Types of Data Analysis

Analysis involves estimating the values of unknown parameters of the population and testing hypothesis for drawing inferences.

Types of Analysis
a. Qualitative analysis
b. Content analysis
c. Quantitative analysis
d. Descriptive analysis
e. Bivariate analysis
f. Sequential analysis
g. Casual analysis
h. Multivariate analysis
i. Inferential analysis

j. Statistical analysis

Qualitative Analysis
It is less influenced by theoretical assumption. The limitation of this type of analysis is that the findings tend to be unrealisable. The information categories and interpreted after, differ considerable from one investigator to another one. In this system researcher to go through, research cycle, to increase reliability, repeating the research cycle is of value in some ways, but it does not ensure that the findings will have high reliability. Qualitative analyses are carried out in several different kinds of study like interview, case studies and observational studies.

Content Analysis
Content analysis is used where originally qualitative information is reduced to numerical terms. It is a method of analysis media output includes articles published in new papers, speeches made in radio, television and various type of propaganda. This method of analysis is applied to all most all form of communications.

Quantitative Analysis
The numerical data collected in study through descriptive statistics analysis can be conducted through measure of central tendency.

Descriptive Analysis
This analysis of one variable is called one dimensional analysis. This analysis measures condition at particular time.

Bivariate Analysis
The analysis in respect of two variables is called bivariate analysis. In this analysis collected data in placed into tabular form, so that the meaning of the data can be derived. In this method simple dimensional data is developed and put into two or more categories.

Sequential Analysis
When only factor is revel in the table at one time, this type of analysis is called sequential analysis is called sequential analysis. If we do the further analysis of the same data regard four going showed that person with leave travel concession facilities are more frequently going on tourism than those who are not gating facilities of casual analysis. It is concerned with study of one variable affecting another one.

Multivariate Analysis

With an advancement of computer application there is fast development of multivariate analysis, in which statistical method simultaneously analysis more than two variables.

Inferential Analysis

In order to decide the validity of data to indicate conclusion this analysis is concerned with tests for significance of hypothesis. One the basis of inferential analysis the task of interpretation is performed by estimating the population values.

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Observation - Methods Of Primary Data Collection

Observation is one way to collect primary data. It is a purposeful, systematic and selective way of watching and listening to an interaction or phenomenon as it takes place. There are many situations in which observation is the most appropriate method of data collection; for example, when you want to learn about the interaction in a group, study the dietary patterns of a population, ascertain the functions performed by a worker , or study the behaviour or personality traits of an individual. it is also appropriate in situations where full and/or accurate information cannot be elicited by questioning, because respondents either are not co-operative or are unaware of the answer because it is difficult for them to detach themselves from the interaction. in summary, when you are more interested in the behaviour than in the
perceptions of individuals, or when subjects are so involved in the interaction that they are unable to provide objective information about it, observation is the best approach to collect the required information.
Types of observation - there are two types of observation:
a.  Participant observation
b. Non-participant observation

Participant observation is when you, as a researcher, participate in the activities of the group observed in the same manner as its members, with or without their knowing that they are being observed.

For example, you might want to examine the reactions of the general population toward people in wheelchairs. you can study their reactions by sitting in a wheelchair yourself of you might want to study the life of prisoners and pretend to be a prisoner in order to do this.

Non-participant observation is when you, as researcher, do not get involved in the activities of the group but remains a passive observer, watching and listening to its activities and drawing conclusions from this.

For example, you might want to study the functions carried out by a worker in a Railway station. As an observe, you could watch, follow, and record the activities as they are performed. After making a number of observation, conclusions could be drawn about the function carry out in the railway station. Any occupational group in any setting can be observed in the same manner.

Problems with using observation as a method of data collection
The use of observation as a method of data collection may suffer from a number of problems, which is not to suggest that all or any of these necessarily prevails in every situation. But as a beginner you should be aware of these problems.

When individuals or groups become aware that they are being observed, they may change their behaviour. Depending upon the situation, this change could be positive or negative – it may increase or decrease, for example, their productivity and may occur for a number of reasons. When a change in the behaviour of person or groups is attributed to their being observed it is known as the Hawthome Effect. The use of observation in such a situation may introduce distortion: What is observed may not
represent their normal behaviour.

