The Lemon Juice Experiment-Introvert vs Extrovert

The amount of saliva you produce after putting a drop of lemon juice on your tongue might tell you something about your personality.

It’s to do with a part of your brain called the Reticular Activating System (RAS) which responds to stimuli like food, or social contact. For example, it controls the amount of saliva you produce in response to food. A good food stimulus is lemon juice. Squeezing lemon juice on to your tongue makes your mouth water, and it does this because your RAS is responding to the lemon juice.

Scientists now think introverts have increased activity in their RAS and therefore increased production of saliva. The theory is that the RAS in introverts has a high level of activity, even when it isn’t being stimulated. So it only needs a small stimulus to produce a large response. This means that introverts are likely to produce a large amount of saliva in response to lemon juice. But because the RAS also reacts to social contact, introverts react more strongly to meeting people too.

In extraverts, on the other hand, there is a low level of activity in the RAS when it isn’t stimulated, so they require a much larger stimulus to generate a response. So they usually produce less saliva in response to lemon juice than introverts, but are more comfortable with social contact.

Try this simple test with your friends and family and compare your results.

The Test

You will need:

* Lemon juice
* Kitchen scales
* Cotton wool balls

This is what you need to do:

* Put a large drop of lemon juice on your tongue and swill it around your mouth for ten seconds
* Use the cotton wool balls to mop up all the saliva that you produce
* When you’ve mopped it all up, put the cotton wool balls on your kitchen scales and see how much they weigh
* Compare your results with your friends and family, and see whose weighs the most

We expect that you will find:

* That introverts produce a lot of saliva in response to lemon juice
* That extraverts don’t produce much saliva in response to lemon juice

Now try our personality test and our ‘necker cube’ experiment to see if they say you are more of an extravert or an introvert. And to find out whether the results from the lemon juice experiment tally up.

In this test, the introverts produced 50% more saliva than the extraverts. But it’s worth bearing in mind that there are lots of other factors that affect saliva production, such as time of day and how thirsty you are.

http://www.bbc.co.uk/ science/humanbody/mind/articles/personalityandindividuality/lemons.shtml

Do Opposites Attract Or Do Birds Of A Feather Flock Together?

Do people tend to select romantic partners that are similar to them or opposite to them? And does spouse similarity lead to marital happiness? In one of the most comprehensive studies ever undertaken on these questions, researchers at the University of Iowa find that people tend to marry those who are similar in attitudes, religion and values. However, it is similarity in personality that appears to be more important in having a happy marriage.
Psychologist Eva C. Klohnen, Ph.D., and graduate student Shanhong Luo, M.A., of the University of Iowa looked at assortative mating issues (mating based on similar or opposite characteristics) among 291 newlyweds who had participated in the Iowa Marital Assessment Project. The newlyweds had been married less than a year at the time the study began and had dated each other for an average of three and a half years. The couples were assessed on a broad range of personality characteristics, attitudes and relationship quality indicators.

Results show that couples were highly similar on attitudes and values; however, they had little or no above-chance similarity on personality-related domains such as attachment, extraversion, conscientiousness and positive or negative emotions. There is no evidence that opposites attract. What is most intriguing is that when the researchers assessed marital quality and happiness, they found that personality similarity was related to marital satisfaction, but attitude similarity was not.

"People may be attracted to those who have similar attitudes, values, and beliefs and even marry them – at least in part – on the basis of this similarity because attitudes are highly visible and salient characteristics and they are fundamental to the way people lead their lives," explain the authors. Personality-related characteristics, on the other hand, take much longer to be known and to be accurately perceived and are not likely to play a more substantial role until later in the relationship, they add.

"However, once people are in a committed relationship, it is primarily personality similarity that influences marital happiness because being in a committed relationship entails regular interaction and requires extensive coordination in dealing with tasks, issues and problems of daily living. Whereas personality similarity is likely to facilitate this process, personality differences may result in more friction and conflict in daily life," say the authors. "As far as attitudes are concerned, people who chose to marry each other should be well aware of how similar or different they are on these domains because attitudes are very visible and salient. This suggests that attitudinal and value differences, when they exist, are part of a conscious decision to stay together on the basis of other important considerations, according to Luo and Klohnen.

