WHAT IS PSYCHOLOGY, DEFINITION OF PSYCHOLOGY, MEAN OF PSYCHOLOGY

WHAT IS PSYCHOLOGY?   

Beginning with the first psychological laboratory, founded

 in 1879 by German philosopher and physiologist

Wilhelm Wundt, modern psychology’s can be traced in 

many disciplines and countries. Psychology’s

historical perspectives and current activities lead us to 

define the field as the science of behavior and mental 

processes.

Theoretical perspectives of psychology 

There are many disciplines that study human nature. 

Psychology is one. Within psychology, the biological,

behavioral, psychoanalytic, cognitive and social+l- cultural 

perspectives are complementary. Each has its own

purposes, questions, and limits; together they provide a fuller 

understanding of mind and behavior.   

        DEFINITION

“Psychology is the scientific study of behavior and mental processes …. Human or Animal”

Behavior is overt, manifest, obvious, and easy to study;    

the mental processes that help carryout these

behaviors are covert, underlying, hidden, and not easy to 

study. Besides behavior, what causes these

behaviors to occur and the mental processes involved in it 

is an important area of interest for a

psychologist.

Psychologists study animals’ behavior too; to better understand and predict human behavior, the

study of animal behavior becomes essential at times, 

especially because some researches cannot be

carried out with humans due to safety reasons or 

ethical issues

Job Application Form,

Job Application Form, 

Job Application Template 

Employment Form

Principles of accounting,Basic Accounting,Financial Accounting Lecture #1

Islamic Story 2

Business Accounting and Bookkeeping

SCREEN SHOOT:

IN this video discus how to manage the books of account of  business.

1.  The  term bookkeeping means not same different people give different ideas:

1. Some people thinking that bookkeeping is the same as accounting. They assume that keeping a company's books and preparing its financial statements and tax reports are all part of bookkeeping. Accountants do not share their view.
2. Some people see t bookkeeping as limited to recording transactions in journals or daybooks and then posting the amounts into accounts in ledgers. After the amounts are posted, the bookkeeping has ended and an accountant with a college degree takes over. The accountant will make adjusting entries and then prepare the financial statements and other reports.
3. The past distinctions between bookkeeping and accounting have become blurred with the use of computers and accounting software. For example, a person with little bookkeeping training can use the accounting software to record vendor invoices, prepare sales invoices, etc. and the software will update the accounts in the general ledger automatically. Once the format of the financial statements has been established, the software will be able to generate the financial statements with the click of a button.

Marketing and distribution

Marketing are activities of a company associated with buying and selling a product or service. It includes advertising, selling and delivering products to people. People who work in marketing departments of companies try to get the attention of target audiences by using slogans, packaging design, celebrity endorsements and general media exposure.

I.T Services for business

SCREEN SHOOT:

Information technology (IT) is the study of computer and other things are related with IT like mobile games tablet  application of computers to store, study, retrieve, transmit, and manipulate data,or information, often in the context of a business or other enterprise. IT is considered a subset of information and communications technology (ICT).

Product Designed for Marketing

BUSINESS PLAN

Business. An organization or economic system where goods and services are exchanged for one another or for money.The businesses is divided in to three type of business one sole proprietorship, Partnership, Company , than company divided to more types butdiscus next time.  

HOW TO START NEW BUSINESS

Business. An organization or economic system where goods and services are exchanged for one another or for money.The businesses is divided in to three type of business one sole proprietorship, Partnership, Company , than company divided to more types but discus next time.  

NONRANDOM SAMPLING

‘Nonrandom sampling’ implies that kind of sampling in which the population units are drawn into the sample by using one’s personal judgment. This type of sampling is also known as purposive sampling. Within this category, one very important type of sampling is known as Quota Sampling.

QUOTA SAMPLING

In this type of sampling, the selection of the sampling unit from the population is no longer dictated by chance. A sampling frame is not used at all, and the choice of the actual sample units to be interviewed is left to the discretion of the interviewer. However, the interviewer is restricted by quota controls. For example, one particular interviewer may be told to interview ten married women between thirty and forty years of age living in town X, whose husbands are professional workers, and five unmarried professional women of the same age living in the same town. Quota sampling is often used in commercial surveys such as consumer market-research. Also, it is often used in public opinion polls.

ADVANTAGES OF QUOTA SAMPLING

· There is no need to construct a frame.
· It is a very quick form of investigation.
· Cost reduction.

