Wednesday, October 15, 2014

B. Stat examination (3rd Sem), ISI., Kolkata

Topics

1. Perceptual organization
2. Information processing model
3. Theories of forgetting
4. Experiments in classical conditioning
5. Laws of learning and learning curve
6. Variables and measurement
7. Characteristics of good questionnaire

Below are the outlines of the chapter for bird's eye view. Some chapters are available by clicking respecting sites.

1. Perceptual Organization


Perceptual organization:  It is the process of establishing relations among potentially separate elements of the object in perception. Perceptual organization guides the interpretation of the object. It includes 4 principles as proximity, similarity, good form, closure.

ProximityAccording to the law of proximity, things that are near each other seem to be grouped together.
SimilarityOther things being equal, elements which are similar in structure or have common characteristics will be grouped together.
Good Form (Law of Pragnanz): This law states that perceptual organization will always be as “good” as the prevailing conditions allow. The simplest organization requiring the least cognitive effort will always emerge. Pragnanz means that we perceive the simplest organization that fits the stimulus pattern.
Closure: An incomplete figure will be seen as a complete one. a figure consisting of incomplete lines, that have gap in them. It is perceived as a triangle despite the fact that its sides are incomplete. A closure like phenomenon yields subjective contours.


2. Information processing model:





3. Theories of forgetting


8) What is forgetting?

Forgetting is the loss, permanent or temporary, of the ability to recall or recognize something learned earlier (Munn, 1967).

9) Discuss the causes of forgetting/ theories of forgetting.

 According to information-processing theories, forgetting occurs as, some information due to lack of attention may not have reached to short term memory (STM) from sensory register, or, due to inadequate encoding or rehearsal , information have not been transferred from short-term memory (STM) to long-term memory(LTM). According to levels of processing theory, information is
not stored in LTM because rehearsal was not sufficiently elaborate. But forgetting does not occur only through loss of much information before being stored in LTM. Constructive processes at work, during the process of encoding, distort what is stored and people think they forget because memory
does not match events as they actually occurred. Thus, forgetting occurs due to following causes:

i) Information when not properly transferred from STM to LTM. This is explained by Trace Decay Theory and Displacement theory.

ii) Trouble in properly locating information already available in LTM. This is explained by Interference theory, Retrieval theory and Motivated forgetting.

iii) Forgetting occurred due to some changes of biological processes, which occur, with time. This results in amnesia, alzeihmer’s disease etc. This is explained by Biological Decay theory.

A) TRACE DECAY THEORY OF FORGETTING

This explanation of forgetting in short term memory assumes that memories leave a trace in the brain. A trace is some form of physical and/or chemical change in the nervous system. Trace decay theory states that forgetting occurs as a result of the automatic decay or fading of the memory trace. Trace decay theory focuses on time and the limited duration of short term memory. This theory suggests short term memory can only hold information for between 15 and 30 seconds unless it is rehearsed. After this time the information / trace decays and fades away. No one disputes the fact that memory tends to get worse the longer the delay between learning and recall, but there is disagreement about the explanation for this effect. According to the trace decay theory of forgetting, the events between learning and recall have no affect whatsoever on recall. It is the
length of time the information has to be retained that is important. The longer the time, the more the memory trace decays and as a consequence more information is forgotten. There are a number of methodological problems confronting researchers trying to investigate the trace decay theory.

One of the major problems is controlling for the events that occur between learning and recall. Clearly, in any real-life situation, the time between learning something and recalling it will be filled with all kinds of different events. This makes it very difficult to be sure that any forgetting which takes place is the result of decay rather than a consequence of the intervening events. Support for
the idea that forgetting from short-term memory might be the result of decay over time came from research carried out by Brown (1958) in the United Kingdom, and Peterson and Peterson (1959) in the United States. The technique they developed has become known as the Brown-Peterson task.

B) DISPLACEMENT FROM STM

Displacement seeks to explain forgetting in short term memory, and suggests it’s due to a lack of availability. Displacement theory provides a very simple explanation of forgetting. Because of its limited capacity, suggested by Miller to be 7+/- 2 items, STM can only hold small amounts of information. When STM is 'full', new information displaces or 'pushes out’ old information and takes its place. The old information which is displaced is forgotten in STM. Support for the view that displacement was responsible for the loss of information from short-term memory came from studies using the 'free-recall' method. A typical study would use the following procedure: participants listen to a list of words read out a steady rate, usually two seconds per word; they are then asked to recall as many of words as possible. They are free to recall the words in any order, hence the term 'free recall'. The findings from studies using free recall are fairly reliable and they produce similar results on each occasion.

