Instructions:

Write your answers and paste all outputs onto this document

READ questions carefully and answer all parts.

Cut and paste R code and output into this document and type any answers and explanations

required. Note that the questions are in bold, as to distinguish them easily from your answers.

Keeping your answers well organized will help me grade them quickly and accurately.

This exam was not designed to be tricky, but may take some time.

You're using only the "Carnivores_data.csv" dataset for all questions.

SAVE both your R output and your exam document early and often! SAVE the exam document

as "Lastname_FINAL_Practical_Biol215.doc"

When you are done, submit both your script and this filled out document to Canvas. (Separate

submissions)

Regardless of significance, report and interpret all of the required analyses.

GOOD LUCK!

As a reminder, the 5 steps for hypothesis tests are as follows:

1. State the research question and appropriate null (H0) and alternative (HA)

hypotheses

2. Explore the data graphically (i.e. make an appropriate graph)

3. Select the appropriate test (correlation, regression, independent t-test,

dependent t-test, ANOVA, or Chi-Squared

4. Calculate and report the necessary test statistics, degrees of freedom, and p-

value (copy the R code and the model output in the appropriate location of the

word file)

5. Interpret the results: test statistic(s)/p-value in terms of H0 and draw conclusions

about your data

Description:

A biologist studies the response of carnivores to wildfires. They setup infrared

wildlife cameras at

n = 100

nature preserves throughout San Diego County. Cameras were set in

areas that burned in the 2003 as well as control areas that did not burn

(variable=FIRE_HISTORY). They classified each site based on the level of development

(variable=HABITAT) as well as the dominant vegetation (variable = VEGETATION). They

were able to measure the density of two common carnivores (Striped Skunk and Coyote). They

were able to document the presence or absence of two less common species (Bobcat and Gray

Fox).

Description of Variables:

Variable

Type

Description or units

HABITAT

Categorical

Urban, Suburban, Rural

FIRE_HISTORY

Categorical

Burned, Unburned

FIRE_HISTORY_BINARY Categorical

0 = Absence, 1 = Absence

VEGETATION

Categorical

Grasses, Shrubs

PRESERVE_SIZE

Continuous

units = acres

SKUNK_DENSITY

Continuous

units = animals per square km

COYOTE_DENSITY Continuous

units = animals per square km

BOBCAT_PRESENCE

Categorical

Present, Absent

GRAYFOX_PRESENCE

Categorical

Present, Absent

Data (partial):

1. Does skunk density (SKUNK_DENSITY) affect coyote density (COYOTE_DENSITY)?

What is coyote density when skunk density is 10.5 skunks/km

2

?

2. Is preserve size (PRESERVE_SIZE) correlated with skunk density

(SKUNK_DENSITY)? Preserve size is independent. Skunk density is dependent.

3. Does mean skunk density (SKUNK_DENSITY) differ between sites with different

dominant vegetation (VEGETATION)?

4. Is there a difference in coyote density between 2003 (COYOTE_DENSITY) and 2020

(COYOTE_DENSITY_2020) in

a) burned (FIRE_HISTORY = BURNED or FIRE_HISTORY_BINARY=1) and

b) unburned (FIRE_HISTORY = UNBURNED or FIRE_HISTORY_BINARY=0)

preserves?

*Note that this will require you to run a test both for part a) and part b).

** For the boxplot

s

, use the format boxplot(x,y). Remember to include all labels.

*** Hint: You will be comparing coyote density in the

same

preserves over time.

5. Does mean preserve size (PRESERVE_SIZE) differ among habitats (HABITAT)?

6. Is there an association between the fire history (FIRE_HISTORY) and bobcat presence

(BOBCAT_PRESENCE) at the sites? Fire history is independent. Bobcat presence is

dependent.

7. Enter the dataset below into R to answer the

question: Is there a difference in % algal cover

(algae_cover) among Low (24 degrees C), Medium

(26 degrees C), and High (30 degrees C)

temperatures (temp)?

algae_cover

temp

34.16

Low

54.84

Low

66.91

Low

49.47

Low

64.72

Low

36.6

Low

35.14

Low

41.93

Low

42.55

Medium

47.57

Medium

59.88

Medium

37.31

Medium

44.73

Medium

55.16

Medium

60.24

Medium

47.19

Medium

67.22

High

67.98

High

67.96

High

60.12

High

68.02

High

84.97

High

73.7

High

72.02

High

All numbers for copy and paste:

34.16, 54.84, 66.91, 49.47, 64.72, 36.6,

35.14, 41.93, 42.55, 47.57, 59.88, 37.31,

44.73, 55.16, 60.24, 47.19, 67.22, 67.9