D-DS-FN-23 Dell Data Science Foundations Questions and Answers

The GROUP BY clause in the SQL statement implies the use of an aggregate function. In this case, avg(prod_cost) is an aggregate function that calculates the average of the product costs for each group of products.

Linear regression is the appropriate technique for estimating a continuous target variable, such as home sale price, based on other continuous and categorical input variables like square footage, number of bedrooms, and lot size.

The Hadoop Distributed File System (HDFS) is a master/slave system designed to run on commodity hardware, meaning it can efficiently store large volumes of data across inexpensive, off-the-shelf hardware.

In linear regression, the model output includes coefficients that indicate the relative impact of the input variables on the outcome. These coefficients represent how much each input variable influences the predicted outcome.

Feature selection involves identifying the most useful input variables that contribute meaningfully to the model, improving accuracy and reducing complexity during the model building phase.

Spark's in-memory data processing avoids the need to write intermediate data to disk, which significantly speeds up processing compared to MapReduce, which writes intermediate data to disk after each operation. This makes Spark much faster for iterative tasks.

An itemset is a set of discrete variables (or items) that are linked or appear together in a transaction or dataset, commonly used in association rule mining to find relationships between items.

The decision tree having 17 layers and a leaf node with only three customers suggests that the tree is overfitting the data. This is because a deep tree with many layers can lead to overfitting, where the model fits the training data too closely, capturing noise and small details that do not generalize well to new data. Reducing the tree depth or pruning the tree can help mitigate overfitting.

In logistic regression, the threshold determines the cutoff for classifying an outcome. If the probability exceeds the threshold (0.3 in this case), the model predicts the positive class—here, that the borrower will default.

A box and whisker plot is ideal for visualizing the relationship between time spent and product category, especially when you have multiple categories. It shows the distribution of time spent in each product category, including the median, quartiles, and any potential outliers.

Data conditioning in the data preparation phase refers to the process of cleaning the data, normalizing datasets, and performing transformations to ensure the data is in a suitable format for analysis or modeling.

In ANOVA (Analysis of Variance), the null hypothesis is that all population means are equal to each other. The goal is to test whether there is evidence to reject this hypothesis, indicating that at least one population mean differs from the others.

A Type I error occurs when the null hypothesis is rejected even though it is actually true. This is also known as a "false positive" in hypothesis testing.

The Scheduler in Hadoop is responsible for allocating compute and memory resources across various applications running on the cluster. It decides how resources are distributed based on policies and availability.