Week 4 quiz

Author: edj-boston

Diff for: week-04/quiz.md

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+Quiz
+====
+
+Question 1
+----------
+
+What is produced at the end of this snippet of R code?
+
+	set.seed(1)
+	rpois(5, 2)
+
+### Answer
+
+A vector with the numbers 1, 1, 2, 4, 1
+
+### Explanation
+
+Because the `set.seed()' function is used, `rpois()' will always output the same vector in this code.
+
+
+Question 2
+----------
+
+What R function can be used to generate standard Normal random variables?
+
+### Answer
+
+rnorm
+
+### Explanation
+
+Functions beginning with the `r` prefix are used to simulate random variates.
+
+Standard probability distributions in R have a set of four functions that can be used to simulate variates, evaluate the density, evaluate the cumulative density, and evaluate the quantile function.
+
+
+Question 3
+----------
+
+When simulating data, why is using the `set.seed()` function important?
+
+### Answer
+			
+It ensures that the sequence of random numbers is reproducible.
+
+
+Question 4
+----------
+
+Which function can be used to evaluate the inverse cumulative distribution function for the Poisson distribution?
+
+### Answer
+
+qpois
+
+### Explanation
+
+Probability distribution functions beginning with the `q` prefix are used to evaluate the quantile function.
+
+
+Question 5
+----------
+
+What does the following code do?
+
+	set.seed(10)
+	x <- rbinom(10, 10, 0.5)
+	e <- rnorm(10, 0, 20)
+	y <- 0.5 + 2 * x + e
+
+### Answer
+
+Generate data from a Normal linear model
+
+
+Question 6
+----------
+What R function can be used to generate Binomial random variables?
+
+### Answer
+
+rbinom
+
+
+Question 7
+----------
+
+What aspect of the R runtime does the profiler keep track of when an R expression is evaluated?
+
+### Answer
+
+the function call stack	
+
+
+Question 8
+----------
+Consider the following R code
+
+	library(datasets)
+	Rprof()
+	fit <- lm(y ~ x1 + x2)
+	Rprof(NULL)
+
+(Assume that y, x1, and x2 are present in the workspace.) Without running the code, what percentage of the run time is spent in the `lm` function, based on the `by.total` method of normalization shown in `summaryRprof()`?
+
+
+### Answer
+
+100%
+
+### Explanation
+
+When using `by.total` normalization, the top-level function (in this case, `lm()`) always takes 100% of the time.
+
+
+Question 9
+----------
+
+When using `system.time()`, what is the user time?
+
+### Answer
+
+It is the time spent by the CPU evaluating an expression
+
+
+Question 10
+-----------
+
+If a computer has more than one available processor and R is able to take advantage of that, then which of the following is true when using `system.time()`?
+
+### Answer
+
+Elapsed time may be smaller than user time