Mar. 15: Surveying
Introduction Assignment

Due Date: March 29th, 9:30am

Watch: Crash Course Sampling and Survey
Guided Summary:

1. Why is it important to have questions that actually measure what you want to know?
   Adequate information about physical activity habits is essential for surveillance, implementing, and evaluating public health initiatives in this area. Previous studies have shown that question order and differences in wording result in systematic differences in people’s responses to questionnaires; however, this has never been shown for physical activity questions. The analysis shows that questionnaire design choices can either help or hurt the quality of data collected by interviewers. Furthermore, the behaviors of experienced and inexperienced interviewers are affected in similar ways. In other words, interviewing experience does not compensate for format deficits in the design of survey instruments.
2. What is a leading question? Why are they problematic?
   A leading question is a type of question that prompts a respondent towards providing an already-determined answer. This type of question is suggestive as it is framed in such a way that it implies or points to its answer(s). Leading questions result in biased or false answers, as respondents are prone to simply mimic the words of the interviewer. How we word these questions may affect the user response and also may give them extra clues about the interface. We may end up with inaccurate feedback that may or may not truly reflect the user’s experience
3. What is the ideal survey sample? Why is it difficult to do in real life?
   Most statisticians agree that the minimum sample size to get any kind of meaningful result is 100. If your population is less than 100 then you really need to survey all of them.A good maximum sample size is usually around 10% of the population, as long as this does not exceed 1000. Data on sub-populations (such as a particular ethnic group) may be too unreliable to be useful.
   Data for small geographical areas also may be too unreliable to be useful.
   (Because of the above reasons) detailed cross-tabulations may not be practical.
   Estimates are subject to sampling error which arises as the estimates are calculated from a part (sample) of the population.
   May have difficulty communicating the precision (accuracy) of the estimates to users.
4. What is underrepresentation bias?
   It is a method of selecting respondents from some groups so that they make up a larger share of a sample than they actually do the population.
5. What is stratified random sampling?
   Stratified random sampling is a method of sampling that involves the division of a population into smaller sub-groups known as strata. In stratified random sampling, or stratification, the strata are formed based on members’ shared attributes or characteristics such as income or educational attainment
6. What is cluster sampling?
   In cluster sampling, researchers divide a population into smaller groups known as clusters. They then randomly select among these clusters to form a sample.
   Cluster sampling is a method of probability sampling that is often used to study large populations, particularly those that are widely geographically dispersed. Researchers usually use pre-existing units such as schools or cities as their clusters.
7. What is snowball sampling?
   Snowball sampling or chain-referral sampling is defined as a non-probability sampling technique in which the samples have traits that are rare to find. This is a sampling technique, in which existing subjects provide referrals to recruit samples required for a research study.
8. Why is the census so great for research?
   The main advantage of a census is that the data for small areas may be available, assuming satisfactory response rates are achieved. Data for sub-populations may be available, assuming satisfactory response rates are achieved.

Watch: Survey Methodology
Guided Summary:

1. How does he define survey research methods?
   He defines it as A survey is a research method used for collecting data from a predefined group of respondents to gain information and insights into various topics of interest. They can have multiple purposes, and researchers can conduct it in many ways depending on the methodology chosen and the study’s goal.
2. Compare and contrast open-ended and closed questions?
   Questions can be broadly categorized into two categories; open questions and closed questions. These are also known as open ended and closed ended questions. The main difference between open and closed questions is that open questions are likely to receive long answers whereas closed questions are likely to receive short answers.
   An open-ended question is an open response-style of question, where participants can answer in as much or as little text as they choose. Open-ended questions allow participants to respond to your question based on their own experience, opinions, or level of understanding, which often allows for answers to be longer and more detailed. Open-ended questions are more common in qualitative research designs. Common formats for structuring open-ended questions include asking ‘how’, ‘why’ or ‘what’.
   A closed question is one where the possible answers are restricted to a select number of choices that were pre-determined by the researchers. Closed questions allow for more focused responses, because the range of options to select from are limited to specific factors that the researcher is interested in. Closed questions are more common in quantitative research designs, and can occur in dichotomous or multiple-choice-formats, such as ‘Yes/No’ or ‘Please select…’ questions.
3. What does confidence level mean?
   The confidence level indicates the probability, with which the estimation of the location of a statistical parameter (e.g. an arithmetic mean) in a sample survey is also true for the population.
4. What is the difference between probability and non probability sampling?
   Probability sampling is a sampling technique, in which the subjects of the population get an equal opportunity to be selected as a representative sample. Non-probability sampling is a method of sampling wherein, it is not known that which individual from the population will be selected as a sample.
   The basis of probability sampling is randomization or chance, so it is also known as Random sampling. On the contrary, in non-probability sampling randomization technique is not applied for selecting a sample. Hence it is considered as Non-random sampling.
5. What needs to be considered when deciding which one to do?
   As the subjects are selected randomly by the researcher in probability sampling, so the extent to which it represents the whole population is higher as compared to the non-probability sampling. That is why extrapolation of results to the entire population is possible in the probability sampling but not in non-probability sampling.