Thetazero Pubs
mayahadarvalues value data output function called means mean test question returns

Question 1. Captain Jack is convinced that he can predict how much gold he will find on an island with the following equation: (a * b) - c * 324 + log(a), where a is the area of the island in square meters, b is the number of trees on the island, and c is how drunk he is on a scale of 1 to 10. Create a function called Jacks.Equation that takes a, b, and c as arguments and returns Captain Jack?s predictions. Test your function for an island with an area of 1,000 square meeters that contains 30 trees when Jack is at a 7 / 10 on a drunkenness scale.


Jacks.Equation <- function (a, b, c) {
  
  output <- (a * b) - c * 324 + log(a)
  
  return (output)
}

Test your function for an island with an area of 1,000 square meeters that contains 30 trees when Jack is at a 7 / 10 on a drunkenness scale. => 27738.91

Jacks.Equation (a= 1000, b= 30, c= 7)
## [1] 27738.91

Question 2. Write a function called standardize.me that takes a vector x as an argument, and returns a vector that standardizes the values of x (standardization means subtracting the mean and dividing by the standard deviation).

standardize.me <- function (x) {
  
  output <- (x- mean(x)) / sd (x)
  
  return (output)
}

data <- c(6, 3, 8, 6, 3, 2, 3, 2, 100)

standardize.me (data)
## [1] -0.2740789 -0.3677514 -0.2116305 -0.2740789 -0.3677514 -0.3989756
## [7] -0.3677514 -0.3989756  2.6609937

Question 3. Write a function called remove.outliers that takes a vector as an argument, determines which values of the vector are outliers, and returns a vector with the outliers removed. Define an outlier as any value that is less than 2 standard deviations below the mean, or more than 2 standard deviations above the mean.

When you are finished writing the function, run these commands to make sure your function works

remove.outliers <- function (x) {
  
is.outlier <- x< mean (x) -2*sd(x) | x> mean (x) + 2*sd (x)

new.vector <- x[!is.outlier]
  
  return (new.vector)

}

data <- c(rep(1, 100), -529484903)
mean(data)
## [1] -5242424
mean(remove.outliers(data))
## [1] 1

-5242424, 1


Question 4. Write a function called how.many that takes two arguments (data and value). The function should return a value indicating how many times the element value occured in the vector data

how.many <- function (data, value) {
  value.log <- data == value
  output <- sum (value.log)
  return (output)

}

how.many(data = c(1, 1, 9, 3, 2, 1, 1), value = 1)
## [1] 4
how.many(data = c(1, 1, 9, 3, 2, 1, 1), value = -100)
## [1] 0

Question 5. Write a function called madlib that takes three strings as arguments, and returns the following sentence with the string arguments inserted into the following text:

?If you talk to an ADJECTIVE pirate like NAME you may find that he/she spends more time talking about PLURALNOUN than the pirate arts.?

Your three arguments to the function should be:

adjective, a string indicating an adjective name, a string of a person?s name plural.noun, a string indicatinga plural noun

madlib <- function (adjective, name, plural.noun) {
  
  output <- paste("If you talk to an", adjective , "pirate like", name, "you may find that he/she spends more time talking about",plural.noun)
  return (output)
  
}

madlib("ADJECTIVE", "NOUN", "PLURAL NOUN")
## [1] "If you talk to an ADJECTIVE pirate like NOUN you may find that he/she spends more time talking about PLURAL NOUN"
madlib("inattractive", "my supervisor", "boring stuff")
## [1] "If you talk to an inattractive pirate like my supervisor you may find that he/she spends more time talking about boring stuff"

Question 6. Write a function called ttest.apa that takes a numeric vector as an argument, conducts a one-sample t.test on that vector, and returns a string summarising the test in APA style. Your function should have 3 arguments

x, a vector of data null, the population mean under the null hypothesis p.critical, the critical value for determining significance

unfinished?

ttest.apa <- function (x, null, p.critical){

test.tesult <- t.test(x, mu=0, alternative = ?t?)

if (test.tesults\(parameter < test.tesults\)p.value) {

output <- paste(" (t(" ,test.result\(parameter , ")=", test.result\)statistic, ?p=?, test.result$p.value)

if (test.tesults\(parameter > test.tesults\)p.value) {print (?A one sample t-test was significant?)}

output <- paste(" (t(" ,test.result\(parameter , ")=", test.result\)statistic, ?p=?, test.result$p.value)

return (output)

}

Copyright © 2016 thetazero.com All Rights Reserved. Privacy Policy