Assign codes to the data. Identify recurring themes. What is a Likert scale? Are Likert scales ordinal or interval scales? What is the difference between a control group and an experimental group? What is blinding? What is the difference between single-blind, double-blind and triple-blind studies? In a single-blind study , only the participants are blinded. In a double-blind study , both participants and experimenters are blinded. In a triple-blind study , the assignment is hidden not only from participants and experimenters, but also from the researchers analyzing the data.
Why is blinding important? What is a quasi-experiment? When should I use a quasi-experimental design? What is simple random sampling? What is an example of simple random sampling? When should I use simple random sampling? However, it can sometimes be impractical and expensive to implement, depending on the size of the population to be studied, If you have a list of every member of the population and the ability to reach whichever members are selected, you can use simple random sampling.
What is cluster sampling? The clusters should ideally each be mini-representations of the population as a whole. What are the types of cluster sampling? In single-stage sampling , you collect data from every unit within the selected clusters.
In double-stage sampling , you select a random sample of units from within the clusters. In multi-stage sampling , you repeat the procedure of randomly sampling elements from within the clusters until you have reached a manageable sample. What are some advantages and disadvantages of cluster sampling? What is stratified sampling? When should I use stratified sampling? Can I stratify by multiple characteristics at once?
What is systematic sampling? How do I perform systematic sampling? There are three key steps in systematic sampling : Define and list your population , ensuring that it is not ordered in a cyclical or periodic order.
Decide on your sample size and calculate your interval, k , by dividing your population by your target sample size. Choose every k th member of the population as your sample. How can you tell if something is a mediator? Why should you include mediators and moderators in a study?
What is a control variable? Why are control variables important? What is random assignment? How do you randomly assign participants to groups?
When do you use random assignment? Can you use a between- and within-subjects design in the same study? What are the pros and cons of a between-subjects design? Advantages: Prevents carryover effects of learning and fatigue. Shorter study duration. Disadvantages: Needs larger samples for high power. Uses more resources to recruit participants, administer sessions, cover costs, etc.
Individual differences may be an alternative explanation for results. What are the pros and cons of a within-subjects design? Advantages: Only requires small samples, Statistically powerful, Removes the effects of individual differences on the outcomes. Disadvantages: Internal validity threats reduce the likelihood of establishing a direct relationship between variables, Time-related effects, such as growth, can influence the outcomes, Carryover effects mean that the specific order of different treatments affect the outcomes.
What is a factorial design? What are the types of extraneous variables? Experimenter effects : unintentional actions by researchers that influence study outcomes. What are the requirements for a controlled experiment? Controlled experiments require: A control group that receives a standard treatment, a fake treatment, or no treatment. Random assignment of participants to ensure the groups are equivalent.
What are explanatory and response variables? The difference between explanatory and response variables is simple: An explanatory variable is the expected cause, and it explains the results.
A response variable is the expected effect, and it responds to other variables. How do explanatory variables differ from independent variables? How do you plot explanatory and response variables on a graph? If you have quantitative variables , use a scatterplot or a line graph. If your response variable is categorical, use a scatterplot or a line graph. If your explanatory variable is categorical, use a bar graph.
Is random error or systematic error worse? How do you avoid measurement errors? What is a correlation? A positive correlation means that both variables change in the same direction. A negative correlation means that the variables change in opposite directions. What is correlational research? What is a correlation coefficient? How many variables are in a correlation?
In an experimental design , you manipulate an independent variable and measure its effect on a dependent variable. In a correlational design , you measure variables without manipulating any of them. How do you order a questionnaire? How do you administer questionnaires? What is a research design? What do I need to include in my research design? Why is research design important? What are the main types of research design? Quantitative research designs can be divided into two main categories: Correlational and descriptive designs are used to investigate characteristics, averages, trends, and associations between variables.
Experimental and quasi-experimental designs are used to test causal relationships. What are the assumptions of the Pearson correlation coefficient? What do the sign and value of the correlation coefficient tell you? Is the correlation coefficient the same as the slope of the line? What is multistage sampling? What is triangulation in research? What are the main types of mixed methods research designs? These are four of the most common mixed methods designs : Convergent parallel: Quantitative and qualitative data are collected at the same time and analyzed separately.
After both analyses are complete, compare your results to draw overall conclusions. Embedded: Quantitative and qualitative data are collected at the same time, but within a larger quantitative or qualitative design. One type of data is secondary to the other. Explanatory sequential: Quantitative data is collected and analyzed first, followed by qualitative data.
You can use this design if you think your qualitative data will explain and contextualize your quantitative findings. Exploratory sequential: Qualitative data is collected and analyzed first, followed by quantitative data.
You can use this design if you think the quantitative data will confirm or validate your qualitative findings. What are the pros and cons of multistage sampling? Is multistage sampling a probability sampling method? What are ethical considerations in research? Why do research ethics matter? What is research misconduct? Ask our team Want to contact us directly? Email info scribbr. How does Scribbr help students graduate? What type of documents does Scribbr proofread?
I might have sneak in citations to them. Experimental Design for Biologists: 1. System Validation. Video minutes. Share Buffer 2. David Crotty davidacrotty. View All Posts by David Crotty. I believe that IRB approval is discussed in the video on system validation. Comments are closed. Select personalised ads. Apply market research to generate audience insights. Measure content performance. Develop and improve products. List of Partners vendors.
Share Flipboard Email. Anne Marie Helmenstine, Ph. Chemistry Expert. Helmenstine holds a Ph. She has taught science courses at the high school, college, and graduate levels. Facebook Facebook Twitter Twitter. Updated December 11, Controlled Experiment A controlled experiment is simply an experiment in which all factors are held constant except for one: the independent variable.
A common type of controlled experiment compares a control group against an experimental group. All variables are identical between the two groups except for the factor being tested. The advantage of a controlled experiment is that it is easier to eliminate uncertainty about the significance of the results.
Most experiments have more than one controlled variable. For example, if you are testing a new cold medicine, the controlled variable might be that the patient has a cold and a fever. If you tested someone without those two controls, your results would be inaccurate and possibly misleading. These are the variables being tested, such as the new cold medication. Only one independent variable is typically tested at a time.
In simple terms, the independent variable is the potential cause of an observed effect. This is the variable most likely to change from one experiment to the next, such as changing the amount of medicine given when trying to determine the correct dosage. Related: 10 Types of Variables in Research and Statistics. Developing a control in an experiment depends on the independent variables being tested.
When testing new medication, the control group doesn't receive it. If testing the effect of sunlight on the growth of a flower, the control group of flowers might be grown inside and away from the sun.
Here are the steps to take when performing an experiment with a control group:. Your experiment should begin with a question that needs an answer. Perhaps you've noticed an effect and are curious about its cause. This is your hypothesis, the integral starting point for figuring out what your control is going to be.
Related: Hypothesis: Definition and Examples. Once you've settled on the question you hope to answer, begin making observations on the topic you hope to study. If you're a medical professional trying to determine what effects a particular exercise regimen has on arthritic patients, note any patients doing similar exercises. Record any observations you make about their type of arthritis, what their regimen is and what effects it seems to have.
This helps you decide which independent variables you wish to test and which groups are most likely to display the effects these variables may have. With a question that needs answering and some observation-based data, choose a more specific hypothesis.
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