There is always the possibility of observer bias. If an observer is biased, she/he can easily introduce bias and there is no easy way to verify the observations and the interference drawn from them

The interpretation draws from observations may vary from observer to observer. There is the possibility of incomplete observation and/or recording, which varies with the method of recording. an observer may watch keenly but at the expense of detailed recording. The opposite problem may occur when the observer takes detailed notes but in doing so misses some of the interaction. Situations in which observations can be made observations can be made under two conditions:
 a. Natural
 b. Controlled
Observing a group in its natural operation rather than interviewing in its activities is classified as observation under natural condition. Introducing a stimulus to the group for in to react to and observing the reaction is called controlled observation.

Recording of Observation
There are many ways of recording observation. The selection of a method of recording depends upon the purpose of the observation. Keep in mind the each method has its advantages and disadvantages.

Narrative – in this form of recording the researcher records a description of the interaction in his/her own words. Usually, he/she makes brief notes while observing the interaction and soon after the observation makes detailed notes in narrative form. In addition, some researchers may interpret the interaction and draw conclusions from it. The biggest advantage of narrative recording it that it provides a deeper insight into the interaction. However, a disadvantage is that an observer may be biased in his/her observation and, therefore, the interpretations and conclusions drawn from the observation may also be biased. Also, if a researcher’s attention is on observing, he/she might forget to record an important piece of interaction and, obviously, in the process of recording, part of the interaction may be missed. Hence, there is always the possibility of incomplete recording and/or observation> In addition, with different observers the comparability of narrative recording can be a problem.

Scales – at times some observers may prefer to develop a scale in order to rate various aspects of the interaction or phenomenon. The recording is done on a scale developed by the observer/researcher. A scale may be one, two or three directional, depending upon the purpose of the observation.

Schedules Sent Through Enumerators - Methods of Primary Data Collection

Another method of data collection is sending schedules through the enumerators or interviewers. The enumerators contact the informants, get replies to the questions contained in a schedule and fill them in their own handwriting in the questionnaire form. There is difference between questionnaire and schedule. Questionnaire refers to a device for securing answers to questions by using a form which the respondent fills in him self, whereas schedule is the name usually applied to a set of questions which are asked in a face-to face situation with another person. This method is free from most of the limitations of the mailed questionnaire method.
Merits:
The main merits or advantages of this method are listed below:
1. It can be adopted in those cases where informants are illiterate.
2. There is very little scope of non-response as the enumerators go personally to obtain the information.
3. The information received is more reliable as the accuracy of statements can be checked by supplementary questions wherever necessary.
This method too like others is not free from defects or limitations. The main limitations are listed below:
Demerits:
1. In comparison to other methods of collecting primary data, this method is quite costly as enumerators are generally paid persons.
2. The success of the method depends largely upon the training imparted to the enumerators.
3. Interviewing is a very skilled work and it requires experience and training. Many statisticians have the tendency to neglect this extremely important part of the data collecting process and this result in bad interviews. Without good interviewing most of the information collected may be of doubtful value.
4. Interviewing is not only a skilled work but it also requires a great degree of politeness and thus the way the enumerators conduct the interview would affect the data collected. When questions are asked by a number of different interviewers, it is possible that variations in the personalities of the interviewers will cause variation in the answers obtained. This variation will not be obvious. Hence, every effort must be made to remove as much of variation as possible due to different interviewers.

Mailed Questionnaire Method - Methods of Primary Data Collection

Under this method, a list of questions pertaining to the survey which is known as ‘Questionnaire’ is prepared and sent to the various informants by post. Sometimes the researcher himself too contacts the respondents and gets the responses related to various questions in the questionnaire.

The questionnaire contains questions and provides space for answers. A request is made to the informants through a covering letter to fill up the questionnaire and send it back within a specified time.

The questionnaire studies can be classified on the basis of:
a. The degree to which the questionnaire is formalized or structured.
b. The disguise or lack of disguise of the questionnaire and
c. The communication method used.

