Questions and Answers
What is the primary purpose of a null hypothesis in hypothesis testing?
Which type of test is used to determine whether a sample mean is significantly different from a population mean in either direction?
What is the term for rejecting the null hypothesis when it is actually true?
What is the purpose of randomization in experiment design?
Signup and view all the answers
What is the term for a variable that can affect the outcome of an experiment but is not controlled for?
Signup and view all the answers
What is the purpose of replicating an experiment?
Signup and view all the answers
What type of study is used to prevent both the participants and researchers from being aware of the group assignments or treatment conditions?
Signup and view all the answers
What is the term for the probability of obtaining the observed results (or more extreme results) assuming the null hypothesis is true?
Signup and view all the answers
What is the primary purpose of observation in the scientific method?
Signup and view all the answers
What is a characteristic of a good observation?
Signup and view all the answers
What is a hypothesis?
Signup and view all the answers
What is a characteristic of a good hypothesis?
Signup and view all the answers
What is the main difference between a null hypothesis and an alternative hypothesis?
Signup and view all the answers
Why is it important to make observations during an experiment?
Signup and view all the answers
Study Notes
Hypothesis Testing
- Null Hypothesis (H0): a statement of no difference or no effect, predicting that the observed phenomenon is due to chance
- Alternative Hypothesis (H1): a statement of difference or effect, predicting that the observed phenomenon is real
- One-Tailed Test: tests whether the sample mean is significantly greater than (or less than) the population mean
- Two-Tailed Test: tests whether the sample mean is significantly different from the population mean (in either direction)
- Type I Error: rejecting the null hypothesis when it is actually true (false positive)
- Type II Error: failing to reject the null hypothesis when it is actually false (false negative)
- Level of Significance (α): the maximum probability of committing a Type I error, typically set at 0.05
- P-Value: the probability of obtaining the observed results (or more extreme results) assuming the null hypothesis is true
- Test Statistic: a numerical value that summarizes the difference between the sample data and the null hypothesis
Experiment Design
- Independent Variable: the variable being manipulated by the researcher
- Dependent Variable: the variable being measured or observed in response to the independent variable
- Control Group: a group that does not receive the treatment or manipulation, used as a baseline for comparison
- Experimental Group: a group that receives the treatment or manipulation
- Randomization: the process of randomly assigning participants to either the control or experimental group
- Replication: repeating the experiment multiple times to increase the reliability of the results
- Confounding Variables: variables that can affect the outcome of the experiment and are not controlled for
- Blind Study: a study in which the participants or researchers are unaware of the group assignments or treatment conditions
- Double-Blind Study: a study in which both the participants and researchers are unaware of the group assignments or treatment conditions
Hypothesis Testing
- A null hypothesis (H0) proposes no real effect or difference, attributing observed outcomes to chance
- An alternative hypothesis (H1) proposes a real effect or difference, suggesting observed outcomes are genuine
- One-tailed tests examine if sample means are significantly greater or less than population means
- Two-tailed tests examine if sample means differ significantly from population means in either direction
- Type I errors occur when rejecting a true null hypothesis (false positive), with a 5% chance of occurrence (α = 0.05)
- Type II errors occur when failing to reject a false null hypothesis (false negative)
- P-values represent the probability of achieving observed results (or more extreme) assuming a true null hypothesis
- Test statistics numerically summarize differences between sample data and the null hypothesis
Experiment Design
- Independent variables are manipulated by researchers to observe effects
- Dependent variables are measured or observed in response to independent variables
- Control groups serve as baselines, unaffected by the treatment or manipulation
- Experimental groups receive the treatment or manipulation, allowing for comparison with control groups
- Randomization ensures participants are randomly assigned to control or experimental groups
- Replication involves repeating experiments to increase result reliability
- Confounding variables can affect experiment outcomes and require control
- Blind studies conceal group assignments or treatment conditions from participants or researchers
- Double-blind studies conceal group assignments or treatment conditions from both participants and researchers
Scientific Method
Observation
- The first step in the scientific method, involving careful and systematic observations about the world around us
- Can be done through direct observation (using senses) or indirect observation (using tools or instruments)
- A good observation must be:
- Accurate (free from bias and error)
- Precise (detailed and specific)
- Relevant (related to the problem or question being studied)
Hypothesis
- A proposed explanation for the observations made, predicting the outcome of an experiment
- Characteristics of a good hypothesis:
- Specific (clearly states what is being tested)
- Testable (can be proven or disproven through experimentation)
- Falsifiable (can be proven wrong if data doesn't support it)
- Simple (easy to understand and communicate)
- Types of hypotheses:
- Null hypothesis (states no significant difference or relationship)
- Alternative hypothesis (states significant difference or relationship)
Studying That Suits You
Use AI to generate personalized quizzes and flashcards to suit your learning preferences.
Description
Learn about the fundamentals of Hypothesis Testing, including Null and Alternative Hypothesis, One-Tailed and Two-Tailed Tests, and more. Test your understanding of statistical concepts!
