#1
What is the purpose of a control group in an experiment?
To ensure that the experiment is conducted ethically
To provide a baseline for comparison with the treatment group
To make the experiment more complex
To increase the sample size
#2
What is the difference between qualitative and quantitative data?
Qualitative data can be measured numerically, while quantitative data describes qualities.
Qualitative data describes qualities or characteristics, while quantitative data can be measured numerically.
There is no difference between qualitative and quantitative data.
Qualitative data is more reliable than quantitative data.
#3
What is the purpose of a placebo in a clinical trial?
To ensure that participants are aware of the treatment they are receiving
To serve as a standard of comparison for the treatment being studied
To guarantee that all participants receive an active treatment
To increase the effectiveness of the treatment
#4
What is the role of a hypothesis in experimental design?
To ensure that the experiment produces statistically significant results
To provide a tentative explanation for observed phenomena
To prove the null hypothesis wrong
To limit the scope of the experiment
#5
What is the purpose of random sampling in research?
To ensure that every member of the population has an equal chance of being selected
To guarantee that the sample size is large enough
To increase the representativeness of the sample
To reduce the variability of the data
#6
In experimental design, what is the difference between an independent variable and a dependent variable?
An independent variable is manipulated by the researcher, while a dependent variable is observed and measured for changes.
An independent variable is observed and measured for changes, while a dependent variable is manipulated by the researcher.
Both independent and dependent variables are manipulated by the researcher.
Both independent and dependent variables are observed and measured for changes.
#7
Which of the following best describes a randomized controlled trial (RCT)?
A type of observational study
A study where participants are randomly assigned to intervention groups
A study where researchers directly intervene in the natural environment
A study conducted without a control group
#8
What is the purpose of blinding in an experiment?
To make the experiment more visually appealing
To prevent bias in the outcome assessment
To increase the cost-effectiveness of the experiment
To ensure that all participants are aware of the experiment's purpose
#9
Which statistical test is appropriate for comparing means of three or more groups?
T-test
Chi-square test
Analysis of Variance (ANOVA)
Mann-Whitney U test
#10
In experimental design, what is the purpose of randomization?
To ensure that every participant receives the same treatment
To reduce the likelihood of bias in treatment assignment
To increase the cost of the experiment
To limit the generalizability of the results
#11
What is a factorial design in experimental research?
A design that includes multiple factors and levels, allowing for the examination of interactions
A design that involves only one factor and one level
A design used exclusively in observational studies
A design where participants are randomly assigned to treatment groups
#12
What is the main advantage of a crossover study design?
It requires fewer participants
It allows for the assessment of carryover effects
It is less expensive to conduct
It ensures blinding of participants
#13
What is the purpose of a pilot study in experimental design?
To gather data that will be used in the final analysis
To test the feasibility of the study protocol
To recruit participants for the main study
To conduct preliminary statistical analysis
#14
What is the difference between Type I and Type II errors in hypothesis testing?
Type I error occurs when the null hypothesis is true but rejected, while Type II error occurs when the null hypothesis is false but accepted.
Type I error occurs when the null hypothesis is false but accepted, while Type II error occurs when the null hypothesis is true but rejected.
Type I error occurs when the null hypothesis is correctly rejected, while Type II error occurs when the null hypothesis is incorrectly rejected.
Type I error occurs when the null hypothesis is incorrectly rejected, while Type II error occurs when the null hypothesis is correctly rejected.
#15
What does statistical power represent in hypothesis testing?
The probability of rejecting the null hypothesis when it is true
The probability of accepting the null hypothesis when it is false
The likelihood of making a Type I error
The likelihood of making a Type II error
#16
What is the primary purpose of conducting sensitivity analysis in statistical modeling?
To determine the significance of the results
To assess the impact of potential sources of uncertainty or bias
To calculate effect sizes
To select the appropriate statistical test
#17
Why is it important to consider effect size in addition to statistical significance?
Effect size ensures that the sample size is large enough to detect a significant difference.
Effect size provides information about the practical significance of the results.
Effect size helps in determining the appropriate statistical test to use.
Effect size ensures that the data are normally distributed.
#18
What is the purpose of a power analysis in experimental design?
To determine the appropriate sample size needed to detect a significant effect
To calculate the effect size based on the sample size
To assess the distributional assumptions of the data
To determine the statistical significance threshold