves assessing the degree of association between two or more variables.
In this type of design, researchers do not directly manipulate variables but rather observe naturally occurring differences.
The characteristics under consideration are related.
It is important to note that correlation doesn't prove causality, it just shows the strength of the relationship among variables.
Poor school performance may be related to lack of sleep.
We don't know if the lack of sleep caused the poor performance or if the poor school performance caused the lack of sleep.
If an unknown factor is playing a role, it is known as a confounder, a third variable, or an extraneous variable.
One way to gather information is through surveys.
One can accumulate a lot of data using either questionnaires or interviews.
Such techniques can be used to assess voter characteristics, teen alcohol and drug use, and criminal behavior.
Survey studies can look at the relationship between educational levels and socio-economic status.
Correlational studies are easier to conduct and are less expensive than experiments.
Some relationships can't be studied ethically in experiments.
No one will allow you to randomly assign half of your baby participants to the child abuse condition, even if you want to study how child abuse affects self-efficacy in adulthood.
Case studies are often used in clinical research.
A case study is a psychological study of a single person.
The assumption is that an in-depth understanding of single cases will allow for general conclusions about other similar cases.
Case studies have been used to investigate the lives of notable figures.
Multiple case studies on similar cases are combined to draw conclusions.
Case studies can't lead to conclusions regarding causality.
Carl Rogers and Sigmund Freud used case studies to draw conclusions about psychology.
There is a danger of generalizing from the outcomes of case studies.
Because of the predictable outcomes of repeated tests, researchers try to ensure that their studies are generalizable.
The conceptual definition and operational definition are important features of studies.
The operational definition refers to the way in which the theory or issue will be observed or measured in the study.
In a study on the effects of adolescent substance abuse, the way in which taking drugs affects adolescent behavior is the conceptual definition, while the number of recorded days the student is absent from school due to excessive use of substances is the operational definition.
External and internal operational definitions have to be valid.
The results of an experiment can be attributed to the manipulation of the independent variable, rather than to some other variable.
If the experiment is repeated under similar conditions, it is important that the study have the same results.
Inter-rater reliability is the degree to which different raters agree on their observations of the same data.
naturalistic observation has enriched our knowledge of psychology by allowing researchers to observe behavior outside of a lab.
Scientists collect data.
This data is analyzed.
There are two types of statistics: descriptive and inferential.
Inferential statistics allow researchers to test hypotheses about data and determine how confident they can be in their conclusions about the data.
Descriptive statistics describe data.
They don't allow conclusions to be made about anything other than the numbers they describe.
The mean, mode, and median are commonly used descriptive statistics.
The typical value in a set of data is characterized by the descriptive statistics.
The mean is the average of the numbers.
The mode is the most common value in the data set.
The median is the number in the middle of the distribution.
A normal curve can be used to represent these statistics.
The mean, median, and mode are the same in a perfectly normal distribution.
The range is the largest number minus the smallest number.
The mean and standard deviation are two factors that affect the normal distribution graph.
The location of the center of the graph is determined by the mean of the distribution and the standard deviation.
The curve is short and wide when the standard deviation is large, and tall and narrow when the standard deviation is small.
The normal distributions look like a bell-shaped curve.
Almost all of the scores are within one standard deviation above or below the mean, and almost all of the scores are within two standard deviations above or below the mean.
A person with a score of 115 is one standard deviation above the mean if they have an IQ of 100.
Questions about normal distributions can appear on the test.
Questions about percentages and skewed distributions are often trick questions because they don't all share the same mathematical properties.
The curve on the left has a bigger standard deviation than the curve on the right.
The median is a better indicator of central tendency than the mean.
A positive skew means that most values are on the lower end.
A "tail" or skew is created by this.
Most values are on the higher end, but there are some very small values.
A "tail" or skew is created by this.
The mean, mode, and median give approximations of the central tendency of a group of numbers, but they don't tell us much about the variability in that set of numbers.
The standard deviation is a commonly used measure of variability.
Say you have a set of numbers that have a mean of 100.
The standard deviation will be small if most of those numbers are close to 100.
The standard deviation will be large if the mean of 100 comes from 50 to 150 numbers.
It's not likely that there will be any questions that will help you with your math skills, but you should be able to read a graph and understand what the standard deviation is in a study.
The mean and standard deviation of the reaction times of 1,000 subjects in a study are 1.3 and 0.2 seconds, respectively.
The normal distribution and one standard deviation above and below would be represented by participants with a reaction time between 1.1 and 1.5 seconds.
Approximately 700 of 1,000 people would have this reaction time.
More than three standard deviations above the mean is what a reaction time of over 1.9 seconds would be like.
The data is likely to fall into a category of three standard deviations above or below the mean.
About 1.5 of the 1,000 subjects would be 0.15 percent above the mean.
The percentile is a descriptive stat.
When reporting scores on standardized tests, this stat is used a lot.
If your SAT score is in the 85th percentile, you are more likely to score higher than the other test-takers.
Standard deviation is the average distribution of numbers.
