Explore the lengths of time variable from the random sample of 100 iTunes songs

Question

Explore the lengths of time variable from the random sample of 100 iTunes songs data set posted on blackboard. Note, the “Time in Minutes” column converted the data that was written minutes:seconds into minutes written as a decimal. For example 2:30 is written as 2.5 minutes.

a) Create a frequency histogram of the “Time in Minutes” variable and describe the shape of this histogram. Do you see any possible outliers? If so, please identify the outlier(s) by song title and length of time.

b) Create a relative frequency histogram of the “Time in Minutes” variable. What is the difference between these two graphs?

c) Provide the mean and standard deviation using R.

d) Provide the five-number summary. First calculate the quartiles by hand using the fractile method seen in the notes and verify your result using R (calculate quartiles using Type = 6).

e) Graph the five number summary using a boxplot using R.

f)Mathematically check for outliers using the fence rule (show work by hand). Do these outliers match the ones you identified in part (a) and marked on the boxplot?

g) What would be the most appropriate measures of center and spread for this distribution based on your analysis?

PLEASEE PROVIDE YOUR COMMAND WINDOW SCREEN SHOT or something that will show your steps in order to get the answers PLEASE

Explanation / Answer

Solutionc:

code in R

mean(Time in Minutes)

sd(Time in Minutes)

Solutiond:

fivenum(Time in Minutes)

Solutione:

boxplot(Time in Minutes)

to get otliers code is:

outlier_values <- boxplot.stats(Time in Minutes)$out # outlier values.
boxplot(stout, main="Time in Minutes ", boxwex=0.1)
mtext(paste("Outliers: ", paste(outlier_values, collapse=", ")), cex=0.6)

Solutionf:

fence rule

value below

Q1-1.5IQR

and values above

Q3+1.5 IQR are outliers

where IQR=Q3-Q1

SOlutiong:

median would be appropriate measure ast is not affected by outliers

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