In R/RStudio using the read.csv() function: sleep <- read.csv("sleep.csv")

(1a) Paste your pair-wise scatterplot below using plot(sleep)

(1b) Examine the pair-wise scatterplot in (1a). Which pair of variables, if any, would you expect to be negatively correlated? Which pair of variables, if any, would you expect to be positively correlated. Justify your response.

(1c) Consider the correlation coefficient, r, between all possible pairs of the variables within the sleep dataset. Write the null and alternative hypotheses for r in a correlation analysis.

(1d) Now, conduct a correlation analysis between all possible pairs of the variables within the sleep dataset. Paste your code and output below for each pair of variables.

(1e) Using the output from cor.test in (1d), what is the estimate of the correlation coefficient, r, for each pair of variables?

(1f) Using alpha = 0.01 and the output from (1d), what is your statistical conclusion and interpretation for each pair of variables?

sleep.csv (Use this data to answer the above questions):

TotalSleep LifeSpan Gestation 3.3 38.6 645 8.3 4.5 42 12.5 14 60 16.5 6 25 3.9 69 624 9.8 27 180 19.7 19 35 6.2 30.4 392 14.5 28 63 9.7 50 230 12.5 7 112 3.9 30 281 10.3 11 117 3.1 40 365 8.4 3.5 42 8.6 50 28 10.7 6 42 10.7 10.4 120 6.1 34 202 18.1 7 32 6.5 28 400 3.8 20 148 14.4 3.9 16 12 39.3 252 6.2 41 310 13 16.2 63 13.8 9 28 8.2 7.6 68 2.9 46 336 10.8 22.4 100 7.8 16.3 33 9.1 2.6 21.5 19.9 24 50 8 100 267 10.6 11 30 11.2 15 45 13.2 3.2 19 12.8 2 30 19.4 5 12 17.4 6.5 120 5.3 23.6 440 17 12 140 10.9 20.2 170 13.7 13 17 8.4 27 115 8.4 18 31 12.5 13.7 63 13.2 4.7 21 9.8 9.8 52 9.6 29 164 6.6 7 225 5.4 6 225 2.6 17 150 3.8 20 151 11 12.7 90 10.3 3.5 15 13.3 4.5 60 5.4 7.5 200 15.8 2.3 46 10.3 24 210 19.4 3 14 15.3 13 38