**Quota Sampling**

Quota sampling is a non-probability sampling technique used in statistics and economics. It is a method of selecting a sample where the researcher identifies specific quotas or characteristics that need to be represented in the sample. Quotas are predetermined proportions or percentages that reflect the distribution of certain characteristics in the population under study.

**Procedure of Quota Sampling:**

1. Identification of Quotas: The researcher identifies the specific quotas or characteristics that need to be represented in the sample. For example, if the population is divided into different age groups, the researcher may set quotas for each age group.

2. Selection of Participants: The researcher then selects participants who meet the required quotas. The selection is typically done by convenience or judgment sampling, where the researcher chooses individuals who are readily available and meet the desired quota.

3. Filling the Quotas: The researcher continues to select participants until the quotas for each characteristic are filled. This may involve adjusting the sample size for each quota to ensure the desired representation.

**Advantages of Quota Sampling:**

1. Cost-effective: Quota sampling can be more cost-effective compared to other sampling methods as it does not require a complete list of the population or complex randomization procedures.

2. Quick and Convenient: Quota sampling allows researchers to quickly gather data as they can conveniently select participants based on specific quotas.

3. Representation: Quota sampling ensures that the sample represents the desired characteristics in the population, making it useful when studying specific subgroups.

**Limitations of Quota Sampling:**

1. Non-Probability Sampling: Quota sampling is a non-probability sampling method, which means the selection of participants is not based on randomization. This limits the generalizability of the findings to the entire population.

2. Sampling Bias: The researcher's judgment plays a crucial role in selecting participants, which can introduce sampling bias if the researcher's choices are not representative of the population.

3. Lack of Precision: Quota sampling does not provide a precise estimate of the population parameters as it does not follow randomization procedures.

**Mixed Sampling**

Mixed sampling, also known as mixed-mode sampling, is a sampling technique that combines different sampling methods within a single study. It involves using multiple modes of data collection, such as face-to-face interviews, telephone interviews, online surveys, or mailed questionnaires, to gather information from the sample.

**Procedure of Mixed Sampling:**

1. Selection of Sampling Methods: The researcher determines the appropriate sampling methods based on the research objectives, available resources, and the characteristics of the target population.

2. Sample Design: The researcher designs the sample by selecting participants using different sampling methods. For example, a mixed sample may include participants who were randomly selected for face-to-face interviews, while others were recruited through an online survey.

3. Data Collection: Data is collected using the selected methods, which may involve using different questionnaires or interview protocols depending on the mode of data collection.

4. Integration of Data: The data collected from different modes are combined and analyzed as a single dataset. This allows for comparisons and investigation of potential mode effects.

**Advantages of Mixed Sampling:**

1. Methodological Flexibility: Mixed sampling allows researchers to utilize multiple sampling methods, enabling them to reach a broader range of participants and collect data in various ways.

2. Data Validation: By collecting data through different modes, researchers can validate the findings and identify potential biases or mode effects.

3. Increased Response Rates

In frist the survey is conducted by any group of people but in second the the survey is conducted different people