Given that their research indicates that similarity in attitudes and values may play a different role in relationship development than does personality similarity, Luo and Klohnen suggest that future research should examine how similarity in different domains are related to relationship outcomes for couples in earlier and later stages of relationship development.

###

Article: "Assortative Mating and Marital Quality in Newlyweds: A Couple-Centered Approach," Shanhong Luo and Eva C. Klohnen, University of Iowa; Journal of Personality and Social Psychology, Vol. 88, No. 2.

Full text of the article is available from the APA Public Affairs Office or at http://www.apa.org/journals/releases/psp882304.pdf

http://www.sciencedaily.com/releases/2005/02/050213191438.htm#

Tip of the Day: Multiple Regression

A more sophisticated test than correlation and is used when trying to explore the predictive power of a set of Independent variables on one Dependent Variable

Questionnaire of the Week

This is a link to the 29-item Locus of Control Scale developed by Julian Rotter. Locus of Control refers to the extent to which individuals believe that they can control events that affect them. On This site you will also find the scoring key for the instrument. Click Here

The Classroom as a Social Environment

In viewing the classroom as a social system, we are employing a conceptual framework within which relations can be observed and tested and reliable knowledge about teaching-learning behaviors might possibly be constructed. It is a model capable of bringing home to us the network of interrelationships of which the specific classroom forms a small but vital connecting link. We are forced to direct our attention to teacher-pupil and pupil-pupil interaction, and to the nature of the learning occurring for each member as a result of participation in the particular ongoing system.

Psychology 101: Example of Classical Conditioning

Psychology 101: Example of Classical Conditioning

Student-Centered Class Room Management

Student centered classroom Management would be one built on the perspectives of constructivist theories.

Persons learn best when:

• They provide input into the planning of their own goals and processes
• They have opportunities for social learning
• They feel comfortable in the learning environment
• They have a variety of learning options appropriate to their learning styles

This suggests learning will be enhanced and students will be more motivated to attend and participate in programs that provide opportunities for learners to be involved in the management of their own setting.

Tip of the Day: Pilot Study

Conduct a pilot study
Pretesting, or conducting a pilot study, is like a dress rehearsal for your survey. Although it
takes time, conducting a pilot study saves time in the long run because it helps you identify
potential problems with your survey’s design while there is still time to fix them.

How to select a sampling Technique and survey method

A sample is a part of an entire population that possesses attitudes, opinions, habits, or
characteristics that you wish to study. A census includes an entire population. Consider the size
of the population you’re sampling, and then decide whether you want to survey a sample
or a census. If you elect to survey a sample, you might use one of the following techniques.

Purposive sampling
Use non-probabilistic or purposive sampling, if you want to learn about people with special
characteristics. Purposive sampling is often used for focus groups.

Example:
You want to survey females between the ages of 18 and 25 who watch television
at least 10 hours a week. (yep, days of our lives)You’ll want to conduct a purposive sample, to be
sure that you include all of the relevant characteristics and exclude individuals
who don’t fit these requirements. Using every “nth” name Systematic sampling, the easiest random sampling method, generates a multiple of a number: for example, every 5th, 10th, or 34th name from a population list. Beware of hidden patterns in your list that could compromise the integrity of the sample, however. The list may include names sorted by frequency or recency
of contact, geographic origin, or similar company size.
Using more than one sampling method You may use more than one sampling method for your survey. You may conduct a simple random sample but purposely over-sample one
stratum—households with a certain level of income, for example. With these additional data, you can perform two studies: one on the whole population and the other on a specific subset. This
type of sample is called a stratified sample.

Choose a survey method
There are two basic methods for conducting a survey: self-administered and interviewer administered.
Self-administered surveys can be written—a paper questionnaire handed out to respondents or sent by mail, or conducted electronically via the Web. Self-administered surveys
can also be oral. Interviewer administered
surveys can be conducted in person or over the phone, with interviewers recording results on paper or electronically. If questions are personal or require a lot of thought, self-administered
surveys are a good choice.

