_____ imputation is a basic method of handling missing data by replacing missing values with the most frequent category (for categorical variables).
- Listwise
- Mean
- Median
- Mode
'Mode' imputation is a basic method of handling missing data by replacing missing values with the most frequent category (for categorical variables). It is easy to implement but might introduce bias by overrepresenting the most frequent category.
Which measure of central tendency will be most affected in a scenario where the dataset has extreme values?
- Mean
- Median
- Mode
- nan
The "Mean" or average will be most affected in a scenario where the dataset has extreme values. Since the mean is calculated by taking into account all values in the dataset, outliers or extreme values can cause significant shifts in the mean, making it less representative of the dataset's central tendency.
Suppose you're given a task to find the outliers in the multivariate dataset. Which plot will be helpful in this context and why?
- Bar Plot
- Box Plot
- Histogram
- Scatter Plot
A scatter plot would be helpful in finding outliers in a multivariate dataset. By plotting different variable combinations, you can identify points that fall far from the general distribution, which could indicate potential outliers.
A wildlife study records the number of different bird species seen during each observation period. How would you classify this data type?
- Continuous data
- Discrete data
- Nominal data
- Ordinal data
The number of different bird species seen during each observation period is a count and therefore classified as discrete data.
How can a Uniform Distribution be transformed into a Normal Distribution?
- By adding a constant to each value
- By applying the Central Limit Theorem
- By squaring each value
- It can't be transformed
A Uniform Distribution can be approximated to a Normal Distribution by the application of the Central Limit Theorem, which states that the sum of a large number of independent and identically distributed variables, irrespective of their shape, tends towards a Normal Distribution.
You are working with a normally distributed data set. How would the standard deviation help you understand the data?
- It can tell you how spread out the data is around the mean
- It can tell you the range of the data
- It can tell you the skewness of the data
- It can tell you where the outliers are
For a normally distributed dataset, the "Standard Deviation" tells you "How spread out the data is around the mean". In a normal distribution, about 68% of values are within 1 standard deviation from the mean, 95% within 2 standard deviations, and 99.7% within 3 standard deviations.
Which of the following is NOT a deployment option for AEM?
- Cloud Deployment
- Hybrid Deployment
- Mainframe Deployment
- On-Premises Deployment
Mainframe Deployment is not a standard deployment option for AEM. AEM supports deployment in the cloud, on-premises, and hybrid environments.
What is Sightly (HTL) in the context of AEM?
- Database Management System
- Design Framework
- Programming Language
- Templating Language
Sightly (HTL) is a templating language in AEM used for creating dynamic and flexible templates for web components.
What are the common types of errors that can be encountered in AEM deployments?
- Configuration errors, resource unavailability, and runtime exceptions
- Server downtime, network latency, and database connection errors
- Syntax errors, logical bugs, and code redundancy
- User interface glitches, browser compatibility issues, and content duplication
Common errors in AEM deployments include configuration errors, resource unavailability, and runtime exceptions, which can impact system stability and performance.
To troubleshoot AEM caching problems, it is essential to understand caching _______ and eviction strategies.
- Configurations
- Mechanisms
- Policies
- Strategies
Understanding caching policies is crucial to troubleshoot AEM caching problems, as it involves managing how content is stored and retrieved from the cache.