For a company observing seasonal sales patterns, which time series model would be best suited to forecast future sales?
- Autoregressive Integrated Moving Average (ARIMA)
- Exponential Smoothing State Space Models (ETS)
- Long Short-Term Memory (LSTM) Networks
- Seasonal Decomposition of Time Series (STL)
Seasonal Decomposition of Time Series (STL) is well-suited for capturing and forecasting seasonal patterns in time series data. It decomposes the time series into components such as trend, seasonality, and remainder. Other models like ARIMA, ETS, and LSTMs may be used for different patterns but STL is specifically designed for seasonality.
The Pandas function _______ is essential for reshaping data from wide format to long format.
- melt()
- pivot_long()
- reshape()
- wide_to_long()
The melt() function in Pandas is essential for reshaping data from wide format to long format. It unpivots the data, making it suitable for various analyses and visualizations.
______ Per Employee' is a performance metric that evaluates the productivity of the workforce.
- Efficiency
- Output
- Profit
- Revenue
'Output Per Employee' is a performance metric that measures the amount of output or work produced by each employee. It is an indicator of workforce productivity. In this context, the blank should be filled with "Output."
For complex data sets, _______ visualization helps to simplify data into a more understandable format.
- Cluster
- Hierarchical
- Tree
- Treemap
Cluster visualization is effective for complex data sets as it groups similar data points together, simplifying the overall representation and making it more understandable.
To extract data from a website, a scraper typically parses the website's ________ structure.
- CSS
- Database
- HTML
- JavaScript
A scraper typically parses the website's HTML structure to extract data. HTML (Hypertext Markup Language) defines the structure of web pages, and parsing it allows the scraper to locate and extract the relevant information.
How is 'Cost Per Acquisition' (CPA) significant in marketing performance analysis?
- CPA measures the cost of acquiring new customers through marketing efforts.
- CPA determines the overall marketing budget for a campaign.
- CPA assesses the total revenue generated by a marketing campaign.
- CPA evaluates the brand awareness created by marketing activities.
Cost Per Acquisition (CPA) is significant in marketing performance analysis as it measures the cost incurred to acquire a new customer through marketing efforts. It helps assess the efficiency and effectiveness of marketing campaigns in acquiring valuable customers. The other options are not accurate descriptions of CPA.
For a sales dashboard, what type of visualization is typically used to represent sales trends over time?
- Line Chart
- Pie Chart
- Radar Chart
- Scatter Plot
A line chart is typically used in a sales dashboard to represent sales trends over time. Line charts are effective for showing the progression of sales data, making it easy to identify patterns, fluctuations, and overall trends.
When analyzing a case study for a logistics company, which key performance indicator (KPI) is most relevant for assessing delivery efficiency?
- Customer Acquisition Cost
- Employee Satisfaction Score
- On-time Delivery Rate
- Return on Investment (ROI)
The On-time Delivery Rate is the most relevant KPI for assessing delivery efficiency in a logistics company. It measures the percentage of deliveries that are made on time, reflecting the company's ability to meet customer expectations regarding delivery timelines.
In dplyr, which function combines two data frames horizontally?
- bind_rows()
- cbind()
- combine()
- merge()
In dplyr, the bind_rows() function is used to combine two data frames horizontally. It stacks the rows of the second data frame below the first, assuming the columns have the same names and types. merge() is used for more complex merging, and cbind() is a base R function for column binding. combine() is not a valid function in this context.
The function ________ is used in R to create user-defined functions.
- create_function()
- define_function()
- function()
- user_function()
In R, the function() keyword is used to create user-defined functions. It is followed by a set of parentheses that can contain function arguments, and then the function body is enclosed in curly braces.
If x = [10, 20, 30, 40, 50], what is the output of print(x[-2])?
- 20
- 30
- 40
- 50
The output is the element at the index -2 in the list, which is 40. Negative indexing counts elements from the end of the list.
In managing a data project, what is a 'data roadmap' and why is it important?
- It focuses on data storage infrastructure
- It is a strategy for data security implementation
- It is a visual representation of data flows within the organization
- It outlines the project timeline and milestones related to data initiatives
A data roadmap in data project management outlines the project timeline, milestones, and key activities related to data initiatives. It provides a strategic view, helping teams understand the sequence of tasks and dependencies. It is not specifically about data security or storage infrastructure.