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

Linear Regression Analysis, Using LifeSpan to predict Gestation

(3a) Use R/RStudio to conduct a linear regression to determine if LifeSpan (independent variable) predicts Gestation (dependent variable) using the dataset above.

Fit a linear regression using lm(). Paste your code and output below.

(3b) Using your output from (3a), what is the estimate of the slope of the linear regression? What is your statistical conclusion and interpretation of the slope estimate when using alpha = 0.05?

(3c) Interpret the adjusted R-squared value from your output from (3a). What does this value represent?

(3d) Use your output from (3a) to write the regression equation.

(3e) Use your regression equation from (3d) to predict the Gestation time in mammals that have a LifeSpan = 7, 32, and 68.

(3f) Plot the relationship between LifeSpan and Gestation using plot(). Plot LifeSpan on the x-axis and Gestation on the y-axis. Add appropriate axis labels and a main title, and a color of your choice.

After making this plot, you can add a line of best fit based on your linear regression using the abline() function in R/RStudio:

abline(object name)

where object name is the object where your linear regression model was stored when using lm() in (3a). Paste your plot with your line of best fit below.