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The Importance of Sampling and Hypothesis Testing

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1. Why is sampling strategy important? Please provide one or two examples from your work or past experience?

2. What is the difference between the population of the study and the sampling frame? Provide an example to support your response.

3. Non-probability (purposive, quota) and probability (simply random, cluster) are two very different types of sampling designs. What are the pros/cons of each design? When and why would you choose one from the other? Provide an example to support your response.

4. Why is it important to create a hypothesis before conducting research?

5. What are the differences between directional and non-directional hypothesis? Provide an example of each case.

6. What is the difference between a null hypothesis and an alternative hypothesis? Provide an example to support your response.

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Solution Summary

This solution discusses the concepts of sampling and the purpose of hypothesis when conducting research.

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1. Why is sampling strategy important? Please provide one or two examples from your work or past experience?

Sampling strategy is important as it ensures that the right mix of respondents is selected that provides correct insights about the population can be inferred. For example: A soft drink marketer interested in understanding the preferences of consumers may select random sampling technique as soft drink is a product consumed by all types of customers. However, a premium real estate agent would select a stratified clustering technique based on income to understand preferences of customers as the customers are very few with high income levels.

2. What is the difference between the population of the study and the sampling frame? Provide an example to support your response.

Population represents the actual count of people that eligible to participate in a study under consideration. E.g.: An insurance services firm's population is all the individuals with income greater than > 10000 USD.

The listing of the accessible population drawn from the population is the sampling frame. E.g.: An insurance provider interested in targeting customers may get the list of customers from a telephone directory (a sampling frame).

3. Non-probability (purposive, quota) and probability (simply random, cluster) are two very different types of ...

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