Encyclopedia of Counseling Research & Program Evaluation

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  1. ACA stands for
    American Counseling Association
  2. Basic Reserach
    Basic Research contributes knowledge to a theory.
  3. Applied Reserach
    Applied Research helps answer the question, if a theory helps solve real world problems.
  4. What does Reliable mean? what is meant by a reliable experiment?
    Reliable means the extent to which an experiment, test, or measuring procedure yields the same results on repeated trials. A reliable experiment means that the experiement can be replicate
  5. What is Parsimony? and the principle of parsimony?
    Parsimonious means “being thrifty or stingy.” A person who values parsimony will apply the thriftiest or most logically economical explanation for a set of phenomena.

    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.

    Example: Suppose a student consistently falls asleep in her statistics class. She theorizes that before each class, her statistics 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.
  6. What is a true experience?
    control of all relevant variables, high control settings

    • negatives not real world
    • positive control of varibles
  7. confunding varibiles
    keeping out unwanted variables so experiment is not confounded (not accurate)
  8. exterminating varibiles
    ex participents taking natural remedies in the outside lab, in a study of depression
  9. IV
    Independent varible
  10. IV independent variable is
    variable manipulated by researcher

    like a medical IV, is the treatment provided to participant.
  11. DV
    are the date, the scores, human response

    ex how much wieght
  12. Dependent variable is
  13. the effect of __________  on ___________
    IV, DV
  14. REBT
    • rational emotive behavioral therapy
    • or RET rational emotive therapy
  15. using REBT, for alcoholic treatment, 16 sessions of REBT, data of how many drinks each participant has, with control group
    • level 1 control group- no treatment
    • level 2 16 sessions of IV (rebt)
    • level 3 8 sessions of IV

    all experiments have have at least 2 levels
  16. the control group never gets the
    IV or experimental varibile
  17. random sampling get rid of what
    a technique of assigning participants to the control group (variable) and experimental group (variable), keeping groups equal and researcher honest, and avoiding sample bias
  18. sampling bais
  19. Variables
    Variables: the events, characteristics, behaviors, or conditions that researchers measure and study.
  20. Subject or participant
    Subject or participant: an individual person or animal a researcher studies.
  21. Sample
    Sample: a collection of subjects researchers study. Researchers use samples because they cannot study the entire population.
  22. 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
  23. What are the 3 main goals of Psychologists research?
    • 3 main goals of Psychologists research
    • 1. To find ways to measure and describe behavior
    • 2. To understand why, when, and how events occur
    • 3. To apply this knowledge to solving real-world problems
  24. What is a theory?
    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.
  25. What are the 4 Qualities of Research?
    Research must be 

    • 1. Replicable
    • 2. Falsifiable
    • 3. Precise
    • 4. Parsimonious
  26. What is Falsifiable?
    falsifiable means that a theory or hypothesis 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 and hypotheses need to be falsifiable because all researchers can succumb to the confirmation bias.
  27. What is the Confirmation Bias?
    Confirmation Bias is when researchers look for and accept 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 the monster that supposedly hides in them, and they have no way to prove this theory wrong.
  28. Operational definitions
    By stating hypotheses precisely it is ensure that they can be replicate using 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 cool weather. She needs to have an operational definition of happiness so that she can measure precisely how happy the toddlers are. She might operationally define happiness as “the number of smiles per hour.”
  29. What are examples of descriptive or correlational research methods. 
    Examples of descriptive or correlational research methods are Case studies, surveys, naturalistic observation, and laboratory observation. 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.
  30. True or false a correlation mean causation.
    False: a correlation is not the same as causation. In a correlation 2 factors may be related without one 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 people to stay married longer. Instead, a third factor explains the correlation: both balding and long marriages are associated with old age.
  31. A correlation coefficient measures what and how? 
    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 the variables.The higher the correlation coefficient, the stronger the correlation. A +0.9 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.
  32. A positive correlation (+) means that
    as one variable increases, the other does too.

    Example: The more years of education a person receives, the higher his or her yearly income is.A negative correlation (–) means that when one variable increases, the other one decreases.Example: The more hours a high school student works during the week, the fewer A’s he or she gets in class.
  33. Image Upload 1
    No correlation
  34. Image Upload 2
    Perfect positive correlation
  35. Image Upload 3
    Perfect negative correlation
  36. 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 intentionallyGive answers based on wishful thinking rather than the truthFail to understand the questions the survey asksForget parts of the experience they need to describe
  37. psychological tests to collect information about personality traits, emotional states, aptitudes, interests, abilities, values, or behaviors. Researchers usually standardizethese 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.
  38. 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.
  39. Researchers determine a test’s 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.
  40. 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 produce roughly the same results no matter which version of the test is used.
  41. ValidityA test is valid if it actually measures the quality it claims to measure. There are two types of validity:
  42. 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.
  43. 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.
  44. 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.
  45. researcher manipulates theindependent variable and observes the dependent 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.
  46. Image Upload 4
  47. 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.
  48. variable that is manipulated is the independent variable.
  49. Extraneous VariablesIdeally, 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.
  50. 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 guarantees the two groups’ similarity.
  51. Disadvantages of ExperimentsThe 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 causal 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.
  52. Bias in ResearchBias is the distortion of results by a variable. Common types of bias include sampling bias, subject bias, and experimenter bias.
  53. 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 eighteen and forty-five. 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.
  54. Subject BiasResearch 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 or 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.
  55. Experimenter BiasExperimenter 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.
  56. EthicsEthics 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.
  57. statistics refers to the analysis and interpretation of this numerical data. Psychologists use statistics to organize, summarize, and interpret the information they collect.
  58. 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 wants to find out how many hours students study for three different courses. Each course has 100 students. The researcher does a survey of ten students in each of the courses. On the survey, he asks the students to write down the number of hours per week they spend studying for that course. The data look like this:
  59. Researchers summarize their data by calculating measures of central tendency, such as the mean, the median, and the mode.
  60. The most commonly used measure of central tendency is themean, which is the arithmetic average of the scores. The mean is calculated by adding up all the scores and dividing the sum by the number of scores. mean is not a good summary method to use when the data include a few extremely high or extremely low scores.
  61. A distribution with a few very high scores is called a positively skewed distribution. A distribution with a few very low scores is called a negatively skewed distribution. The mean of a positively skewed distribution will be deceptively high, and the mean of a negatively skewed distribution will be deceptively low.
  62. 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.
  63. Another measure of central tendency is the mode. Themode is the most frequently occurring score in a distribution.
  64. Measuring VariationMeasures of variation tell researchers how much the scores in a distribution differ. Examples of measures of variation include the range and the standard deviation.
  65. The range is the difference between the highest and the lowest scores in the distribution. Researchers calculate the range by subtracting the lowest score from the highest score.
  66. The standard deviation provides more information about the amount of variation in scores. It tells a researcher the degree to which scores vary around the mean of the data.
  67. Inferential StatisticsAfter analyzing statistics, researchers make inferences about how reliable and significant their data are.Example: The researcher’s survey 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 eight hours, and for students in Courses B and C, the average was about six 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.
  68. 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
  69. Psychologists usually consider a result to be statistically significant if such a result occurs just by chance 5 or fewer times out of every 100 times a study is done. They call this statistical significance 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.
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Encyclopedia of Counseling Research & Program Evaluation
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