C) INTERFERENCE THEORY

Memory can be disrupted or interfered with by what we have previously learned or by what we will learn in the future. This idea suggests that information in long term memory may become confused or combined with other information during encoding thus distorting or disrupting memories. Interference theory states that forgetting occurs because memories interfere with and disrupt one another, in other words forgetting occurs because of interference from other memories (Baddeley, 1999). There are two ways in which interference can cause forgetting:

1. Proactive interference (pro=forward) occurs when you cannot learn a new task because of an old task that had been learnt. When what we already know interferes with what we are currently learning – where old memories disrupt new memories.

2. Retroactive interference (retro=backward) occurs when you forget a previously learnt task due to the learning of a new task. In other words, later learning interferes with earlier learning - where new memories disrupt old memories. Proactive and retroactive Interference is thought to be more likely to occur where the memories are similar, for example: confusing old and new telephone numbers. Chandler (1989) stated that students who study similar subjects at the same time often experience interference. Previous learning can sometimes interfere with new learning (e.g. difficulties we have with foreign
currency when travelling abroad). Also new learning can sometimes cause confusion with previous learning. (Starting French may affect our memory of previously learned Spanish vocabulary). In the short term memory interference can occur in the form of distractions so that we don’t get the chance to process the information properly in the first place. (e.g. someone using a loud drill just
outside the door of the classroom.)


D) RETRIEVAL FAILURE THEORY

Retrieval failure is where the information is in long term memory, but cannot be accessed. Such

information is said to be available (i.e. it is still stored) but not accessible (i.e. it cannot be retrieved). It cannot be accessed because the retrieval cues are not present. When we store a new memory we also store information about the situation and these are known as retrieval cues. When we come into the same situation again, these retrieval cues can trigger the memory of the situation. Retrieval cues can be:

o External / Context - in the environment, e.g. smell, place etc.
o Internal / State- inside of us, e.g. physical, emotional, mood, drunk etc.

There is considerable evidence that information is more likely to be retrieved from long-term memory if appropriate retrieval cues are present. This evidence comes from both laboratory experiments and everyday experience. A retrieval cue is a hint or clue that can help retrieval.

Tulving (1974) argued that information would be more readily retrieved if the cues present when the information was encoded were also present when its retrieval is required. He suggested that information about the physical surroundings (external context) and about the physical or psychological state of the learner (internal context) is stored at the same time as information is
learned. Reinstating the state or context makes recall easier by providing relevant information,

while retrieval failure occurs when appropriate cues are not present. For example, when we are in a different context (i.e. situation) or state.

E) MOTIVATED FORGETTING

 Sigmund Freud (1951) clearly stated the principle underlying motivated forgetting. Freud’s key concept in psychoanalysis, repression is the form of motivated forgetting. Repression refers to the tendency of people to have difficulty retrieving anxiety provoking or threatening information from
the long term memory. Perhaps this explains why people generally remember pleasant events more often than they do unpleasant ones; the unpleasant memories have been repressed.

F) BIOLOGICAL DECAY THEORY

Forgetting occurred due to some changes of biological processes, which occur, with time. This results in amnesia, alzeihmer’s disease etc. (Refer to Morgan & King Book, Pg no. 208-212).

4. Experiments in classical conditioning


pavlov classical conditioning

Know the theory here

7. Characteristics of good questionnaire

Questionnaire is a device to gauge individual differences in behaviour. Good questionnaire has four major characteristics

a) Standardization:  The instruction, testing environment, test administration procedure, test scoring are standardized.

b) Reliability:  Test items and test periods are consistent.

c) Validity: Test items and test scores are measuring what they intend to measure.

d) Norm: The standard on which basis individual or group classification will be determined