SIMPLE RANDOM SAMPLING

In this type of sampling, the chance of any one element of the parent pop being included in the sample is the same as for any other element. By extension, it follows that, in simple random sampling, the chance of any one sample appearing is the same as for any other. There exists quite a lot of misconception regarding the concept of random sampling. Many a time, haphazard selection is considered to be equivalent to simple random sampling. For example, a market research interviewer may select women shoppers to find their attitude to brand X of a product by stopping one and then another as they pass along a busy shopping area --- and he may think that he has accomplished simple random sampling!
Actually, there is a strong possibility of bias as the interviewer may tend to ask his questions of young
attractive women rather than older housewives, or he may stop women who have packets of brand X prominently on show in their shopping bags!.
In this example, there is no suggestion of INTENTIONAL bias! From experience, it is known that the human being is a poor random selector --- one who is very subject to bias.
Fundamental psychological traits prevent complete objectivity, and no amount of training or conscious effort can eradicate them. As stated earlier, random sampling is that in which population units are selected by the lottery method. As you know, the traditional method of writing people’s names on small pieces of paper, folding these pieces of paper and shuffling them is very cumbersome!
A much more convenient alternative is the use of RANDOM NUMBERS TABLES.
A random number table is a page full of digits from zero to 9. These digits are printed on the page in a TOTALLY

random manner i.e. there is no systematic pattern of printing these digits on the page.

OTHER TYPES OF RANDOM SAMPLING

· ·Stratified sampling (if the population is heterogeneous)
· Systematic sampling (practically, more convenient than simple random sampling)
· Cluster sampling (sometimes the sampling units exist in natural clusters)
· Multi-stage sampling
All these designs rest upon random or quasi-random sampling. They are various forms of PROBABILITY sampling ---
that in which each sampling unit has a known (but not necessarily equal) probability of being selected.
Because of this knowledge, there exist methods by which the precision and the reliability of the estimates can be calculated OBJECTIVELY.
It should be realized that in practice, several sampling techniques are incorporated into each survey design, and only rarely will simple random sample be used, or a multi-stage design be employed, without stratification. The point to remember is that whatever method be adopted, care should be exercised at every step so as to make the results as reliable as possible.

SAMPLING & NON-SAMPLING ERRORS

1. SAMPLING ERROR

The difference between the estimate derived from the sample (i.e. the statistic) and the true population value (i.e. the parameter) is technically called the sampling error. For example,
Sampling error = X -U
Sampling error arises due to the fact that a sample cannot exactly represent the pop, even if it is drawn in a correct manner

2. NON-SAMPLING ERROR

Besides sampling errors, there are certain errors which are not attributable to sampling but arise in the process of data
collection, even if a complete count is carried out.
Main sources of non sampling errors are:
· The defect in the sampling frame.
· Faulty reporting of facts due to personal preferences.
· Negligence or indifference of the investigators
· Non-response to mail questionnaires.
These (non-sampling) errors can be avoided through
· Following up the non-response,
· Proper training of the investigators.
· Correct manipulation of the collected information,
Let us now consider exactly what is meant by ‘sampling error’: We can say that there are two types of non-response ---
partial non-response and total non-response. ‘Partial non-response’ implies that the respondent refuses to answer some of the questions. On the other hand, ‘total non-response’ implies that the respondent refuses to answer any of the questions. Of course, the problem of late returns and non-response of the kind that I have just mentioned occurs in the case of HUMAN populations. Although refusal of sample units to cooperate is encountered in interview surveys, it is far more of a problem in mail surveys. It is not uncommon to find the response rate to mail questionnaires as low as 15 or 20%.The provision of INFORMATION ABOUT THE PURPOSE OF THE SURVEY helps in stimulating interest, thus increasing the chances of greater response. Particularly if it can be shown that the work will be to the ADVANTAGE of the respondent IN THE LONG RUN.
Similarly, the respondent will be encouraged to reply if a pre-paid and addressed ENVELOPE is sent out with the questionnaire. But in spite of these ways of reducing non-response, we are bound to have some amount of non-response.
Hence, a decision has to be taken about how many RECALLS should be made.
The term ‘recall’ implies that we approach the respondent more than once in order to persuade him to respond to our queries.
Another point worth considering is:
How long the process of data collection should be continued? Obviously, no such process can be carried out for an indefinite period of time! In fact, the longer the time period over which the survey is conducted, the greater will be the potential VARIATIONS in attitudes and opinions of the respondents. Hence, a well-defined cut-off date generally needs to be established. Let us now look at the various ways in which we can select a sample from our population. We begin by looking at the difference between non-random and RANDOM sampling. First of all, what do we mean by nonrandom sampling?

