To start with the new package in RStudio, double-click the pkgname.Rproj file that _______(a) Delete()(b) Create()(c) Run()(d) Exit()I have been asked this question in an interview for internship.This interesting question is from Packages in chapter Commands, Packages, Visualizing Data and Linear Regression of R Programming

To start with the new package in RStudio, double-click the pkgname.Rpr

1.	To start with the new package in RStudio, double-click the pkgname.Rproj file that _______(a) Delete()(b) Create()(c) Run()(d) Exit()I have been asked this question in an interview for internship.This interesting question is from Packages in chapter Commands, Packages, Visualizing Data and Linear Regression of R Programming
Answer» The correct choice is (B) CREATE() To elaborate: To GET started with your new PACKAGE in RStudio, double-click the pkgname.Rproj file that create() just made. This will open a new RStudio project for your package. Projects are the way to develop packages.

Discussion

No Comment Found

Related InterviewSolutions

In order to calculate confidence intervals and hypothesis tests, it is assumed that the errors are independent and normally distributed with mean zero and _______(a) Mean(b) Variance(c) SD(d) KNNI got this question in homework.The origin of the question is Linear Regression topic in chapter Commands, Packages, Visualizing Data and Linear Regression of R Programming
What do we do the curvilinear relationship in linear regression?(a) consider(b) ignore(c) may be considered(d) sometimes considerThe question was posed to me in examination.This question is from Linear Regression topic in division Commands, Packages, Visualizing Data and Linear Regression of R Programming
Although it may seem overly simplistic, _______ is extremely useful both conceptually and practically.(a) Linear regression(b) Logistic regression(c) Gradient Descent(d) Greedy algorithmsThe question was asked in exam.This interesting question is from Linear Regression topic in section Commands, Packages, Visualizing Data and Linear Regression of R Programming
Which of the following is preferred for text analytics?(a) R(b) Python(c) S(d) EDRThe question was asked during an interview for a job.Enquiry is from Predictive Analytics topic in section Commands, Packages, Visualizing Data and Linear Regression of R Programming
If Linear regression model perfectly first i.e., train error is zero, then _____________________(a) Test error is also always zero(b) Test error is non zero(c) Couldn’t comment on Test error(d) Test error is equal to Train errorI had been asked this question in an internship interview.I'm obligated to ask this question of Linear Regression topic in chapter Commands, Packages, Visualizing Data and Linear Regression of R Programming
Which of the following package has temporary files?(a) Single(b) Source(c) Bundle(d) DoubleI got this question during an internship interview.The doubt is from Packages topic in chapter Commands, Packages, Visualizing Data and Linear Regression of R Programming
In practice, Line of best fit or regression line is found when _____________(a) Sum of residuals (∑(Y – h(X))) is minimum(b) Sum of the absolute value of residuals (∑|Y-h(X)|) is maximum(c) Sum of the square of residuals ( ∑ (Y-h(X))2) is minimum(d) Sum of the square of residuals ( ∑ (Y-h(X))2) is maximumThis question was addressed to me during an internship interview.This question is from Linear Regression in section Commands, Packages, Visualizing Data and Linear Regression of R Programming
Which of the following package provide namespace management functions not yet present in base R?(a) stringr(b) namespace(c) nbpMatching(d) messagewarningThis question was posed to me during an online exam.My enquiry is from Packages in portion Commands, Packages, Visualizing Data and Linear Regression of R Programming
Which function is used for seeing currently active libraries?(a) Curlib()(b) Currlib()(c) .libpaths()(d) Pathlibr()The question was asked in an internship interview.I'm obligated to ask this question of Packages topic in chapter Commands, Packages, Visualizing Data and Linear Regression of R Programming
Which of the following statement applies the function (FUN) to either rows (1) or columns (2) on object X?(a) apply(x,1,min)(b) apply(x,2,max)(c) col.max(x)(d) apply(X, MARGIN, FUN, …)I have been asked this question in quiz.This intriguing question comes from Commands in portion Commands, Packages, Visualizing Data and Linear Regression of R Programming

Discussion

No Comment Found

Related InterviewSolutions

Reply to Comment