Sunday, October 12, 2014

PSYCHOPHYSICS & MEASUREMENT SCALES


PSYCHOPHYSICS & MEASUREMENT SCALES

D. Dutta Roy
B. STAT. 3rd Year (Elective)
13. 10. 2014

In Psychology, there is peaceful co-existence of science and arts. It is science as it deals with systematic investigation. It is arts as it deals with subjective experience. Multiple cognitions about single object appear at the same time in psychological research. Psychological research is very complex as same object is perceived differentially to different people. Black cloud is appeared as threat to tourists as they apprehend cancellation of tour. On the other side, same cloud is appeared as security to the farmers who anticipate rain from black cloud. When other is perceiving cloud as black, the farmer does not think that it is black as black carries different meanings to farmers. This typical phenomenon is studied in Psychology. Another typical phenomenon is simultaneous presence of different meanings to same object. One villager is worried as he is not getting different transports like city. At the same time, he thinks that more transports cause more air pollution so he is free from respiratory disorders. All these issues are discussed in psychophysics and scales of measurement.

4.1 PSYCHOPHYSICS: Psychophysics is the study about relation between change in physical and psychological scale. Weber and Fechner have noted that change in experience is not similar to the change in physical events. One dim light may not be sensed but systematically graded change makes it sensed. It means presence of dim light in physical scale but not in psychological scale. With gradual increase in intensity, one level will come where in presence of light occcurs 50% of total trials. In other words, there is 50% chance of the absence of light. This lower limit of absence and presence of light is called absolute threshold. When it occurs at the upper limit of intensity, it is called terminal threshold. Threshold refers to the level of stimulus intensity where in change occurs 50% of total trials. Gradual change in intensity of light may not be differentiated with earlier presentation of light intensity. Again, one level will come where in individual just notices difference. The limit where in difference is perceptible 50% of total trials. is called differential threshold or DL. After DL, terminal threshold comes when stimulus intensity is extreme. Knowledge of psychophysics helps us in construction of item, response categories and administration of items.

4.2 RESPONSE CATEGORIES AND PROBABILITY

The intention of response scale construction is to gauge individual differences in response. Experiments of Psychophysics describe how response changes with change in stimulus characteristics. Item stem represents stimulus characteristics. And response categories are psychological change. Stimulus characteristics should be felt by respondents but level of experience should differ. This is most important in item construction. To assess satisfaction with any object, initially, it is important to assess whether each respondent is exposed to the object. For example, the question - "Are you satisfied with library service ?" assumes that each respondent is aware of the meaning of library, has experience in library service and has different levels of satisfaction. The response 'yes' or 'no' should differ at least 50 % of respondents for between individuals and 50% of times in case of within individuals. In Survey research, between individual difference is important but in clinical or individual based research, within individual difference is used. Student's independent t - ratio is used for between individual or between group differences. But within individual difference requires paired t-test. Above example includes binary response categories. Binary response categories are useful when there is 50% probability for each category to occur. But there is some situation where in 50% probability does not occur. Rather each response category needs graded difference. For example, those who are satisfied with library service, may be very satisfied, or moderately satisfied. Like wise, those who are not satisfied may be less and least satisfied. Under any condition, there will be 50% chance to occur. It means 50% chance to be occurred for each response category.

4.3 MEASUREMENT SCALES:

Scale is the continuum having graded series of numerical values. It has start and end points. Start and end points are determined by researcher. The changes in the scale are graded series, therefore, it is systematic in nature. It has numerical values so it can be used for measurement. Example is thermometer, weight machine. Scaling follows principles of maximization and minimization. Maximization principle asserts wide variation of response categories like five or seven point response scales. To understand extent of happiness, researcher can use five point response scales like very happy, happy, undecided, less happy and least happy. Sometimes, respondent can not make discrimination between very happy and happy due to low intelligence, depression etc. In this case, researcher can minimize number of response categories like happy and unhappy. Depending on characteristics of respondent, researcher selects specific measurement scale out of four. These are nominal, ordinal, interval and ratio scales. Instruction, response pattern and scoring procedure vary with types of measurement scales.

4.3.1 Nominal Scale

It is a system of assigning number symbols for labeling. Researcher uses this scale for classification following three principles -minimization, equality and discrimination.

Minimization : Response categories are smaller. These are usually 2 or 3. For example, in the Eysenck Personality Questionnaire or EPQ, response categories are three - yes, no, don't know.