Statistical SIgnificance

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"Significance level" is a misleading term that many researchers do not fully understand. This article may help you understand the concept of statistical significance and the meaning of the numbers produced by The Survey System.

This article is presented in two parts. The first part simplifies the concept of statistical significance as much as possible; so that non-technical readers can use the concept to help make decisions based on their data. The second part provides more technical readers with a fuller discussion of the exact meaning of statistical significance numbers.

In normal English, "significant" means important, while in Statistics "significant" means probably true (not due to chance). A research finding may be true without being important. When statisticians say a result is "highly significant" they mean it is very probably true. They do not (necessarily) mean it is highly important.

Take a look at the table below. The chi (pronounced kie like pie) squares at the bottom of the table show two rows of numbers. The top row numbers of 0.07 and 24.4 are the chi square statistics themselves. The meaning of these statistics may be ignored for the purposes of this article. The second row contains values .795 and .001. These are the significance levels and are explained following the table.

Do you buy Brand X gasoline?
			Area		Type of Vehicle
		Total	City	Suburb	Car	Truck	Bus	Van
	Base	713	361	352	247	150	44	180
Yes		428 60%	215 60%	213 61%	131 53%	74 49%	29 66%	131 73%
No		285 40%	146 40%	139 40%	116 47%	76 51%	15 34%	49 27%
	Chi Square		0.07 .795		24.4 .001

Significance levels show you how likely a result is due to chance. The most common level, used to mean something is good enough to be believed, is .95. This means that the finding has a 95% chance of being true. However, this value is also used in a misleading way. No statistical package will show you "95%" or ".95" to indicate this level. Instead it will show you ".05," meaning that the finding has a five percent (.05) chance of not being true, which is the converse of a 95% chance of being true. To find the significance level, subtract the number shown from one. For example, a value of ".01" means that there is a 99% (1-.01=.99) chance of it being true. In this table, there is probably no difference in purchases of gasoline X by people in the city center and the suburbs, because the probability is .795 (i.e., there is only a 20.5% chance that the difference is true). In contrast the high significance level for type of vehicle (.001 or 99.9%) indicates there is almost certainly a true difference in purchases of Brand X by owners of different vehicles in the population from which the sample was drawn.

The Survey System uses significance levels with several statistics. In all cases, the p value tells you how likely something is to be not true. If a chi square test shows probability of .04, it means that there is a 96% (1-.04=.96) chance that the answers given by different groups in a banner really are different. If a t-test reports a probability of .07, it means that there is a 93% chance that the two means being compared would be truly different if you looked at the entire population.

People sometimes think that the 95% level is sacred when looking at significance levels. If a test shows a .06 probability, it means that it has a 94% chance of being true. You can't be quite as sure about it as if it had a 95% chance of being be true, but the odds still are that it is true. The 95% level comes from academic publications, where a theory usually has to have at least a 95% chance of being true to be considered worth telling people about. In the business world if something has a 90% chance of being true (probability =.1), it can't be considered proven, but it is probably better to act as if it were true rather than false.

If you do a large number of tests, falsely significant results are a problem. Remember that a 95% chance of something being true means there is a 5% chance of it being false. This means that of every 100 tests that show results significant at the 95% level, the odds are that five of them do so falsely. If you took a totally random, meaningless set of data and did 100 significance tests, the odds are that five tests would be falsely reported significant. As you can see, the more tests you do, the more of a problem these false positives are. You cannot tell which the false results are - you just know they are there.

Limiting the number of tests to a small group chosen before the data is collected is one way to reduce the problem. If this isn't practical, there are other ways of solving this problem. The best approach from a statistical point of view is to repeat the study and see if you get the same results. If something is statistically significant in two separate studies, it is probably true. In real life it is not usually practical to repeat a survey, but you can use the "split halves" technique of dividing your sample randomly into two halves and do the tests on each. If something is significant in both halves, it is probably true. The main problem with this technique is that when you halve the sample size, a difference has to be larger to be statistically significant.

