Objective and Subjective Tendencies:
Posted by Magellanic Cloud on August 28, 2006
Objective Tendencies and Subjective Tendencies:
Objective Tendencies:
For example, in Geography, the ‘climate’ is considered to be long term average of weather conditions. ‘Objective’ (actual) data of various elements of weather such as temperature, humidity, precipitation, etc. is collected over long period of time (lets say 30 years), then using the techniques of the statistical analysis, various averages are derived. These averages are the ‘objective tendencies’ in this case. These tendencies are objective because the source data was objective in nature.
‘Objective tendencies’ are different from ‘objective principles’. The ‘principles’ that are objectively verifiable to be true are the objective principles.
‘Principles’ cannot be objectively verified using statistical techniques. The results of statistical techniques can only be objective or subjective tendencies. Tendencies are different from principles. Principles are generalized abstractions of material or abstract phenomena. Principles can be objectively verified only through laboratory method. Whenever ‘principles’ shall be tested using laboratory methods, we always shall receive the expected results (in case of causeeffect relations, however, we may or may not get the expected results but in case of ‘principles’, we always shall receive the expected results).
Tendencies, on the other hand, are derived (i.e. not verified) using statistical techniques. Generally such tendencies are derived out of the statistical analysis which is performed on past or present data. On the basis of such derived results, predictions about the characteristics of the phenomenon in question, about the future periods are made. There is no guarantee, however, that in future, the characteristics of the phenomenon shall be those as were anticipated or predicted as per the results of those statistical techniques. The term ‘verification’ does not seem to be suitably applied in the case of tendencies because ‘verification’ is always done with the hope to get the expected results. Since there is no guarantee in the case of tendencies that the actual outcome of the phenomenon shall always be as per the predictions, so we do not have any such hope to get the expected results in the case of tendencies. So the term ‘verification’ is not suitably applicable in the case of tendencies. Tendencies, however can be rederived (i.e. not verified). Upon rederivation, the tendencies may not give the same result as before.
In case of ‘principles’ the term ‘verification’ is suitable because we hope that we shall get expected results using the laboratory method. In case of tendencies, we cannot have this kind of hope. Whenever we shall again test our results by again applying the statistical technique to the same sample size, we cannot hope to get exactly same outcome (expected) that we received previously. So tendencies cannot be verified, they can just be rederived. We always shall not receive the expected results.
Nature of ObjectiveTendencies:
Objective tendencies are sum total effect of various underlying principles. The principles, individually can be objectively verified through laboratory method but the total effect of so many principles can become so much complex that now this total effect cannot be tested through laboratory experimentation. Now it is convenient to analyze the total effect in terms of statistical analysis.
Difference of ‘Objective Tendencies’ and Mathematics’ concept of ‘Probability’:
‘Objective Tendencies’ are the ‘generalizations’ of particular occurrences that are ‘observed’ and ‘analyzed’ in a controlled manner. In other words, ‘objective tendencies’ are ‘particular to general’ type of conclusions. Particular data about certain objective phenomenon are statistically analyzed and various averages are calculated. The ‘generalized conclusion’ is that so calculated averages are considered to be the integral characteristics of the phenomenon in question. Thus future occurrences are considered to be predictable because it is thought that the calculated averages, which are the ‘integral characteristics’ of phenomenon in question, shall determine the nature, in quantitative terms, of the future occurrences of the phenomenon under study.
The concept of ‘probability’, as found in mathematics, has slightly different meanings. ‘Probability’ is not ‘particular to general’ type of conclusion. In case of probability, the phenomenon under study usually can have limited number of possible outcomes. By applying the ‘mathematical tool’ i.e. probability, it is tried to determine such issues as probability (in numerical or percentage terms) of the occurrence of particular outcome in the immediate next time in future etc. This concept can be better explained by quoting some real numerical problems that can be seen in mathematics’ textbooks. Following are some of the examples:
Example1:
In a box, there are 5 red balls with numbers printed on them (one on each ball) and three white balls with numbers 1,2,3, (one on each ball). From the box a man draw 2 balls at random.
a. What is the probability that one of the balls drawn is white and other is red?
b. What is the probability that the two balls drawn have the same number or the same color?
Example2:
6 cards are drawn at random from a deck of 52 cards. What is the probability that three will be red and three black.
Example3:
Three coins are tossed. What is the probability of
getting (i) exactly two heads (ii) at most two heads (iii) at least one head.
Example4:
“A bag contains 8 white and 8 black balls. 4 balls are drawn. Find the number of possibilities in which;
a. All are white.
b. All are black.
c. 2 white and 2 black.
Another Example with Solution:
Problem:
Find the probability that on throw of a die will;
a. Have ‘3’ on top.
b. Have ‘5’ on top.
c. Greater than ‘4’.
d. An odd number.
Solution:
A die is a cubeshaped gambling instrument with dots numbering one to six on each side. Assume that it is well balanced die; that is, each of the six sides will have an equal chance to turn on the top when the die stops in a throw.
Then the sample points are the six dots and the sample space is;
S = {1,2,3,4,5,6}
The following answers have been “calculated” in the solution :
Solutions:
a. = 1/6
b. = 1/6
c. = 1/3
d. = 1/2
Critical Analysis of this concept of ‘Probability’:First of all we should consider that despite being the ‘probability’ of 1/6 of having ‘3’ on top, the actual practical throws of die, most ‘probably’ shall give different results than to the ones so calculated. There must be something wrong in this type of ‘mathematical’ probability. If it is valid then practically every one out of six throws of die must show ‘3’ on top. If the practical ratio of having ‘3’ on top is different from the calculated value, then this type of ‘probability’ must be invalid. Practical invalidity of this type of probability is quite easy to prove. Just practically throw the die, lets say for 100 times and note down the number of times when die had ‘3’ on top. Most ‘probably’, the practically observed ratio shall be different from the calculated value. Consider the following practical results when a die was actually thrown 102 times and the results are recorded:
Valueon Top