When no formal questionnaire is used, interviewers adapt their questioning to each interview as it progresses. They might even try to elicit responses by indirect methods, such as showing pictures on which the respondent comments. When a researcher follows a prescribed sequence of questions, it is referred to as structured study. On the other hand, when no prescribed sequence of questions exists, the study is non-structured.

When questionnaires are constructed in such a way that the objective is clear to the respondents then these questionnaires are known as non- disguised; on the other hand, when the objective is not clear, the questionnaire is a disguised one. On the basis of these two classifications, four types of studies can be distinguished:
1. Non-disguised structured,
2. Non-disguised non-structured,
3. Disguised structured and
4. Disguised non-structured.
There are certain merits and demerits of this method of data collection which are discussed below:

Merits:
1. Questionnaire method of data collection can be easily adopted where the field of investigation is very vast and the informants are spread over a wide geographical area.
2. This method is relatively cheap and expeditious provided the informants respond in time.
3. This method has proved to be superior when compared to other methods like personal interviews or telephone method. This is because when questions pertaining to personal nature or the ones requiring reaction by the family are put forth to the informants, there is a chance for them to be embarrassed in answering them.

Demerits:
1. This method can be adopted only where the informants are literates so that they can understand written questions and lend the answers in writing.

2. It involves some uncertainty about the response. Co-operation on the part of informants may be difficult to presume.
3. The information provided by the informants may not be correct and it may be difficult to verify the accuracy.
However, by following the guidelines given below, this method can be made more effective:
The questionnaires should be made in such a manner that they do not become an undue burden on the respondents; otherwise the respondents may not return them back.
a. Prepaid postage stamp should be affixed
b. The sample should be large
c. It should be adopted in such enquiries where it is expected that the respondents would return the questionnaire because of their own interest in the enquiry
d. It should be preferred in such enquiries where there could be a legal compulsion to provide the information.

Information from Correspondents - Methods of Primary Data Collection

The investigator appoints local agents or correspondents in different places to collect information under this method. These correspondents collect and transmit the information to the central office where data are processed. This method is generally adopted by news paper agencies.

Correspondents who are posted at different places supply information relating to such events as accidents, riots, strikes, etc., to the head office. The correspondents are generally paid staff or sometimes they may be honorary correspondents also. This method is also adopted generally by the government departments in such cases where regular information is to be collected from a wide area. For example, in the construction of a wholesale price index numbers regular information is obtained from correspondents appointed in different areas. The biggest advantage of this method is that, it is cheap and appropriate for extensive investigation. But a word of caution is that it may not always ensure accurate results because of the personal prejudice and bias of the correspondents.

As stated earlier, this method is suitable and adopted in those cases where the information is to be obtained at regular intervals from a wide area.

Indirect Oral Interviews - Methods of Primary Data Collection

Under this method of data collection, the investigator contacts third parties generally called ‘witnesses’ who are capable of supplying necessary information. This method is generally adopted when the information to be obtained is of a complex nature and informants are not inclined to respond if approached directly. For example, when the researcher is trying to obtain data on bribe or the habit of taking liquor, there is high probability that the bribed / addicted person will not provide the desired data and hence will disturb the whole research process. In this situation taking the help of such persons or agencies or the neighbours who know them well becomes necessary. Since these people know the person well, they can provide the desired data. Enquiry Committees and Commissions appointed by the Government generally adopt this method to get people’s views and all possible details of the facts related to the enquiry.

Though this method is very popular, its correctness depends upon a number of factors such as
1. The person or persons or agency whose help is solicited must be of proven integrity; otherwise any bias or prejudice on their part will not bring out the correct information and the whole process of research will become useless.
2. The ability of the interviewers to draw information from witnesses by means of appropriate questions and cross-examination.
3. It might happen that because of bribery, nepotism or certain other reasons those who are collecting the information give it such a twist that correct conclusions are not arrived at.