Statistical techniques are needed to describe how attributes relate to one another when looking at correlational data.
The correlation coefficients will give us information.
The correlation coefficients show the degree and direction of the relationship between two variables.
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The linear relationship between two attributes is described by the Pearson correlation coefficients.
Pearson correlations are measured on a scale ranging from 1 to 0 and can be positive, negative or both.
A perfect positive correlation is shown by a correlation of 1 As attribute X increases, attribute Y increases proportionally.
As the value of attribute X increases, the value of attribute Y always decreases.
The attributes are not related.
The study assessed 200 male children from ages 1 to 12.
A standardized questionnaire was given to the parents of the children and used to check their "agreeableness" on a scale from 0 to 5.
Standard measures of the behavioral problems exhibited by the children were taken by psychologists.
The correlation between child agreeableness and later behavioral problems was found after the incidents were totaled.
An example of the tricky relationship between correlation and causation can be found in New York City, where the murder rate is directly correlated to the sale of ice cream.
When two variables are correlated, there are always other factors that could influence either of them.
As the temperature rises, more crimes are committed, but people also tend to eat more cold foods, like ice cream.
As the child's agreeableness increases, behavioral problems decrease, so does the correlation between the scores.
Inferential statistics are used to determine our level of confidence in the results if they were only chance.
Experiments are usually conducted with a small group of people.
psychologists want to be able to generalize the results of the experiment to a larger group of people The sample is the small group of people in the experiment, and the population is the large group that the psychologist is trying to generalize from.
The sample should reflect the characteristics of the population as a whole.
The sample is referred to as being representative if it does.
The number of observations is referred to as the sample size.
The total number of subjects in a subgroup of the sample being studied is called the total number of subjects in a subgroup.
The sample size used in a study is usually determined by convenience, expense, and the need to have enough statistical power to conclude that the hypothesis is true within an acceptable margin of error.
The larger the sample size, the more likely it is that the broader population is correct.
Inferential statistics are used for hypothesis testing.
The null hypothesis states that there was no effect on the experiment.
The treatment may have had an effect.
It is possible to reject the null hypothesis with a known level of confidence if the data is not true.
The significance of these tests is that they allow us to examine whether the effects are likely to be a result of treatment or simply the normal variations that occur among samples from the same population.
If a result is found to be statistically significant, that result may be generalized with some level of confidence to the population.
Alpha is the accepted probability that the result of an experiment can be attributed to chance.
If the probability of the results happening by chance is less than 5 percent, the experiment's results will be considered statistically significant.
There are two types of errors when testing a hypothesis.
When the difference does not exist, there is a type I error.
There is no difference when there is a difference.
Because they don't want to conclude that a difference exists if it isn't, psychologists pay close attention to Type I errors.
The p - value is the probability of making a type I error.
The results are statistically significant, not due to chance.
We only have a 5 percent chance of making a type I error if p is 0.05.
If the null hypothesis were correct, a difference as extreme as what was obtained would be found only 5 percent of the time.
Sometimes psychological experiments involve deception, which may be used if the participants are not told the nature of the experiment.
In rare instances, this deception can be extreme.
In the 1970s, Stanley Milgram conducted experiments in which he convinced participants that they were administering painful electric shocks to other participants, when in fact, no shocks were given.
The confederates were aware of the true nature of the experiment but pretended to be participants.
The real participants were those who gave the shocks.
Many people felt that this study was unethical because the participants were not aware of the nature of the study and could have believed that they had done serious harm to other people.
The American Psychological Association has set ethical standards for the treatment of animals and humans.
Before the research is approved, the IRBs assess the research plans to make sure they meet ethical standards.
In order to participate in the study, participants must be told what they are participating in.
If participants become uncomfortable about their participation, they can leave the experiment.
After the experiment is over, participants must receive a debriefing in which they are told the exact purpose of their participation in the research and of any deception that may have been used in the process of experimentation.
Confidentiality is a concern for psychology.
The participants might not want to be revealed in an experiment.
Most psychological data is collected without the participants' names being attached to it.
It is the researcher's ethical obligation to ensure anonymity if it is not possible.
Pain is an issue in experiments.
In the past, shock was used with humans.
Physical pain is rarely used in experiments today.
There is less psychological stress.
The use of animals in psychological experiments is controversial.
Animals are often subjected to stress in experiments.
The animals are euthanized at the end of the research.
Many drugs could not be tested with animals, according to psychologists.
There is a level of experimental control that is not available with human participants.
No ethical researcher wants to cause unnecessary pain to any subject.
Chapter 19 has answers and explanations.
There is a correlation between two variables.
A study is looking at the effects of video games on violent behavior.
A researcher creates an experiment in which 100 random people play violent video games and 100 other people play non-violent video games for an hour.
The researcher observes the behavior of the subjects.
A researcher wants to study the effects of a weight-loss supplement and decides to place an advertisement on buses and subways in New York City to attract subjects.
The researcher noticed that a disproportionate amount of subjects scored low on their test and shifted the peak of the bell curve she was expecting.