The last common error is also important. Most significance tests assume you have a truly random sample. If your sample is not truly random, a significance test may overstate the accuracy of the results, because it only considers random error. The test cannot consider biases resulting from non-random error (for example a badly selected sample).

To summarize:

• In statistical terms, significant does not necessarily mean important.
• Probability values should be read in reverse (1 - p).
• Too many significance tests will turn up some falsely significant relationships.
• Check your sampling procedure to avoid bias.

Part Two - The Exact Meaning of Statistical Significance Numbers

The preceding discussion recommends reading probability values in reverse (1 - p). Doing so will normally lead to correct decision making, but it is something of an over-simplification from the technical point of view. A more complex, technically correct discussion is presented here.

Unfortunately, statistical significance numbers do not directly tell us exactly what we want to know. They tell us how likely we would be to get differences between groups in our sample that are as large or larger than those we see, if there were no differences between the corresponding groups in the population represented by our sample. In other words, these numbers tell us how likely is our data, given the assumption that there are no differences in the population. What we want to know is how likely there are differences in the population, given our data.

Logically, if we are sufficiently unlikely to get a difference found in our sample, if there were no difference in the population, then it is likely that there is a difference in the population. We used this logic in the first part of this article when we said that you can interpret significance numbers by considering 1-p as the probability that there is a difference in the population (where p is the significance number produced by the program). For example, if the significance level is .05 then you could consider the likelihood that there is a difference in the population to be 95% (1-.05).

While this logic passes the common sense test, the mathematics behind statistical significance do not actually guarantee that 1-p gives the exact probability that there is a difference is the population. Even so, many researchers treat 1-p as that probability anyway for two reasons. One is that no one has devised a better general-purpose measure. The other is that using this calculation will usually lead one to a useful interpretation of statistical significance numbers.

In some non-survey fields of research, the possibility that 1-p is not the exact probability that there is a difference in the population may be more important. In these fields, the use of statistical significance numbers may be controversial.


Article taken from HERE. You will also find a sample size calculator to help you work out the number of people you will need to interview in order to obtain results that can be generalized to the target population as precisely as you want.

Psychological Instruments

I am in possession of a number of public domain Psychological Assessment Instruments. If you are in need of an instrument to measure a Variable, drop me a link, I just might have one that would provide you with a measure for the variable of interest.

Tips of the day: Planning your survey

Questionnaire design

Determine your survey’s length. The ideal length depends upon the topic and the
type of population you need to study. In general, limit the length of your questionnaire to encourageprospective respondents to participate.

General guidelines:

■ A survey targeting children should take no longer than 5 to 7 minutes to complete
■ For most populations, self-administered surveys should be no longer than four pages
■ Phone interviews should run no longer than 10 minutes
■ Face-to-face interviews can continue for an hour or longer

Balance length and information

With a shorter questionnaire, you should get a higher response rate and reduce the chance of
error and missing data. However, you will also get less information from your respondents and
may have a less comprehensive study. The key to a successful survey is to ensure that your
questions are concise and easy to understand and gives you valid, reliable information.

Keep questions short

Make each question easy to understand and, if possible, less than 25 words in length.
Avoid using “double negatives,” as this type of phrasing often confuses respondents.
For Example Which of the following questions do you
find clearer?
“I agree that alcohol should be available in
UWI vending machines.”
“I don’t agree that alcohol should not be
available in UWI vending machines.”

Choose appropriate question formats

Some questions can be easily answered with a single answer, but others may require multiple
choices—a scale or a grid. And some may best be answered through an open-ended
text response. Choosing an appropriate format will make it easier for respondents to answer
questions clearly.

Tip of the Day

Exploring relationships- here you are not interest in differences between groups but rather in the strength of the relationship between variables. There are a variety of techniques to do so such as :
Correlations- here you can use Pearson or Spearman correlation to explore the strength of the relationship between two variables. These statistics will provide you with an indication of both the direction and strength of the relationships
Remember, a positive relationship indicates that as one variables increases, so does the other variables, whilst a negative correlation suggests that as one variable increases, the other decreases.