Discrimination: Assigned numbers should make adequate discrimination between the labels. In EPQ, Items measuring psychoticism do not overlap with items measuring neuroticism. Non-overlapping enhances good discrimination power of the questionnaire. Discrimination principle asserts unequal identity or dissimilar properties in the object or event.

Equality: In Nominal Scale, only rule for assigning numbers is that all members of any class shall have the same number and that no two classes shall be assigned the same numbers. This rule accepts principles of equality. Equality principle asserts that each object or event must have same identity. For example, girls with different heights have common property, i.e. they all are girls. Therefore all girl respondents are assigned ‘2’.

 INSTRUCTION: Instruction of nominal scale includes how to label the response. For example, put tick mark over 1 if you are boy and over 2 if you are girl. ITEM STEM: Item stem asks for label. Examples: a) Are you boy or girl? Boy=1, Girl=2. b) What is your religion? Hindu=1, Islam=2, Christian=3. c) What is your Caste? S.T=1, S.C=2, O.B.C=3, General=4. STATISTICS: Frequency and percentage are common descriptive statistics. Chi-square can be used for drawing inferences. Variables with nominal scale can be used as explanatory or independent variables in t-statistics. By adding frequency of similar response, score can be computed. For example, there are 20 items in the questionnaire, out of them 10 items with 'yes' response measure neuroticism. The questionnaire has been administered to patient suffering from General anxiety disorder. It is noted all the 10 items receive 'yes' response. So the score is 10. Extent of score variation indicates extent of neuroticism. Based on score, distance in traits between individuals can be possible but not between the nominal categories. Distance between Yes, No categories of two items can not be determined.

Advantages: a) Nominal scale is useful for classification or categorization. b) It is more flexible. According to hypothesis, numerical values can be assigned. c) Nominal scale is used as explanatory variable.

Disadvantages: a) Nominal scale has no metric properties therefore many parametric statistics requiring continuous distribution can not be determined through nominal scale. b) It requires different statistical conversation techniques to make it continuous.

4.3.2 Ordinal Scale: Nominal scale can not order the events. It can label the event but can not estimate successive occurrence of events. Ordinal Scale assigns numerals or rank value following principles of successive categories. These principles make discrimination among the set of objects in terms of preference. A set of students can be ordered in terms of academic performance. A set of sportsmen can be ordered in terms of sports performance. Order can be made in the form of ascending like first, second, third or descending order like third, second and first. When two students get same marks, their orders will be same. It is called paired order or tied. Tied orders are averaged and next order occurs after the last order. For example, 3 events possess equal ranks say 3. Then each event will get 3, 4, 5 ranks and the average will be 4. Next event will start from 6. Ordinal scale does not assume equal distance between orders. Distance between 1st and 2nd is not equal to distance between 3rd and 4th. This is the disadvantage of the ordinal scale. Advantage of the ordinal scale is it's flexibility. One can follow both ascending and descending orders.

Instruction: Instruction of ordinal scale includes how to arrange the events in ascending or descending order.

Item stem : Item stem includes the issue or event and it's operational definition.

Statistics : When data are arranged in order, frequency, percentage statistics are used like nominal scale. One can estimate which event has received first or second rank by analysis of frequency. One can use median when data are arranged with rank values. Most of the non-parametric statistics follow ordinal scale or ranks. Rank order cosrrelation is widely used statistics when one is interested to determine coefficient of correlation in small sample distribution.

Advantages: a) Ordinal scale is useful to arrange the objects in ascending or descending order. b) Median value can be estimated through ordinal scale. c) Relative preference of the object can be determined with ordinal scale. d) Several non-parametric statistics use ordinal scale.

Disadvantages a) Like, nominal scale, it has limited use in statistics as it does not follow equidistant. b) It can not be scored.

