Factor analysis reduces the dimensions of data by combining similar _______ into groups or factors.
- eigenvalues
- factors
- observations
- variables
Factor analysis reduces the dimensions of data by combining similar variables into groups or factors.
The ________ distribution is symmetric and its mean, median and mode are equal.
- Binomial
- Normal
- Poisson
- Uniform
The normal distribution, also known as the Gaussian distribution, is symmetric, and its mean, median, and mode are all equal. It is shaped like a bell curve, with the data evenly distributed about the mean.
What are the key assumptions for applying the Sign Test?
- Data must be at least ordinal
- Data must be categorical
- Data must be continuous
- Data must be normally distributed
The key assumption for applying the Sign Test is that the data must be at least ordinal. The Sign Test is a non-parametric test and does not require the assumption of normality.
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.
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.
What techniques can be used to detect multicollinearity in a multiple regression model?
- Analysis of Variance (ANOVA)
- Chi-square test
- T-test
- Variance Inflation Factor (VIF)
The Variance Inflation Factor (VIF) is commonly used to detect multicollinearity in regression analysis.
What is the probability of an event that is certain to happen?
- 0
- 0.5
- 1
- The probability is undefined for certain events
The probability of an event that is certain to happen is 1. This is based on the definition of probability as a measure that takes values between 0 and 1, inclusive. An event with a probability of 1 is a sure event.
The optimal number of clusters in K-means clustering is often determined using the ________ method.
- elbow
- foot
- hand
- knee
The optimal number of clusters in K-means clustering is often determined using the elbow method. This involves plotting the explained variation as a function of the number of clusters and picking the elbow of the curve as the number of clusters to use.
The _______ test compares the means of two independent groups.
- Chi-square
- Independent t
- Paired t
- Z
An Independent t-test (or two sample t-test) compares the means of two independent groups.
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.