Which of the following is useful way to put text code data output all in one document?
Answer is “Literate statistical programming”
What does it mean to be a literate statistical program?
literate – It uses natural language (like English) in an appropriate way to the context. statistical – Written in a statistical language or a general purpose language with strong statistical and analytical tools (like R or Python).
Which of the following disadvantage does literate programming have 1 point?
Which of the following disadvantage does literate programming have? Explanation: Code and text is in one place. 7. knitr supports only one documentation language.
Which of the following step is not required in data analysis?
4. Which of the following is not a step in data analysis? Explanation: EDA stands for Exploratory Data Analysis.
What is the main role of statistical functions principles and algorithms?
11. What is the main role of Statistical functions, principles, and algorithms? Explanation: Several Statistical functions, principles, and algorithms are implemented to analyze raw data, build a Statistical Model and infer or predict the result.
Which of the following tool can be used for integrating text and code in one document * A Knitr B ggplot2 C Numpy D None of the mentioned?
Which of the following tool can be used for integrating text and code in one document? Explanation: knitr is a way to write LaTeX, HTML, and Markdown with R code interlaced.
Which of the following tool documentation language is supported by Knitr?
knitr is officially supported in the RStudio IDE for R, LyX, Emacs/ESS and the Architect IDE for data science.
Which of the following is characteristic of processed data?
Which of the following is characteristic of Processed Data? Explanation: Processing includes merging, summarizing and subsetting data. 10.
How is statistics used in data analysis?
Two main statistical methods are used in data analysis: descriptive statistics, which summarize data from a sample using indexes such as the mean or standard deviation, and inferential statistics, which draw conclusions from data that are subject to random variation (e.g., observational errors, sampling variation).
What are the types of data in statistics?
Simple data types
| Data Type | Possible values | Level of measurement |
|---|---|---|
| categorical | 1, 2., K (arbitrary labels) | nominal scale |
| ordinal | integer or real number (arbitrary scale) | ordinal scale |
| binomial | 0, 1., N | interval scale |
| count | nonnegative integers (0, 1.) | ratio scale |
Which of the following language is used in data science?
Python is the most widely used data science programming language in the world today.
What is the data processing pipeline service?
What is the Data Processing Pipeline Service? The Data Processing Pipeline Service consists of analysis pipelines and execution infrastructure that move raw data through analysis, producing measurements that are available for download by the community from the Data Portal.
What are the steps in the test pipeline?
In the preceding diagram, the test pipeline consists of the following steps: A developer commits code changes to the Cloud Source Repositories. Code changes trigger a test build in Cloud Build. Cloud Build builds the self-executing JAR file and deploys it to the test JAR bucket on Cloud Storage.
What are the steps in the CI/CD pipeline?
At a high level, the CI/CD pipeline consists of the following steps: Cloud Build packages the WordCount sample into a self-running Java Archive (JAR) file using the Maven builder . The Maven builder is a container with Maven installed in it.
What is a candidate pipeline?
Each candidate pipeline is a combination of data preprocessing steps, an ML algorithm, and its optimized hyperparameters. You can easily deploy any of these candidate pipelines to use for real-time prediction or batch prediction.