Background information on this question:

Observation: Hiking trails with more human foot traffic have less woody vegetation (e.g, trees) than hiking trails with less human traffic.

Null hypothesis - According to this, we assume that there is no difference in woody vegetation between the hiking trail with more human foot traffic and hiking trail with less human foot traffic. This means, that the woody vegetation on both the hiking trails is equal.

Alternate hypothesis - According to this, we assume that there is difference in woody vegetation between the hiking trail with more human foot traffic and hiking trail with less human foot traffic. This means, that the woody vegetation on both the hiking trails is NOT equal (Not same).

(Note - In the above situation, we want the Alternate hypothesis to be true, because the Observations are in the favor of Alternate hypothesis, that is the woody vegetation shows difference).

Three trails were assessed during this experiment: one where the foot traffic was measured to be 75-100 pedestrians passing by each hour, the second with only 25-50 pedestrians each hour, and one where there was only 1-10 pedestrians per hour.

10 x 10 foot quadrants were laid out at ten random locations along the edges of the trail path and the number of woody plants was counted and averaged based off of the number per species. Also it is recommended to find a site that is mostly untraveled by humans so that the impact of humans on vegetation can be clearly studied.

col 1 is the trail with the heaviest foot traffic and col 3 is the one with lowest.

Preform an appropriate statistical analysis on this dataset using using R / Rstudio.

Include any graphs and codes.

col_1

4.42997745

14.3833311

10.9245504

13.519347

5.7130304

11.8360378

8.48998957

6.4118954

6.69650711

14.9085574

9.0035583

15.0131735

5.77175258

8.62675864

6.29341937

10.1084872

12.401098

7.69408292

15.1653872

15.8350304

9.9629758

7.11236015

9.46526124

10.850238

9.89493765

12.7731377

11.6091491

10.0537892

6.02848047

12.498013

col_2

6.99779882

13.7823765

14.9555421

12.2008619

10.6451985

8.53676049

16.4005181

14.3020606

9.50019858

10.7302933

11.2724708

15.1751479

12.8806075

20.301489

10.7621695

15.7873689

11.7391437

14.669031

10.4676623

9.78825622

14.7170228

15.7800377

15.2220373

13.0585428

9.81023769

16.3094538

14.328481

13.6583221

15.8234953

14.4594935

col_3

16.904244

15.3691788

15.8624455

13.3661336

14.8453987

6.79010939

14.3563245

12.7336823

12.0577005

11.5342023

18.4611658

16.2672352

10.0058901

16.2905963

12.3026818

13.8569539

9.42367831

11.0679103

16.6182887

18.1139277

8.64116185

11.3475687

13.96335

10.9541257

8.54677046

13.0889878

13.8391244

14.4221473

13.7829428

9.19935901

\f