ActualFrequency

‘Probable’Frequency (1/6)

1 
16 
17 
2 
22 
17 
3 
16 
17 
4 
14 
17 
5 
13 
17 
6 
21 
17 
Totals 
102 
102 
Valueon Top

ActualFrequency

‘Probable’Frequency (1/2)

Odd Numbers 
45 
51 
Even Numbers 
57 
51 
Totals 
102 
102 
Valueon Top

ActualFrequency

‘Probable’Frequency (1/3)

Smaller than 3 
38 
34 
3 and 4 
30 
34 
Greater than 4 
34 
34 
Totals 
102 
102 
The comparison of the actual experimental results with the ‘probable’ values clearly shows that this type of ‘probability’, with surety, cannot be considered to be a practically valid concept. This concept is practically invalid because it is logically invalid.
This Type of ‘Probability’ is Logically Incorrect:
When a die is thrown, for example, the fact that which side shall be on the top has nothing to do with the number of times the die is thrown. Actually there is no logical connection between the ‘topvalue’ and the ‘numbers of time’ the die was thrown. The topvalue shall not be determined by the number of times the die would be thrown. The valid logical connection of the topvalue is actually with ‘just how’ the die was thrown i.e. at what speed, force and angle etc. If the die is thrown every time with exactly the same speed, force and angle etc. then no matter for how many times it is thrown, we always shall get the same topvalue. So this type of probability is logically inaccurate because it does not accurately identify the actual logical connection between cause and effect. There is actually no logical connection between topvalue and the number of times the die was thrown. But it is actually wrongly has been assumed that the connection has the existence.
Subjective Tendencies:
Social sciences have the claim that their theories are objective in nature because these theories have been formulated on the basis of the results of well organized research methods. These research methods include laboratory experimentation method as well as statistical analysis method. The laboratory method, in case of social sciences is applied usually on minor and micro level issues such as can a particular kind of training improve the work performance of employees or not. This issue can be tested in laboratory settings. Some of the employees can be given that training on test basis and the effects of the training on their performance can be recorded. If the results found to be satisfactory, then the results are generalized and it is considered that the particular training actually results in better performance of employees. There are other technicalities also involved in this process. Various other theories of these social sciences are said to be based on statistical analysis based research methods. The important thing to be noted is that such statistical techniques, as are used in these research methods, cannot give objective output. In typical such a research, a number of persons are selected on sample basis and their subjective opinions on any particular social issue are taken. This data is compiled and then this compiled data is statistically analyzed and various averages are derived. These averages are claimed to be the objective output.
In fact these averages are not objective in nature. These averages are just ‘subjective tendencies’. These tendencies are subjective because the source data was only the subjective opinions of the selected number of persons.
The concept of ‘subjective tendencies’ should be differentiated from the concept of ‘impartial subjective opinions’. The ‘impartial subjective opinions’ are those that are not one sided or ‘partial’. To be impartial does not necessarily mean that input from all the available opinions on the issue have to be part of the resulting opinion. An impartial subjective opinion may get all the input from only one of the available opinions on the issue and still not be given the status of being ‘one sided’ or ‘partial’. It is so because, as previously also has been described, that while becoming ‘impartial’, all other available opinions are positively evaluated and analyzed. After such evaluation, only one of the opinions may be considered to be the true one. This finally selected opinion, in this case, is the ‘impartial subjective opinion’. The ‘impartial subjective opinions’ can be derived only through oral or written debate which is composed of both objective and subjective elements. We cannot get impartial subjective opinions by applying statistical techniques.
Subjective tendencies, on the other hand, necessarily take input from all the available subjective opinions. In this way the impact or the effect of wrong opinions also becomes part of final results. This is the necessary result of the application of statistical techniques in case of analysis of opinions on any theoretical issue. So statistical analysis based subjective tendencies, in fact are the tendencies of right and wrong opinions. These types of tendencies cannot be considered to be objective facts. But this is what social scientists are actually doing. Now see that the laboratory method, in the case of social issues, which is mostly applicable only in the case of minor and particular micro level issues. Other theoretical issues of these ‘social sciences’ cannot become objective just due to the fact that these issues have been resolved through the application of statistical analysis based research method. The major issues of these ‘social sciences’ for example the major theories of Sociology which are the nature of society and culture as well as roles and functions of various social institutions etc. can neither be tested in laboratory settings for their accuracy and validity, nor it would be right to test these theories using any statistical analysis based research method. So it is just incomprehensible for why the subject of Sociology (including some other ‘social sciences’ as well) is considered to be an objective subject and why this subject is considered to be a ‘social science’ when actually the nature of its major theories and issues is subjective? Actually, the subject of Sociology is considered to be objective in nature for unknown reasons.
