Statistical methods can be divided into descriptive and inferential statistics.
Descriptive statistics summarize data, whereas inferential statistics allow researchers to test hypotheses about data and determine how confident they can be in their inferences about the data.
They do not allow for conclusions to be made about anything other than the particular set of numbers they describe.
Central Tendency —- they characterize the typical value in a set of data. (mean, mode, and median)
The mean —- the arithmetic average of a set of numbers
The mode —- the most frequently occurring value in the data set.
The median —- the number that falls exactly in the middle of a distribution of numbers.
These statistics can be represented by a normal curve
The graph of the normal distribution depends on two factors —- the mean (decide the location of the center of the graph) and the standard deviation (decides the height and width of the graph).
A positive skew —- most values are on the lower end, but there are some exceptionally large values. This creates a “tail” or skew toward the positive end.
A negative skew —- most values are on the higher end, but there are some exceptionally small values. This creates a “tail” or skew toward the negative end.
Although the mean, the mode, and the median give approximations of the central tendency of a group of numbers, they do not tell us much about the variability in that set of numbers.
Variability —- how much the numbers in the set differ from one another.
Standard Deviation —- a function of the average dispersion of numbers around the mean and is a commonly used measure of variability.
Percentile —- express the standing of one score relative to all other scores in a set of data.
It is used frequently when reporting scores on standardized test.
We need statistical techniques to describe how the attributes we are studying relate to one another.
Correlation coefficient —- a numerical value that indicates the degree and direction of the relationship between two variables.
Correlation coefficients range from +1.00 to -1.00.
The sign (+/-) indicates the direction of the correlation, and the number (0 to +/- 1.00) indicates the strength of the relationship.
Pearson correlation coefficient — a descriptive statistic that describes the linear relationship between two attributes.
Pearson correlations can be positive, zero, or negative and are typically measured on a scale ranging from 1 to 0 to -1
From the picture above, we could see that a correlation may be graphed using a scatter plot. The closer the points come to falling on a straight line, the stronger the correlation.
Line of best fit (regression line) — the line drawn through the scatter plot that minimizes the distance of all the points from the line.
Inferential statistics —- used to determine our level of confidence in claiming that a given set of results would be extremely unlikely to occur if the result were only up to chance.
Sample —- the small group of people in the experiment
Population —- the large group to whom the psychologist is trying to generalize
Representative —- the sample reflects the characteristics
Sample size —- number of observations or individuals measured.
Null hypothesis —- a treatment had no effect in an experiment
Alternative hypothesis —- the treatment did have an effect.
Inferential statistics allow us the possibility of rejecting the null hypothesis with a known level of confidence, that is, of saying that our data would be extremely unlikely to have occurred were the null hypothesis true.
Alpha (p value)— the accepted probability that the result of an experiment can be attributed to chance rather than the manipulation of the independent variable.
Given that there is always the possibility that an experiment’s outcome can happen by chance, no matter how improbable, psychologists usually set alpha at 0.05, which means that an experiment’s results will be considered statistically significant if the probability of the results happening by chance is less than 5 percent.
Two types of errors
Type I Error —- the conclusion that a difference exists when in fact this difference does not exist.
Type II Error —- the conclusion that there is no difference when in fact there is a difference.
Psychologists pay particularly close attention to Type I error because they want to be conservative in their inferences: they do not want to conclude that a difference exists if in fact it does not.
|The null is true||The null is False|
|Fail to reject the null||Correct decision||Type II Error|
|Reject the null||Type I error||Correct decision|
Ethics In Research
Psychological experiments involve deception, which might bias results. The deception is typically small, but in rare instances it can be extreme.
In 1970s, Stanley Milgram conducted obedience experiments in which he convinced participants that they were administering painful electric shocks to other participants, when, in fact, no shocks were given.
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In conclusion, this experiment 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.
After this experiment, ethical standards have been set forth by the American Psychological Association (APA) to ensure the proper treatment of animal and human subjects.
Institutional Review Board (IRB) asses the research plans before the research is approved to ensure that it meets all ethical standards.
Informed consent —- participants agree to participate in the study only after they have been told what their participation entails.
Participants are also allowed to leave the experimental situation if they become uncomfortable about their participation.
Debriefing —- after they experiment is concluded, participants must receive it, 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 —- the researcher will not identify the source of any of the data.
Many experiments involve collecting sensitive information about participants that the participants might not want to be revealed. For this reason, most psychological data is collected anonymously, with the participant’s name not attached to the collected data. If such anonymity is not possible, it is the researcher’s ethical obligation to ensure that names and sensitive information about participants are not revealed.
Risk —Participants cannot be placed at significant mental or physical risk.
No Coercion — Participants should be voluntary.
Animal Research must meet the following requirements:
— They must have a clear scientific purpose
— The research must answer a specific, important scientific question
— Animals chosen must be best-suited to answer the question at hand.
— They must care for and house animals in a humane way.
— They must acquire animal subjects legally. Animals must be purchased from accredited companies. If wild animals must be used, they need to be trapped in a humane manner.
— They must design experimental procedures that employ the least amount of suffering feasible.
Subfields in Psychology
Applied Psychology —- psychology put directly into practice.
For example: when a therapist meets with a client/ school psychology
Basic psychology —- grounded in research and is often conducted at universities and private laboratories.
Industrial psychology —- the study of human organization and the application of these principles in solving the complex problems present in a variety of workplaces.
Psychiatry — the study of mental disorders, and its practitioners are medical doctors who can prescribe medication, whereas “psychology” is a much broader category.
- Social psychology