Explore topic-wise InterviewSolutions in .

Right answer is (B) Variance

Easiest EXPLANATION: In order to calculate CONFIDENCE INTERVALS and hypothesis tests, it is assumed that the errors are independent and normally distributed with MEAN zero and variance.

Correct answer is (B) ignore

The explanation: Linear REGRESSION models the straight-line relationship between Y and X. Any CURVILINEAR relationship is ignored. This ASSUMPTION is most easily EVALUATED by using a scatter plot.

The correct choice is (a) LINEAR REGRESSION

To EXPLAIN: Linear regression is a simple approach to supervised learning. It assumes that the dependence of Y on X1, X2, . . . Xp is linear. linear regression is an incredibly powerful tool for analysing data.

Correct choice is (b) Python

Easiest EXPLANATION: pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data STRUCTURES and data ANALYSIS TOOLS for the Python PROGRAMMING.

Correct answer is (C) Couldn’t comment on Test error

To explain I would say: Test Error depends on the test data. If the Test data is an exact REPRESENTATION of TRAIN data then test error is always zero. But this may not be the case.

The CORRECT option is (C) Sum of the square of residuals ( ∑ (Y-h(X))2) is minimum

The EXPLANATION is: Here we penalize higher error value much more as compared to the smaller one, such that there is a significant difference between MAKING big errors and small errors, which makes it EASY to differentiate and select the best fit line.

The CORRECT option is (B) namespace

To elaborate: The PACKAGE namespace is one of the most confusing parts of BUILDING a package. nbpMatching CONTAINS functions for non-bipartite optimal matching.

Correct answer is (C) .libpaths()

To elaborate: A LIBRARY is simply a directory containing INSTALLED packages. EVERYONE can use the dot libPaths() for seeing which LIBRARIES are currently active.

Correct option is (d) apply(X, MARGIN, FUN, …)

To explain I would say: apply(x,2,max) finds the MAXIMUM for each COLUMN.

Correct option is (a) REV(X)

For explanation: rev provides a REVERSED version of its argument.

The CORRECT OPTION is (B) lubridate

To elaborate: lubridate is one of those magical LIBRARIES that just SEEMS to do exactly what you expect it to.

Correct choice is (a) reverse regression method

The best explanation: The sum of SQUARES of the difference between the observations and the LINE in the horizontal direction in the scatter diagram can be minimized to OBTAIN the estimates of 0 1 β and β. This is generally called a reverse or INVERSE regression method.

The correct option is (b) Extrapolation

Explanation: PREDICTING y for a value of X that is WITHIN the interval of points that we saw in the original data is called interpolation. Predicting y for a value of x that’s OUTSIDE the RANGE of values we actually saw for x in the original data is called extrapolation.

Right option is (a) lm(formula, DATA)

Easiest EXPLANATION: lm(formula, data) refers to a linear model in which formula is the object of the class “formula”, representing the RELATION between variables. Now this formula is on applied on the data to create a RELATIONSHIP model.

Right option is (B) lm

For EXPLANATION I would say: lm CALLS the lower LEVEL functions lm.fit.

Correct choice is (b) uniPlot

The best I can EXPLAIN: uniPlot() allows to change PARAMETERS of the packages GRAPHICS, lattice and GGPLOT2 and to make these changes persistent over one R SESSION.

The correct ANSWER is (c) rowMeans(X, na.rm = FALSE, dims = 1)

The EXPLANATION is: False value leads to unexpected result.

Right option is (d) Regression coefficients

To explain: The PARAMETER β0 is termed as intercept TERM and the parameter β1 is termed as slope parameter. These parameters are usually CALLED as regression coefficients.

The correct option is (C) ANOVA

Explanation: If the ANOVA test DETERMINES that the MODEL explains a significant portion of the variability in the data, then we can consider testing each of the hypotheses and correcting for MULTIPLE COMPARISONS.

The CORRECT choice is (a) Library

Best explanation: library() FUNCTION is USED to load a package. library() is not useful when we are developing a package SINCE you have to install the package first. A library is a SIMPLE directory containing installed packages.

Correct choice is (C) Single

To explain: A bundled package is a package that’s been compressed into a single FILE. A SOURCE package is just a DIRECTORY with components like R/, DESCRIPTION, and so on.

Correct answer is (C) ACRM

Easiest explanation: Convenience FUNCTIONS for data preparation and modeling are OFTEN used in aCRM.

Right answer is (b) QCC

To elaborate: qcc can help you monitor transaction volumes, visitors or LOGINS on your WEBSITE, DATABASE operations, and lots of other processes.

The correct answer is (a) browse.workspace

To explain I would say: It is a MAC menu command that CREATES a WINDOW with INFORMATION about all variables in the workspace.

The correct option is (a) DESCRIPTIVE

Easiest explanation: Descriptive is the SIMPLEST CLASS of analytics. Predictive analytics can only forecast what might HAPPEN in the future because all predictive analytics are probabilistic in nature.

The CORRECT answer is (d) by its SLOPE

To explain I WOULD say: For linear regression Y=a+bx+ERROR. If neglect error then Y=a+bx. If X increases by 1, then Y = a+b(x+1) which implies Y=a+bx+b. So Y increases by its slope.

Right ANSWER is (a) alteryx

Easy explanation: Alteryx Analytics, with deep INTEGRATION of the R statistics and PREDICTIVE language, offers a way to bridge these TWO worlds of ease of use and SOPHISTICATED predictive analytics.

Correct CHOICE is (a) Description

Easiest explanation: The job of the DESCRIPTION file is to STORE the metadata about your PACKAGE. When you first start WRITING packages, you’ll mostly use these metadata to RECORD what packages are needed to run your package.

Correct answer is (c) Letters

For EXPLANATION: There are three formal requirements: the name can only consist of letters, NUMBERS and PERIODS, i.e., it must start with the letter and it should not END with a PERIOD.

Correct answer is (b) LIBRARY

The EXPLANATION: library() is not useful when DEVELOPING a package SINCE you have to install the package first. A library is a simple directory containing installed PACKAGES.

The CORRECT option is (c) Text

Easy explanation: An .Rproj file is a text file. If you don’t use RStudio, you can get many of the benefits by starting a new R session and ENSURING that the DIRECTORY is set to the PACKAGE directory.

The CORRECT answer is (a) accelerometry

For explanation: This PACKAGE contains a COLLECTION of FUNCTIONS that perform operations on time-series accelerometer data, such as identify non-wear time, flag minutes that are PART of an activity about, and find the maximum 10-minute average count value.

Correct option is (a) Linear regression

Easy explanation: Linear regression is an INCREDIBLY powerful TOOL for analysing DATA. we’ll focus on finding one of the simplest type of relationship: linear. This PROCESS is unsurprisingly called linear regression, and it has MANY applications.

The CORRECT answer is (c) MULTIPLE Linear model

To explain: When there are more than ONE independent variables in the model, then the linear model is TERMED as the multiple linear REGRESSION model.

Correct answer is (B) BWPLOT()

Explanation: The FUNCTION bwplot() MAKES box-and-whisker plots for numerical VARIABLES.

The correct ANSWER is (a) qqline()

For EXPLANATION: qqnorm is ANOTHER tool for checking normality.

Right answer is (a) VIGNETTES

To explain I would say: Vignettes are built for getting the HTML and PDF output instead of MARKDOWN or LaTeX INPUT. A BUNDLED package is a package that’s been compressed into a single file.

The correct CHOICE is (b) source

Explanation: .Rbuildignore prevents files from the source package and appearing in the bundled package. It allows to have some EXTRA DIRECTORIES in your source package that will not be INCLUDED in the package BUNDLE.