1. What is the difference between experimental and quasi-experimental designs? Give an example of each in

nursing research.

- Experimental designs are those that involve random assignment of participants to different groups or

conditions, and manipulation of one or more independent variables. Quasi-experimental designs are those

that lack random assignment, but still have some form of comparison or control group. For example, an

experimental design in nursing research could be a randomized controlled trial that compares the effects of

two different types of wound dressing on healing outcomes. A quasi-experimental design could be a pretestposttest design that compares the changes in blood pressure of patients who receive a nurse-led intervention

versus those who receive usual care.

2. What are the advantages and disadvantages of using surveys as a data collection method in quantitative

research? Name two types of surveys and explain how they differ.

- Surveys are a data collection method that involve asking participants a series of questions, either verbally

or in written form, to obtain information about their characteristics, attitudes, opinions, behaviors, or

experiences. Surveys can be either cross-sectional or longitudinal. Cross-sectional surveys collect data from

participants at one point in time, while longitudinal surveys collect data from the same participants over

multiple time points. The advantages of using surveys are that they can reach a large and diverse sample,

they are relatively easy and inexpensive to administer, and they can provide standardized and comparable

data. The disadvantages are that they may have low response rates, they may suffer from social desirability

bias or recall bias, and they may not capture the complexity or depth of the phenomena under study.

3. What is the purpose of sampling in quantitative research? What are the criteria for selecting a

representative sample? Name two types of sampling techniques and explain how they differ.

- Sampling is the process of selecting a subset of individuals from a population to participate in a research

study. The purpose of sampling is to obtain a sample that is representative of the population, meaning that it

reflects the characteristics and diversity of the population as closely as possible. The criteria for selecting a

representative sample are: (a) the sample size should be large enough to ensure adequate statistical power

and precision; (b) the sampling frame should include all eligible members of the population; (c) the

sampling method should be appropriate for the research question and design; and (d) the sampling procedure

should be transparent and ethical. Two types of sampling techniques are probability sampling and nonprobability sampling. Probability sampling is when each member of the population has a known and equal

chance of being selected for the sample, such as random sampling or stratified sampling. Non-probability

sampling is when the selection of participants is based on convenience, availability, or other criteria, such as

purposive sampling or snowball sampling.

4. What are the main types of quantitative data analysis methods? What are the factors that influence the

choice of data analysis method?

- The main types of quantitative data analysis methods are descriptive statistics, inferential statistics, and

multivariate statistics. Descriptive statistics are used to summarize and display the characteristics and

distribution of the data, such as mean, median, mode, standard deviation, frequency, percentage, histogram,