Therefore, for the success of this method it is necessary that the evidence of one person alone is not relied upon. Views from other persons and related agencies should also be ascertained to find the real position. Utmost care must be exercised in the selection of these persons because it is on their views that the final conclusions are reached. 

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Direct Personal Interviews - Methods of Primary Data Collection

A face to face contact is made with the informants (persons from whom the information is to be obtained) under this method of collecting data.

The interviewer asks them questions pertaining to the survey and collects the desired information. Thus, if a person wants to collect data about the working conditions of the workers of the BHEL, Trichy, he would go to the factory, contact the workers and obtain the desired information. The information collected in this manner is first hand and also original in character.

There are many merits and demerits of this method, which are discussed as under:

Merits:

1. Most often respondents are happy to pass on the information required from them when contacted personally and thus response is encouraging.

2. The information collected through this method is normally more accurate because interviewer can clear doubts of the informants about certain questions and thus obtain correct information. In case the interviewer apprehends that the informant is not giving accurate information, he may cross-examine him and thereby try to obtain the information.

3. This method also provides the scope for getting supplementary information from the informant, because while interviewing it is possible to ask some supplementary questions which may be of greater use later.

4. There might be some questions which the interviewer would find difficult to ask directly, but with some tactfulness, he can mingle such questions with others and get the desired information. He can twist the questions keeping in mind the informant’s reaction. Precisely, a delicate situation can usually he handled more effectively by a personal interview than by other survey techniques.

5. The interviewer can adjust the language according to the status and educational level of the person interviewed, and thereby can avoid inconvenience and misinterpretation on the part of the informant.

Demerits:

1. This method can prove to be expensive if the number of informants is large and the area is widely spread.

2. There is a greater chance of personal bias and prejudice under this method as compared to other methods.

3. The interviewers have to be thoroughly trained and experienced; otherwise they may not be able to obtain the desired information. Untrained or poorly trained interviewers may spoil the entire work.

4. This method is more time taking as compared to others. This is because interviews can be held only at the convenience of the informants. Thus, if information is to be obtained from the working members of households, interviews will have to be held in the evening or on week end. Even during evening only an hour or two can be used for interviews and hence, the work may have to be continued for a long time, or a large number of people may have to be employed which may involve huge expenses.

Though there are some demerits in this method still we cannot say that it is not useful. The matter of fact is that this method is suitable for intensive rather than extensive field surveys. Hence, it should be used only in those cases where intensive study of a limited field is desired.
In the present time of extreme advancement in the communication system, the investigator instead of going personally and conducting a face to face interview may also obtain information over telephone. A good number of surveys are being conducted every day by newspapers and television channels by sending the reply either by e-mail or SMS. This method has become very popular nowadays as it is less expensive and the response is extremely quick. But this method suffers from some serious defects, such as (a) those who own a phone or a television only can be approached by this method, (b) only few questions can be asked over phone or through television, (c) the respondents may give a vague and reckless answers because answers on phone or through SMS would have to be very short.

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Methods of Collecting Primary Data

Primary data refers to original data that has been collected from the original source first hand. Data collected this way is called primary data. It may be obtained by applying any of the following methods:

1. Observation.     
2. Direct Personal Interviews.       
3. Indirect Oral Interviews.      
4. Information from Correspondents.      
5. Mailed Questionnaire Methods.      

6. Schedule Sent Through Enumerators.

Important properties of the Normal distribution

The normal distribution was first described by Abraham Demoivre (1667-1754) as the limiting form of binomial model in 1733. Normal distribution was rediscovered by Gauss in 1809 and by Laplace in 1812. Both Gauss and Laplace were led to the distribution by their work on the theory of errors of observations arising in physical measuring processes particularly in astronomy. Here I will show you some important properties of Normal distribution

1. The normal curve is “bell shaped” and symmetrical in nature. The distribution of the frequencies on either side of the maximum ordinate of the curve is similar with each other.

