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Data Analytics (with R) Practice Exam Questions

Data Analytics (with R) Practice Exam Questions

R analytics (or R programming language) is amongst the free, open-source software used by professionals for all kinds of data science, statistics, and visualization projects. R programming language is amongst the most powerful, versatile languages with the ability to be integrated into BI platforms like Sisense, to assist with handling business-critical data.

Target Audience

  • Software engineers
  • Web developers
  • Programmers
  • Bachelor’s in science and CS

Skills Required

  • Microsoft Excel.
  • Critical Thinking
  • R or Python–Statistical Programming.
  • Data Visualization.
  • Presentation Skills.
  • Machine Learning.
  • SQL

Career Prospects

  • Data Scientist
  • Data Engineer
  • Data Analyst
  • Machine Learning Engineer
  • Data Journalist
  • Database Admin
  • Financial Analyst
  • Business Analyst

Course Outline

The Data Analytics (with R) Practice Exam covers topics including -

Module 1 - Introduction

  • Evolution and Scope
  • Learning Data for Business Analytics
  • Decision Models
  • Problem Solving and Decision Making

Module 2 - Descriptive Statistical Measures

  • Learning
  • Measures of Location
  • Learning Measures of Dispersion
  • Measures of Shape
  • Learning Measures of Association
  • Learning Excel Descriptive Statistics Tool

Module 3 - Probability Distributions

  • Learning probability basis
  • Discrete Probability Distributions
  • Continuous Probability Distributions
  • Learning Distribution Fitting

Module 4 - Sampling and Estimation

  • Learning Sampling Methods
  • Statistical Sampling
  • Sampling Distributions
  • Learning Estimation
  • Interval Estimates
  • Confidence Intervals
  • Learning Prediction Intervals

Module 5 - Statistical Inference

  • Hypothesis Testing
  • One-Sample Hypothesis Tests
  • Two-Sample Hypothesis Tests
  • Learning ANOVA

Module 6 - R Programming Language Introduction

  • What is R?
  • Learning Objects and Arithmetic
  • Summaries and Subscripting
  • Matrices
  • Attaching to objects
  • Learning Statistical Computation and Simulation
  • Graphics

Module 7- Reading Data from files

  • The read.table() function
  • Learning the scan() function
  • Accessing Builtin Datasets
  • Editing data

Module 8 - Probability Distributions

  • R as a set of statistical tables
  • Examining the distribution of a set of data
  • Learning One- and two-sample tests

Module 9 - Statistical Models in R

  • Defining statistical models; formulae
  • Learning Linear models
  • Generic functions for extracting model information
  • Analysis of variance and model comparison
  • Updating fitted models
  • Generalized Linear Models
  • Learning Nonlinear least squares and maximum likelihood models
  • Some Non-Standard Models

Module 10 - R Graphics Facilities

  • High-Level Plotting Commands
  • Low-level plotting commands
  • Interacting with graphics
  • Using graphics parameters
  • Graphics parameters list
  • Learning Figure margins
  • Learning Device drivers

Module 11 - R Data Import/Export

  • Imports
  • Learning XML
  • Spreadsheet-like data
  • Importing from other statistical systems
  • Relational databases
  • Learning
  • Image files
  • Connections
  • Network interfaces
  • Reading Excel spreadsheets

What do we offer?

  • Full-Length Mock Test with unique questions in each test set
  • Practice objective questions with section-wise scores
  • In-depth and exhaustive explanation for every question
  • Reliable exam reports evaluating strengths and weaknesses
  • Latest Questions with an updated version
  • Tips & Tricks to crack the test
  • Unlimited access

What are our Practice Exams?

  • Practice exams have been designed by professionals and domain experts that simulate real-time exam scenario.
  • Practice exam questions have been created on the basis of content outlined in the official documentation.
  • Each set in the practice exam contains unique questions built with the intent to provide real-time experience to the candidates as well as gain more confidence during exam preparation.
  • Practice exams help to self-evaluate against the exam content and work towards building strength to clear the exam.
  • You can also create your own practice exam based on your choice and preference 

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