What are the implications of having a small expected frequency in a Chi-square test for goodness of fit?
- It can cause the Chi-square distribution approximation to be inaccurate
- It increases the degrees of freedom
- It leads to a higher power of the test
- It leads to a smaller Chi-square statistic
If the expected frequency in any category is too small (common rule of thumb is less than 5), the Chi-square distribution approximation may be inaccurate, leading to incorrect conclusions.
How does the concept of "updating" apply in Bayesian statistics?
- It means changing the data after analysis
- It means replacing old hypotheses with new ones
- It refers to modifying the statistical model
- It refers to the process of using new evidence to update a prior probability
Updating in Bayesian statistics refers to the process of using new evidence to update a prior probability to a posterior probability. Bayes' theorem provides the mathematical framework for this updating process.
The Mann-Whitney U test is a ________ test.
- Chi-square
- correlation
- non-parametric
- parametric
The Mann-Whitney U test is a non-parametric test, meaning it does not assume that the underlying data follows a specific distribution.
The use of __________ in mobile automation testing allows for testing on real device conditions.
- Cloud-based Testing Platforms
- Emulators
- Simulators
- Virtual Machines
Cloud-based testing platforms in mobile automation testing allow for testing on real device conditions. These platforms provide access to a diverse range of real devices, allowing testers to ensure that the application performs well across different devices and operating systems. Using cloud-based platforms enhances the accuracy and effectiveness of mobile automation testing by simulating real-world scenarios.
How does Apache JMeter handle distributed testing across multiple machines?
- By configuring multiple virtual hosts
- By deploying multiple instances on a single machine
- By dividing test cases among team members
- By using master-slave architecture
Apache JMeter handles distributed testing through a master-slave architecture. The master orchestrates the test execution by distributing the load among slave machines. This approach allows for scalability and the simulation of real-world scenarios with a higher number of concurrent users. It enables efficient utilization of resources and better performance testing of applications under different conditions.
Which of the following best describes a key principle of Continuous Integration (CI)?
- Frequent and automated code integration
- Isolating developers from the integration process
- Manual testing before code integration
- Performing integration only at the end
A key principle of Continuous Integration (CI) is frequent and automated code integration. In CI, developers regularly integrate their code changes into a shared repository. Automated build and test processes are triggered upon each integration, helping to identify integration issues early in the development cycle. This practice ensures that the software remains in a continuously integratable state, leading to faster feedback and improved collaboration among team members.
The Sign Test is based on the direction of the _________ between pairs.
- differences
- medians
- ranks
- signs
The Sign Test is based on the direction of the differences between pairs.
How does the Law of Large Numbers impact the calculation of probabilities?
- It changes the probability of an event based on previous outcomes.
- It doesn't affect the calculation of probabilities.
- It guarantees that the experimental probability gets closer to the theoretical probability as the number of trials increases.
- It states that all probabilities must be equal.
The Law of Large Numbers impacts the calculation of probabilities by asserting that as the number of trials (or observations) increases, the experimental probabilities will get closer and closer to the theoretical (or true) probabilities. It gives validity to the notion of probability in practical applications.
If two events A and B are mutually exclusive, the probability of both occurring is _______.
- 0
- 0.5
- 1
- The probability is undefined
If two events A and B are mutually exclusive, the probability of both occurring is 0. Mutually exclusive events cannot occur at the same time.
How does the sample size relate to the power of a test?
- It depends on the effect size
- Larger sample sizes decrease power
- Larger sample sizes increase power
- Sample size has no influence on power
Larger sample sizes increase the power of a test because they provide more data, reducing the influence of random error and making it easier to detect an effect if one exists. This is why researchers often aim to recruit as large a sample as possible, within the constraints of their resources.
In multiple linear regression, the __________ test is used to test if a group of variables contributes to the prediction of the response.
- Chi-square test
- F-test
- T-test
- Z-test
The F-test is used in multiple regression to test whether at least one of the predictors' regression coefficient is not equal to zero. In other words, it tests whether the predictors are significant in explaining the response variable.
How does a higher R-squared value impact the inference in multiple linear regression?
- It decreases the number of observations
- It improves the interpretability of the model
- It increases the residuals
- It makes the model more complex
The R-squared value measures the proportion of the variance in the dependent variable that is predictable from the independent variables. A higher R-squared value, closer to 1, implies a higher proportion of variability in the response variable is explained by the predictors, improving the model's interpretability and predictive power.