SAMPLING FRAME

A sampling frame is a complete list of all the elements in the population. For example:

• The complete list of the BCS students of Virtual University of Pakistan on February 15, 2003
• Speaking of the sampling frame, it must be kept in mind that, as far as possible, our frame should be free fromvarious types of defects:
• does not contain inaccurate elements
• is not incomplete
• is free from duplication, and
• Is not out of date.

Next, let’s talk about the sample that we are going to draw from this population.
As you all know, a sample is only a part of a statistical population, and hence it can represent the population to only to some extent. Of course, it is intuitively logical that the larger the sample, the more likely it is to represent the population. Obviously, the limiting case is that: when the sample size tends to the population size, the sample will tend to be identical to the population. But, of course, in general, the sample is much smaller than the population.
The point is that, in general, statistical sampling seeks to determine how accurate a description of the population the sample and its properties will provide. We may have to compromise on accuracy, but there are certain such advantages of sampling because of which it has an extremely important place in data-based research studies.

ADVANTAGES OF SAMPLING

1. Savings in time and money.
· Although cost per unit in a sample is greater than in a complete investigation, the total cost will
be less (because the sample will be so much smaller than the statistical population from which
it has been drawn).
· A sample survey can be completed faster than a full investigation so that variations from
sample unit to sample unit over time will largely be eliminated.
· Also, the results can be processed and analyzed with increased speed and precision because
there are fewer of them.
2. More detailed information may be obtained from each sample unit.
3. Possibility of follow-up:
(After detailed checking, queries and omissions can be followed up --- a procedure which might prove impossible in a
complete survey).
4. Sampling is the only feasible possibility where tests to destruction are undertaken or where the population is
effectively infinite.
The next two important concepts that need to be considered are those of sampling and non-sampling errors.

‘POPULATION’

A statistical population is the collection of every member of a group possessing the same basic and defined
characteristic, but varying in amount or quality from one member to another.

EXAMPLES

· Finite population:
IQ’s of all children in a school.
· Infinite population:
Barometric pressure:
(There are an indefinitely large number of points on the surface of the earth).
A flight of migrating ducks in Canada
(Many finite pops are so large that they can be treated as effectively infinite). The examples that we have just
considered are those of existent populations.
A hypothetical population can be defined as the aggregate of all the conceivable ways in which a specified event can
happen.

For Example:

• All the possible outcomes from the throw of a die – however long we throw the die and record the results,we could always continue to do so far a still longer period in a theoretical concept – one which has no existence in reality.

•  The No. of ways in which a football team of 11 players can be selected from the 16 possible members named by the Club Manager.

We also need to differentiate between the sampled population and the target population. Sampled population is that from which a sample is chosen whereas the population about which information is sought is called the target population thus our population will consist of the total no. of students in all the colleges in the Punjab.
Suppose on account of shortage of resources or of time, we are able to conduct such a survey on only 5
colleges scattered throughout the province. In this case, the students of all the colleges will constitute the target pop whereas the students of those 5 colleges from which the sample of students will be selected will constitute the sampled population. The above discussion regarding the population, you must have realized how important it is to have a very well-defined population.
The next question is: How will we draw a sample from our population?
The answer is that: In order to draw a random sample from a finite population, the first thing that we need is the complete list of all the elements in our population.
This list is technically called the FRAME.

COLLECTION OF SECONDARY DATA

The secondary data may be obtained from the following sources:
· Official, e.g. the publications of the Statistical Division, Ministry of Finance, the Federal and Provincial
Bureaus of Statistics, Ministries of Food, Agriculture, Industry, Labour, etc.
· Semi-Official, e.g., State Bank of Pakistan, Railway Board, Central Cotton Committee, Boards of Economic
Inquiry, District Councils, Municipalities, etc.
· Publications of Trade Associations, Chambers of Commerce, etc
· Technical and Trade Journals and Newspapers
· Research Organizations such as universities, and other institutions
Let us now consider the POPULATION from which we will be collecting our data. In this context, the first important
question is: Why do we have to resort to Sampling?
The answer is that: If we have available to us every value of the variable under study, then that would be an ideal and a
perfect situation. But, the problem is that this ideal situation is very rarely available --- very rarely do we have access to
the entire population.
The census is an exercise in which an attempt is made to cover the entire population. But, as you might know, even the
most developed countries of the world cannot afford to conduct such a huge exercise on an annual basis!
More often than not, we have to conduct our research study on a sample basis. In fact, the goal of the science of
Statistics is to draw conclusions about large populations on the basis of information contained in small samples.