4.3.3. Interval Scale: In ordinal scale one can not make any subtraction or addition to classify the person, object or event. For example, second rank student can not be subtracted from first rank student to find out difference in performance between two ranked persons. Another problem in rank order scale, equidistance assumption can not be made. We can not assume rank difference between 1 and 2 is equal to same between 2 and 3. But interval scale assumes equidistant points between each of the scale elements. The widely used summated rating scale or Likert type rating scale is interval scale. It has properties of metric scale in terms of the extent of differences in response. It is assumed that response difference is equidistant. Some researchers call it as quassi continuous scale as middle response category appears to be neutral. Some researchers argue that this is categorical scale as they merely consider the numerical values. Therefore, we can interpret differences in the distance along the scale. We contrast this to an ordinal scale where we can only talk about differences in order, not differences in the degree of order. Any parametric statistics are useful to analyze the item data.

 Instruction: Instruction of ordinal scale includes how to rank. But interval scale includes how to rate the response categories. Interval scale follows maximization principles. Response categories are more and equidistant. Numerals are assigned to different ratings. Widely used ratings are strongly agree, agree, undecided, disagree and strongly disagree.

Item-stem : It can be both affirmative and interrogative. To assess one's happiness, item stem may be how much happy are you ? Or I feel happy always. It must be remembered that response categories should not be in the item stem. In earlier example on 'I feel happy always', response categories should not include the text 'always' rather it can be strongly agree, agree, disagree, strongly disagree. Item stem and response categories will be framed in such a manner so that data distribution will not be skewed.

Statistics: Interval scale follows equidistant principles, so any parametric statistics can be used.

Advantages: a) Interval scale follows equidistant principles, so any parametric statistics can be used. b) It can be scored. c) it can be classified into groups by cut-off points.

Disadvantages: a) Interval scale has undecided point. This violates continuity. b) It does not have neutral point like ratio scale.

4.3.4. Ratio scale: Interval scale measures single dimension of variable across graded series. One's feeling of both happiness and unhappiness can be assessed by interval scale using two separate scales measuring happiness and unhappiness separately. Advantage of ratio scale is to assess both feeling of happiness and unhappiness simultaneously. For example, watching black cloud, farmers sometimes feel pleasant and sometimes feel unpleasant. Ratio scale is composed of two bi-polar adjectives. One adjective will be extremely opposite of another. For example, strong and weak, good and bad, active and lazy. This scale is often called as semantic differential scale as meaning of object or event is differentiated semantically with opposite adjectives. As per hypothesis, rating value is assigned to the adjective. Strong, good and active are assigned +3 and weak, bad and lazy are given -3 rating. So two opposite adjectives are located at two opposite poles of neutral point or 0. Other grades like -1,-2 are located between 0 and -3. Similarly, +1 and +2 are located between 0 and 3. So, final scale to assess strong and weak dimension will be +3, +2, +1, 0,-1,-2,-3. So, there are two interval scales ranging from +1 to +3 and from -1 to -3. Respondent assumes +3 as very strong, +2 as strong. Likewise, -3 as very weak, -2 as weak. And 0 is conceived as neutral. Here zero stands for neither more nor less than none of the property represented by the scale.

 Instruction: Instruction includes systematic rating from 0 to -3 or from 0 to +3. As there is no label from 0 to +3 or from 0 to -3, respondent can assign own label following direction of adjectives. For example, instead of very strong, respondent can think of very much strong. Item-stem Scoring: Before scoring, researcher first assumes meaning of high score. For example, +3 is highest score and -3 is lowest. Then +3 will be replaced by 7 and -3 will be replaced by 1. 0 will be replaced by 4. So, highest score will be 7 and lowest score will be 1.

 Statistics: Like interval scale, any parametric and non-parametric statistics can be used with ratio scale.

Advantages: a) Ratio scale can assess one object with bi-polar adjectives simultaneously. b) Like normal probability curve, ratio scale assumes bi-polarity. It has zero like normal probability distribution. And the successive gradation from 0 to +3 or -3 is equidistant. Therfore, it can be used in any parametric statistics. c) It is less time consuming for data collection. d) It can assess different dimensions of one object simultaneously. Osgood has noted three opposite dimensions using ratio scale.

Disadvantages: a)Theoretically, one can not say that attributes of satisfaction are opposite of dissatisfaction. Herzberg has proved that attributes of job satisfaction is not opposite of the same for assessing job dissatisfaction. Therefore, use of bi-polar adjectives for assessing one event can not provide sufficient information. b) It is complex to score as rating values during data collection are replaced by another value during scoring. c) No event can be neutral, therefore considering 0 value as neutral is not meaningful.