1. Experimental Research
Research Methods
Experimental Research

2. Experimental Research
This form of research is the only way to determine a cause and effect relationship between variables.

3. Experimental Research
Experiment: a carefully regulated procedure in which the researcher manipulates one or more variables to see if it influences some other variable.

4. Experimental Research
Example: to measure whether taking antidepressants decreases depression, the researcher would create two groups: one that takes the medication and one that does not. By comparing the results between the groups, the experimenter can determine whether taking antidepressants does indeed reduce depression.

5. Experimental Research
Experimental Group: The group of people who receive the treatment.

6. Experimental Research
Control Group: The group of people who do not receive the treatment.

7. Experimental Research
Random Assignment: Assigning participants to experimental and control groups randomly.
This minimizes preexisting differences between people assigned to different groups.

8. Experimental Research
Population: The entire group about which the investigator wants to draw conclusions.
Sample: The sample of the population chosen by the investigator to study (the participants).

9. Experimental Research
Example: A study on whether sugar increases hyperactivity in children with ADHD.
Population: Children with ADHD
Sample: A group of children with ADHD who will participate in the experiment

10. Experimental Research
Representative Sample: A sample that accurately represents the population being studied.
Example: You wouldn’t want only 12-year-old boys with ADHD to participate in the study.

11. Experimental Research
We tend to generalize from the samples we observe.
If we want our studies to be accurate, we must make sure we select participants that accurately represent the population being studied. Random assignment helps achieve this.

12. Experimental Research
Independent Variable: The variable the experimenter manipulates in order to determine its effects.
It is the “cause” of the results in the experiment.

13. Experimental Research
Dependent Variable: The variable that may change as a result of manipulations in the independent variable.
It is the “effect” in the experiment.

14. Experimental Research
The results of the study (the dependent variable) depend on the independent variable.
IV = Cause
DV = Effect

15. Experimental Research
Hypothesis: Sleeping pill X helps the otherwise healthy person with insomnia to sleep better.
Independent Variable: The cause
Dependent Variable: The effect

16. Experimental Research
Hypothesis: Sleeping pill X helps the otherwise healthy person with insomnia to sleep better.
Independent Variable: Sleeping pill X
Dependent Variable: Quality of sleep

17. Experimental Research
Hypothesis: Taking multivitamins while pregnant will reduce birth defects.
Independent Variable: The cause
Dependent Variable: The effect

18. Experimental Research
Hypothesis: Taking multivitamins while pregnant will reduce birth defects.
Independent Variable: Multivitamins
Dependent Variable: Number of babies with birth defects

19. Experimental Research
An industrial-organizational psychologist examines whether wearing name tags makes the employees happier with their work.
Independent Variable: The cause
Dependent Variable: The effect

20. Experimental Research
An industrial-organizational psychologist examines whether wearing name tags makes the employees happier with their work.
Independent Variable: Name tags
Dependent Variable: Happiness with work

21. Experimental Research
Confounding Variable: An outside influence that affects the results of the study.
Experimenters must make sure to control for confounding variables.

22. Experimental Research
Confounding Variable Example:
Study: How exercise affects weight loss IV: Exercise
DV: Weight loss
Possible confounds: Diet, amount of sleep

23. Experimental Research
Experimenter Bias: Occurs when the experimenter’s expectations influence the outcome of the research.

24. Experimental Research
Research Participant Bias: Occurs when the behavior of the participants during the experiment is influenced by how they think they are supposed to behave or by their expectations about what is happening to them.

25. Experimental Research
Double-Blind Experiment: Neither the experimenter nor the participants are aware of who is in the experimental group and who is in the control group until the results are calculated.

26. Experimental Research
Sampling Bias: When a sample is collected in such a way that some members of the intended population are less likely to be included than others.
Pretty much whenever they aren’t chosen randomly.

27. Experimental Research
Placebo: A harmless substance that looks like a real pill, but has no physiological effect.

28. Experimental Research
Placebo: Given to members of control group to make them think they are receiving the treatment.
Allows researchers to determine whether changes in experimental group are due to the actual medication.

29. Experimental Research
Placebo Effect: Occurs when the participants’ expectations, rather than the experimental treatment, produce a particular outcome.

30. Experimental Research
If the results of a study are replicated, the results are considered to be reliable.

31. Experimental Research
Validity refers to the credibility or believability of the research.

32. Experimental Research
Validity is affected by the quality of the research design.
Should be free from biases and logical errors
Control for and acknowledge any potential confounding variables

33. Research Methods
Statistics

34. Descriptive Statistics
Descriptive Statistics are mathematical procedures used to describe and summarize sets of data in a meaningful way.

35. Descriptive Statistics
A measure of Central Tendency is a single number that represents the overall characteristics of a set of data.

36. Descriptive Statistics
Mean: the average score in a sample.
Obtained by adding the scores and then dividing by the number of scores.
This is the best measure of central tendency.

37. Descriptive Statistics
Median: the middle score in a sample.
If you arrange all the scores in order from lowest to highest, half will be above the median and half will be below it.

38. Descriptive Statistics
Mode: the most common score in a sample.

39. Descriptive Statistics
Measures of variation: refers to how similar or diverse the scores are.
Averages derived from scores with low variability are more reliable than averages based on scores with high variability.

40. Descriptive Statistics
Consider a basketball player who scored between 13 and 17 points in each of her first 10 games.
Knowing this, we would be more confident that she would score near 15 points in her next game than if her scores had varied from 5-25 points.

41. Descriptive Statistics
Range: the gap between the lowest and highest scores.
Provides only a basic estimate of variation.

42. Descriptive Statistics
3, 4, 3, 5, 8, 2, 3, 9, 3
Calculate the
range, median, and mode

43. Descriptive Statistics
3, 4, 3, 5, 8, 2, 3, 9, 3
Range = 7
Median = 3
Mode = 3

44. Descriptive Statistics
2, 4, 5, 7, 7, 9
When you have an even number of scores, the median is calculated by finding the mean of the middle two scores.

45. Descriptive Statistics
2, 4, 5, 7, 7, 9
5 + 7 = 12
12 / 2 = 6
Median = 6

46. Descriptive Statistics
Standard Deviation: indicates how much the scores in a sample differ from the mean (average) in a sample.

47. Descriptive Statistics
If the standard deviation approaches 0, the scores are very similar to each other and very close to the mean.

48. Descriptive Statistics
The higher the standard deviation, the greater the difference among the scores.
Standard deviation is the most useful measure of variation.

49. Descriptive Statistics
Graphing variation
In nature, most scores tend to form a symmetrical bell-shaped distribution known as a normal curve.
This means that 68% of the scores are within 1 standard deviation of the mean.

50. Normal Curve

51. Descriptive Statistics
Positive Skew:
A curve where most values are on the lower end, but there are some exceptionally large/high values.

53. Descriptive Statistics
Negative Skew:
A curve where most values are on the higher end, but there are some exceptionally small/low values.

55. Inferential Statistics
An inference is a conclusion that is reached on the basis of evidence.
Making inferences means drawing conclusions.

56. Inferential Statistics
Mathematical methods that determine whether the data sufficiently supports a research hypothesis.
Tells you the likelihood that your results are accurate and not due to chance.

57. Inferential Statistics
Tells you the likelihood that the independent variable’s effect on the dependent variable is due to chance.

58. Inferential Statistics
Statistical Significance:
Tells you the likelihood that your results are accurate and not due to chance.
Must be less than
p = 5% (.05).

59. Inferential Statistics
If the number is higher than 5% (.05) then the results are not statistically significant.
This means there is a possibility that the results occurred by chance.