3.7 Inference and Experiments

• Random assignment ensures differences between treatment groups are due to the treatment itself.


  True
• A population is the entire group of individuals or objects of interest in a study.

  True
• Hypothesis tests determine if there is enough evidence to reject the null hypothesis.
• Larger sample sizes lead to smaller margins of error in statistical inference.
• Selecting an appropriate sample size is crucial for making accurate inferences about a population
• The purpose of a control group is to provide a baseline for comparison.


  True
• There are two main types of statistical inferences: confidence intervals and hypothesis
• The sample size and margin of error are inversely related
• The treatment group refers to participants in an experiment who receive the treatment being studied
• Randomization ensures that any differences observed between groups can be attributed to the treatment
• Match the concept with its purpose.

  Statistical Significance ↔️ Determine if the treatment had a meaningful effect

  Hypothesis Testing ↔️ Decide whether to accept or reject the null hypothesis
• Selection Bias occurs when participants are not randomly assigned to treatment and control groups
• What is the purpose of a control group in an experiment?

  Provides a baseline for comparison
• Match the concept with its definition:

  Random Assignment ↔️ Participants are randomly assigned to treatment groups

  Control Group ↔️ A group that does not receive the treatment
• Confidence intervals are used to estimate the true value of a population parameter with a certain level of confidence.


  True
• A smaller sample size results in a larger margin of error.


  True
• What happens to the margin of error when the sample size increases?

  It decreases
• Match the group with its definition in experimental design:

  Control Group ↔️ Participants who do not receive treatment

  Treatment Group ↔️ Participants who receive treatment
• What is the primary purpose of inference in experiments?

  Generalize findings to the population
• What do confidence intervals estimate in statistical inference?

  Population parameters
• Why is random assignment important in experimental design?

  To minimize bias
• The control group provides a baseline for comparison in an experiment.


  True
• Experiments without randomization are more susceptible to bias.


  True
• What is confounding in experimental design?

  Effect mixed with other factors
• Inference is the process of drawing conclusions about a population based on a sample.
• Inference allows us to make educated guesses about the characteristics of a population by analyzing data from a sample.
• What are the two primary types of statistical inferences?

  Confidence intervals and hypothesis tests
• What is the purpose of hypothesis testing in statistical inference?

  Assess a claim about a population
• Steps in experimental design for valid inferences:

  1️⃣ Define the research question

  2️⃣ Select a representative sample

  3️⃣ Randomly assign participants to groups

  4️⃣ Apply the treatment to the treatment group

  5️⃣ Collect and analyze data

  6️⃣ Draw conclusions based on evidence
• A larger sample size reduces the uncertainty around an estimate.


  True
• The treatment group receives the experimental treatment
• Random assignment ensures any differences between groups can be attributed to the treatment.


  True
• Hypothesis tests evaluate evidence to support or reject a claim about population parameters.

  True
• The purpose of a control group is to provide a baseline for comparison.


  True
• What is the purpose of the treatment group in an experiment?

  To measure treatment effect
• Arrange the following experimental types based on their validity.

  1️⃣ Randomized Experiment

  2️⃣ Non-Randomized Experiment
• A small p-value suggests the null hypothesis is unlikely.


  True
• Arrange the following experimental design principles in order of their importance for reducing bias.

  1️⃣ Random Assignment

  2️⃣ Control Group