2. The maximum ordinate of the normal curve is at. Hence the mean, median and mode of the normal distribution coincide.

3. It ranges between to

4. The value of the maximum ordinate is

5. The points where the curve change from convex to concave or vice versa is at

6. The first and third quartiles are equidistant from median.

7. The area under the normal curve distribution are:

a. covers 68.27% area

b. covers 95.45% area

c. covers 99.73% area

8. When μ = 0 and σ = 1, then the normal distribution will be a standard normal curve. The probability function of standard normal curve is

The following table gives the area under the normal probability curve for some important value of Z.

Distance from the mean ordinate in Terms of ± σ	Area under the curve
Z = ± 0.6745	0.50
Z = ± 1.0	0.6826
Z = ± 1.96	0.95
Z = ± 2.00	0.9544
Z = ± 2.58	0.99
Z = ± 3.0	0.9973

9. All odd moments are equal to zero.

10. Skewness = 0 and Kurtosis = 3 in normal distribution.

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Measurement Scales–Nominal, Ordinal, Interval and Ratio

Measurement scales are classified popularly under four categories:

1. Nominal,
2. Ordinal,
3. Interval,
4. Ratio.

Let’s discuss in brief about these measurement scales before going on for some technical details. If you want to test Network of 50 smart phone users. Let’s begins by evaluating each on 4G – Non 4G data; this is a nominal measurement. Then the users ranks the Quality from best to worst; this is an ordinal measurement. Next, the mobile users uses a 5 or 7 point scale that has equal distance between points to rate the 4G network with regard to some criterion (e.g., data speed, Coverage, cost and etc.., ); this is an interval measurement. Finally, the user considers another network dimensions (eg.3G) and assigns 100 points among the 50 smart phone users; this is a ratio measurement. The characteristics of these measurement scales are summarized in below table.

Note: Likert scale variables falls under Ordinal and/or Interval scale depends on the nature of the measurement.

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What are type I and type II errors?

Image by Clker Free Vector Images via Pixabay

Testing  of hypothesis is widespread not only in statistics, but also in the natural and social sciences. When we do a hypothesis test, two types of errors are possible these errors are termed as experimental errors. They are Type-I or Type-II errors. It is important to understand both these effects in order to  manage error and report it, for the right interpretation of conclusion from a experiment.

Decision made	Null Hypothesis is actually
	True	False
Reject Null	Type I error	Correct rejection
Fail to reject Null	Correct decision	Type II error

Type I errors occurs when we reject a true null hypothesis - 

The Type I error occurs when a the null hypothesis (H0) is rejected in favor of the research hypothesis (H1), when in reality the 'null' is correct. Type I errors are equivalent to false positives. For example, suppose there is a test that is used to detect a disease in a person. If a Type I error occurs in the test, it means that the test will say the person is suffering from that disease even though he is healthy. Type I errors can be controlled. The value of alpha, which is related to the level of significance that we selected has a direct bearing on type I errors. Alpha is the maximum probability that we have a type I error. For a 95% confidence level, the value of alpha is 0.05. This means that there is a 5% probability that we will reject a true null hypothesis. 

Type II errors happen when we fail to reject a false null hypothesis -

Type II error occurs when we do not reject a null hypothesis that is false. It is equivalent to false negatives.  From the above said example of a medical test for a disease, if a Type-II error occurs, then it means that the test will not detect the disease in the person even though he is actually suffering from it.The probability of a type II error is given by the Greek letter beta. This number is related to the power or sensitivity of the hypothesis test, denoted by 1 – beta.

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Dependent, Independent variables and their different names

In research, variables of different nature are used. Two major variables used in such case is Independent and Dependent variables.

Independent variables:

A variable (often denoted by x ) whose variation does not depend on that of another is called as Independent variables. Other names for Independent variables are exogenous variable, predictor variable, regressor, controlled variable, manipulated variable, explanatory variable, exposure variable (in reliability theory), risk factor (in medical statistics), feature (in machine learning and pattern recognition) or an "input variable."

Dependent variables:

A variable (often denoted by y ) whose value depends on that of another is known as Dependent variables. Other names for Dependent variables are Endogenous variable (similar not exactly the same as dependent variables), response variable, regressand, predicted variable, measured variable, explained variable, experimental variable, responding variable, outcome variable and output variable.