These subjective tendencies are also not ‘principles’. There can be no subjective principles. Subjectivity cannot be verified through laboratory methods. Even if some phenomenon of human’s internal feelings is verifiable under laboratory settings, then in this case even this ‘internal feeling’ cannot be considered to be subjective in nature. Now this type of ‘internal feeling’ has become objective, because it is verifiable under laboratory settings. Only those internal feelings and information are subjective which cannot be known to others by using any external object or event including laboratory method. Subjectivity can be known to others only through proper use of argumentation.
The things that can be verified through laboratory methods are ‘objective principles’. And the ‘principles’ are only those that can be objectively verified through laboratory methods. Since subjectivity cannot be objectively verified using the laboratory methods, so there cannot be any such thing as ‘subjective principles’. And if subjectivity becomes testable using laboratory method then it automatically becomes objective. So subjective principles cannot exist. Subjectivity can be in the form of ‘impartial subjective opinion’ or may be in the form of ‘subjective tendencies’. These two are separate concepts and should be applied for different purposes. The ‘objective tendencies’ can be used for the purpose to forecast future objective events. The ‘subjective tendencies’, on the other hand, can be used only for the purpose to forecast future tendencies of subjective opinions. It means that future social events cannot be rightly forecasted using the subjective tendenciesbecause the impact of wrong opinions, which is part of subjective tendencies would not let us rightly forecast about the social events. Future social events however can be better forecasted using the accurate impartial subjective opinions.
Objective Tendencies 
Forecasting about the future objective events may or may not be true with more chances of being true. 
Subjective Tendencies 
Forecasting about the future social events have to be wrong except in the case of by chance true forecasting. Forecasting about future tendencies of subjective opinions, however may or may not be true with more chances of being true. 
Accurate Impartial Subjective Opinions 
Forecasting about future social events as well as about future subjective tendencies may or may not be true with more chances of being true. 
Objective tendencies only can forecast about future objective events. Subjective tendencies cannot forecast about future social events but these subjective tendencies can forecast about future pattern of subjective opinions. Accurate impartial opinions can forecast about future social events as well as about future pattern of subjective opinions.
As already have been stated that the subjective tendencies, due to their nature, cannot be used to forecast about future social events. These tendencies, however, can be used to forecast just about the future patterns and tendencies of future subjective opinions.
A given pattern of a number of subjective opinions
cannot accurately represent the overall social situation. This pattern only represent the general opinions on the issue i.e. it do not represent the actual situation about the issue. On the other hand, the impartial subjective opinion can represent the overall social situation. Personal Opinions on Social Issues can be of
following Types (i.e. following type of data can be collected through survey forms for the purpose of finding their statistical averages):
1) Likings/ dislikings of people (their own) 
On the basis of statistical averages of these likings/ dislikings we only can conclude that certain percentage of people would possibly ‘like’ the product etc. On the basis of this information, we however cannot conclude that the product itself is good or bad etc. 
2) Objective facts such as age, sex, education etc. 
Statistical analysis of these kind of data shall give ‘objective tendencies’. 
3) Personal Attitudes 
Similar to the case of likings/ dislikings. 
4) Opinions about any particular social issue 
Statistical analysis of these kind of data would always give misleading results due to the involvement of the impact of wrong opinions even in the final results. 
Khurram said
khuram,
let me point out your invalid understanding of probability.
You say “Actually there is no logical connection between the ‘topvalue’ and the ‘numbers of time’ the die was thrown”
Exactly! That is why this process is called ‘random’ . Probabilty theory is the study of random processes. It is not an attempt to discover hidden connections.
You say, “But it is actually wrongly has been assumed that the connection has the existence.”
Wrong! Why do you think so? Probability theory does NOT make any claim about discovering any connection. It describes the outcome over a large number of iterations of processes that are random i.e. there is NO connection between throws. Given that the throws are RANDOM probability theory says that the outcome of ‘3 on top’ will occur 1/6 of the times. This does not mean that probability theory knows what the next outcome will be. Nor does it mean that throws will follow a pattern where a ‘3’ occurs every 6th throw. Any prediction of a specific throw or any prediction of a pattern will invalidate the randomness.