MEN AND WOMEN FOUND MORE SIMILAR THAN PORTRAYED IN POPULAR MEDIA

The popular media has portrayed men and women as psychologically different as two planets – Mars and Venus - but these differences are vastly overestimated and the two sexes are more similar in personality, communication, cognitive ability and leadership than realized, according to a review of 46 meta-analyses conducted over the last 20 years.

According to the meta-analysis of studies on gender differences reported on in the current issue of the American Psychologist, males and females from childhood to adulthood are more alike than different on most but not all psychological variables, said psychologist Janet S. Hyde, Ph.D., of the University of Wisconsin in Madison. Psychological differences based on gender were examined in studies that looked at a number of psychological traits and abilities to determine how much gender influenced an outcome. The traits and variables examined were cognitive abilities, verbal and nonverbal communication, social or psychological traits like aggression or leadership, psychological well-being like self-esteem, motor behaviors like throwing distance and moral reasoning.

Gender differences accounted for either zero or a very small effect for most of the psychological variables examined, according to Hyde. Only motor behaviors (throwing distance), some aspects of sexuality and heightened physical aggression showed marked gender differences.

Furthermore, gender differences seem to depend on the context they were measured in, said Hyde. In studies where gender norms are removed, researchers demonstrated how important gender roles and social context were in determining a person’s actions. In one study where participants in the experimental group were told that they were not identified as male or female nor wore any identification, neither sex conformed to a stereotyped image when given the opportunity to act aggressively. They did the opposite to what was expected.

Over-inflated claims of gender difference seen in the mass media affect men and women in work, parenting and relationships, said Hyde. Studies of gender and evaluation of leaders in the workplace show that women who go against the caring, nurturing stereotype may pay for it dearly when being hired or evaluated. This also happens with the portrayals of relationships in the media. Best-selling books and popular magazine articles assert that women and men can’t get along because they communicate too differently, said Dr. Hyde. Maybe the problem is that they give up prematurely because they believe they can’t change what they mistakenly believe is an innate trait, she added.

Children also suffer the consequences of these exaggerated claims of gender difference. There is a wide spread belief that boys are better in math than girls, said Dr Hyde. But according to this meta-analysis, boys and girls perform equally in math until high school where boys do gain a small advantage. Unfortunately, elementary aged mathematically-talented girls may be overlooked by parents who have lower expectations for a daughter’s success in math versus a son’s likelihood to succeed in math. Research has shown that parents’ expectations for their children’s math success relate strongly to a child’s self-confidence and his or her performance.

The misrepresentation of how different the sexes are, which is not supported by the scientific evidence, harms men and women of all ages in many different areas of life, said Dr. Hyde. “The claims can hurt women’s opportunities in the workplace, dissuade couples from trying to resolve conflict and communication problems and cause unnecessary obstacles that hurt children and adolescents’ self-esteem.”

Sourced from: The Gender Similarities Hypothesis,” Janet Shibley Hyde, Ph.D., University of Wisconsin – Madison; American Psychologist, Vol. 60, No. 6.

Tip of the Day: Data Collection

when wishing to collect data from diverse geographical locations, it might be useful to use an online survey tool such as Qualtrics, to help simplify the task. Qualtrics allows you to create questionnaires online, after which you simply send out the links to your population of interest. Best of all, the collected data can be downloaded directly into SPSS for analysis.[Yep, your days of keying in data are over :)]
www.Qualtrics.com

Example of Classical Conditioning

Tip of the day: SPSS Correlations

When seeking a relationship between more than 10 variables, it is useful to run a correlation matrix, that way you can see all the sigificant relationships at one glance, instead of having to scroll down the page and seek them one by one.

Gestalt and memory processes

Kaffka’s Memory•

•Memory Process
–Brain activity based on specific environmental event
•Memory trace
–Remnant of memory process remain in the brain after environmental stimulus is gone
•Trace system
–Consolidation of a number of trace systems
•Interaction of these three produces smoother and organized Memory

Welcome

I decided to create this blog to provide my many tutorial students, access to some material that appears to be difficult to find at times :). Hopefully This blog will be insightful and provide some direction as you travel through University Life. Feel free to comment about the material presented, and please make any suggestions as to material you would like to see covered.

Teddy