Risers Institute of Advance Studies

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TYPE OF INSTRUMENTS
Test :
A test is measuring the knowledge, skill, feeling, intelligence. Or aptitude of an individual or group.Type of test
Achievement test
Aptitude test

Questionnaire:
It is a data gathering instrument though which respondent answer questions or respond to statements in writing. Type of Questionnaire.
Close ended form
Open ended form

Interviews:
Interviews is a technique of collecting information orally form others in a face to face situation.Type of interviews.
Individual interview
Structured interview
Group interview
Unstructured interview
Panel interview

Observation:
Observation seek to ascertain what people think and do by watching them n action as they express themselves in various situation and activities.

Rating scale
Rating scale involves qualitative description do a limited number of aspects of a thing.

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What is Research Instruments?
A research instrument is a tool used to collect, measure, and analyze data related to your subject. Research instruments can be tests, surveys, scales, questionnaires, or even checklists.To assure the strength of your study, it is important to use previously validated instruments. It applies to both qualitative and quantitative approaches. It can produce quantitative and/or qualitative data.

Non-probability sampling methods.
In a non-probability sample, individuals are selected based on non-random criteria, and not every individual has a chance of being included. This type of sample is easier and cheaper to access, but you can’t use it to make valid statistical inferences about the whole population. Non-probability sampling techniques are often appropriate for exploratory and qualitative research. In these types of research, the aim is not to test a hypothesis about a broad population, but to develop an initial understanding of a small or under-researched population.

1. Convenience sampling
A convenience sample simply includes the individuals who happen to be most accessible to the researcher. This is an easy and inexpensive way to gather initial data, but there is no way to tell if the sample is representative of the population, so it can’t produce generalizable results.

2. Judgmental sampling
This type of sampling involves the researcher using their judgement to select a sample that is most useful to the purposes of the research. It is often used in qualitative research, where the researcher wants to gain detailed knowledge about a specific phenomenon rather than make statistical inferences.

3. Quota sampling
Quota sampling means to take a very tailored sample that’s in proportion to some characteristic or trait of a population. For example, you could divide a population by the state they live in, income or education level, or s*x. The population is divided into groups (also called strata) and samples are taken from each group to meet a quota.

4. Snowball sampling
If the population is hard to access, snowball sampling can be used to recruit participants via other participants. The number of people you have access to “snowballs” as you get in contact with more people.

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Probability sampling methods
Probability sampling means that every member of the population has a chance of being selected. If you want to produce results that are representative of the whole population, you need to use a probability sampling technique.

There are four main types of probability sample
1. Simple random sampling
In a simple random sample, every member of the population has an equal chance of being selected. Your sampling frame should include the whole population.

2. Systematic sampling
Systematic sampling is similar to simple random sampling, but it is usually slightly easier to conduct. Every member of the population is listed with a number, but instead of randomly generating numbers, individuals are chosen at regular intervals.

3. Stratified sampling
This sampling method is appropriate when the population has mixed characteristics, and you want to ensure that every characteristic is proportionally represented in the sample.
You divide the population into subgroups (called strata) based on the relevant characteristic (e.g. gender, age range, income bracket, job role).

4. Cluster sampling
Cluster sampling also involves dividing the population into subgroups, but each subgroup should have similar characteristics to the whole sample. Instead of sampling individuals from each subgroup, you randomly select entire subgroups.

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What is Sampling?
POPULATION
The population is the entire group that you want to draw conclusions about.

SAMPLE
The sample is the specific group of individuals that you will collect data from.

SAMPLING
The sampling is the act, a process of selecting a suitable sample or a representative part of a population for the purpose of determining characteristics of the whole population.

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METHOD OF DATA COLLECTION

Primary Data
When we obtain data directly from individuals, objects or processes, we refer to it as primary data. Quantitative or qualitative data can be collected using this approach. Such data is usually collected solely for the research problem to you will study. Primary data has several advantages. First, we tailor it to our specific research question, so there are no customization needed to make the data usable. Second, primary data is reliable because you control how the data is collected and can monitor its quality. Third, by collecting primary data, you spend your resources in collecting only required data. Finally, primary data is proprietary, so you enjoy advantages over those who cannot access the data.
Despite its advantages, primary data also has disadvantages of which you need to be aware. The first problem with primary data is that it is costlier to acquire as compared to secondary data. Obtaining primary data also requires more time as compared to gathering secondary data.

Secondary Data
When you collect data after another researcher or agency that initially gathered it makes it available, you are gathering secondary data. Examples of secondary data are census data published by the US Census Bureau, stock prices data published by CNN and salaries data published by the Bureau of Labour Statistics.
One advantage to using secondary data is that it will save you time and money, although some data sets require you to pay for access. A second advantage is the relative ease with which you can obtain it. You can easily access secondary data from publications, government agencies, data aggregation websites and blogs. A third advantage is that it eliminates effort duplication since you can identify existing data that matches your needs instead of gather new data.