you say, “If the practical ratio of having ‘3′ on top is different from the calculated value, then this type of ‘probability’” That is correct, but you need a large number of iterations to get a result that is statistically significant. Just 6 or 12 or 18 throws are not enough. A statistician can make detailed calulations about expected deviation.
This is all very basic statistics and I am surprised that you have such a poor understanding of it.
Please try to understand something before trying to criticize it.
khuram said
Khurram,,
You have pointed out that probability is the study of “random” processes. Then why you apply it to a process which is NOT random at all…??? Throw of dice has PERFECT logical relationship with “Just how the dice is thrown”. So it is NOT a random process. The top number shall NOT be RANDOM. Top number shall be DETERMINED by such things as just how and at which angle etc. the dice was thrown.
Try to find the “logical connections” between events of this universe. What can be regarded as RANDOM, in the real sense, is just the behavior of elementary particles as provided by the Quantum Physics. My advice still is that do not lose courage and try to find … May be one day we shall find some order in the behavior of elementary particles as well. This type of “Probability” whose purpose is to make calculated “guesses” … should NOT given the status of more than a “guess”. And there is just little difference between such a “calculated” guess and any ordinary “intuitive” guess.
And why you are saying that only “large” number of instances will give the “satisfactory” result. After all this type of probability method was “invented” with the view to just win the gambling games. In gambling, the crucial instance may be ONLY ONE. You may not have liberty to try your luck over LARGE NUMBER of instances. Given the situation that only one instance is usually the the crucial one,, then you should try to find the actual factors that really determine the outcome i.e. the top number. Do study this mathematical ‘probability’ also … for the sake of wasting your time. But better option is to try to find logical connections between the events of this universe. Even in the case of Quantum Physics … do not lose hope. Try to find the “cause” of that randomness.
With best wishes,,,
Khuram
Khurram said
khuram,
You are right that only quantum processes are truly random and all other processes are deterministic. No one disagrees with that! Then why have Probability theory at all? That’s because for some processes the variables involved are so complex that it is practically very difficult to predict the outcome. Imagine how complicated it would be to predict the throw of a dice by computing all the forces acting on it. Such processes approximate randomness and probability theory is very useful in understanding their behaviour. Probability theory does NOT ASSERT that the throw of a dice is random. It only ASSUMES that the process is random and based on that assumption it makes prediction about outcomes. The fact that over a large number of iterations these predictions are validated means that the process was close enough to random. Whether a process was actually random or deterministic is a matter for physicists to investigate not statisticians. Probability theory is simply a tool for physicists and others (e.g. insurance actuaries) to make practical predictions when they are faced with degrees of randomness.
“And why you are saying that only “large” number of instances will give the “satisfactory” result. After all this type of probability method was “invented” with the view to just win the gambling games”
Indeed probability theory is used to win gambling games, but by the CASINO and NOT the gamblers. No gambler can predict the outcome of a single bet. Even gamblers who do have a strategy implement it over a large number of bets and not single bets. But the casinoes use probability theory to design the games in their favor. Take the example of the game of Roulette. There are 36 numbers, half red and half black. Then the casinoes add a 0 which is green. If you bet on black or red your odd of winning are 18/37 which is less than 50%. The odds of casino winning is 19/37 which is slightly more than 50%. A lot of people will win individual bets. Some may even have long winning streaks. But the casino knows that in the long term it will make money because over a large number of bets it will win slightly more often than the gambler. All casino games are designed like that. No casino has ever been driven out of business by too successful gamblers.
“Even in the case of Quantum Physics … do not lose hope. Try to find the “cause” of that randomness.”
Einstein spent the last 30 years of his life trying to find ‘hidden variables’ because he was uncomfortable with randomness as the explanation of fundamental physical processes. He died without success. After his death a person called Bell came up with a theorem to predict results of certain experiments that could determine whether the underlying processes were random or a result of hidden variables. In the 60’s/70’s era people were able to carry out experiments to test this theorem. The experimental results showed conclusively that there are no hidden variables. Quantun processes are truly random. (See Bell’ theorem at wikipedia)