Problem 1

(A)

The mean for steps taken is:

## [1] 9622.533

The median is:

## [1] 9385.5

The standard deviation is:

## [1] 3736.228

(B)

The mean for hours slept is:

## [1] 7.402049

The median is:

## [1] 8.02

The standard deviation is:

## [1] 2.097509

(C)

Distance Quantiles in miles

Q1: 2.9925

Q2: 4.1050

Q3: 5.27

##     0%    25%    50%    75%   100% 
## 0.1000 2.9925 4.1050 5.2700 8.1900

(D)

Steps Quantile

Q1: 6809.25

Q2: 9385.50

Q3: 12065.25

##       0%      25%      50%      75%     100% 
##   233.00  6809.25  9385.50 12065.25 18754.00

Problem 2

(A)

5 number summary for total hours of sleep per day

## [1] 0.00 7.22 8.02 8.53 9.78

(B)

This is the upper cutoff for hours asleep:

##    75% 
## 10.485

This is the lower cutoff for hours asleep:

##   25% 
## 5.265

(C)

The typical deviation from the average is 1.631983 miles per day.

## [1] 1.631983

(D)

The standard deviation is 38.76822% of the mean.

## [1] 38.76822

Problem 3

(A)

This is a box plot of the data of Dr. Melcon’s steps per day. Wednesday appears to be less active than the rest, possibly because she is lecturing for a long period of time and isn’t moving very much.

(B)

This is a box plot of the data of Dr. Melcon’s hours of sleep per day. It appears that Sunday is devoted the most time toward sleeping.

(C)

This is a histogram of the distance Dr. Melcon travels per day. The plot appears to be symmetric because the left and right tails both reach 0 at approximately the same time.

(D)

This is a histogram of the sleep Dr. Melcon gets per day. The plot is skewed to the right because the right tail frequency is higher than the left.

Appendix of Code

{r,echo = FALSE}

ErinsFitbit = read.csv(ErinsFitbit)

1A

mean(ErinsFitbit$Steps)

median(ErinsFitbit$Steps)

sd(ErinsFitbit$Steps)

1B

mean(ErinsFitbit$Asleep)

median(ErinsFitbit$Asleep)

sd(ErinsFitbit$Asleep)

1C

quantile(ErinsFitbit$Distance)

1D

quantile(ErinsFitbit$Steps)

2A

fivenum(ErinsFitbit$Asleep)

2B

Q1 = quantile(ErinsFitbit$Asleep, c(0.25))

Q3 = quantile(ErinsFitbit$Asleep, c(0.75))

upper.cutoff = Q3 + 1.5*(Q3-Q1)

lower.cutoff = Q1 - 1.5*(Q3-Q1)

upper.cutoff

lower.cutoff

2C

sd(ErinsFitbit$Distance)

2D

y = mean(ErinsFitbit$Distance)

s = sd(ErinsFitbit$Distance)

cv = ((s/y)*100)

3A

boxplot(ErinsFitbit\(Steps ~ ErinsFitbit\)Day, Data = ErinsFitbit)

3B

boxplot(ErinsFitbit\(Asleep ~ ErinsFitbit\)Day, Data = ErinsFitbit)

3C

hist(ErinsFitbit$Distance, main = “Miles Traveled per Day” ,xlab = “Miles Traveled”, freq = TRUE)

3D

hist(ErinsFitbit$Asleep, main = “Hours Slept per Day”, xlab = “Hours of Sleep”, freq = TRUE)