Formal Report Eco Lab.pdf

Data Management Leur Eidrian Carl Ladera Matt Janzel Lanto Johnny Hill Salaysay

Abstract Studies involve the collection of data. This data is then put through statistical tests to determine the conclusion of the study. In this exercise, the correlation between the ppm of pesticides and the number of guppies was identified. It was found out that it had a strong negative correlation. Introduction All ecological studies involve collecting data (Smith & Smith, 2015). Data can be classified as either categorical or numerical. Categorical data are qualitative which involves observations based on the features, color, etc. It can be subdivided into two categories, nominal and ordinal. Nominal data are unordered categories while ordinal data are ordered categories. If only two observations exists such as the presence or absence, then the categorical data is referred to as binary. Numerical data are measured based on quantity like height, length, and weight. Numerical data can be subdivided into two categories, discrete and continuous. Discrete data can only contain certain values while continuous data can contain any values. Data are put through statistical tests to determine if there are effects or trends in the experiment. Statistical tests

provide the grounds whether to accept or reject a hypothesis. Statistical tests also help in providing a conclusion. Statistical tests come in two categories, parametric and non-parametric. In parametric stats, it involves using data from a population that follows a probability distribution. In non-parametric, it involves data that follows no probability distribution and often arranged in ranks. Spearman’s rank correlation coefficient is a nonparametric measure of rank correlation. It determines the strength and direction of the monotonic relationship between two variables.

The value of the correlation coefficient, ⍴, can range between -1, 0, 1. ⍴ < 0 signifies negative correlation, ⍴ = 0 signifies no correlation, and ⍴ > 0 signifies positive correlation. The distance of ⍴ to -1 or 1 shows the strength of correlation.

Methodology A problem was given to the students in order for them to determine what statistical test to use. Problem A DENR official was alerted to the presence of a leak in the pipeline of a pesticide factory that was slowly releasing pesticide by-products into a nearby creek. Although the pesticide company issued a statement that the leaked material was non-toxic, the official went to the site and collected water samples from the start of the leak upstream all the way to the end of the creek, at 10 meter intervals. He also counted the number of guppies at each collecting site. Each water sample was analyzed for the presence and amount of the pesticide by-product at the lab. The results obtained are as follows: TABLE 1: Amount of pesticide by-product and the number of guppies Amount of the Number pesticide Guppies by-product (ppm) A

170

of

D

90

7

E

80

3

F

75

7

G

55

8

H

55

10

I

42

12

J

28

7

K

22

30

L

20

40

M

17

42

Methods The problem showed non-parametric values and a test for correlation was implied. The statistical test Spearman’s rank was used to identify the relationship between the amount of pesticide and the number of guppies since it uses non-parametric data and is used to identify the correlation.

4

B

145

2

C

145

5

Ho = between the guppies. Ha = between the guppies.

There is no correlation ppm of pesticide and the There is a correlation ppm of pesticide and the

Results and Discussion TABLE 2: Statistical analysis

ppm (x)

A 170

No. of gup pies (y)

Rank x

Ran ky

d

d​2

3

10

100

1

10. 5

110 .25

4

13

2

11. 5

5

11. 5

4

7.5

56. 25

D 90

7

10

6

4

16

E 80

3

9

2

7

49

F 75

7

8

6

2

4

8

-2. 5

6.2 5 12. 25

B 145 C 145

G 55

8

6.5

H 55

10

6.5

9

-3. 5

I

42

12

5

10

-5

25

J

28

7

4

6

-2

4

K 22

30

3

11

-8

64

L

20

40

2

12

-10

100

M 17

42

1

13

-12

144

T o t a l 944

177

91

91

0

691

Spearman rank correlation is a non-parametric test that is used to measure the degree of association between two variables. The test does not carry any assumptions about the distribution of the data and is the appropriate correlation analysis when the variables are measured on a scale that is at least ordinal. The test also measures the strength and direction of monotonic association between two variables. Monotonicity is "less restrictive" than that of a linear relationship. A monotonic relationship is a relationship that does either of the two: (1) as the value of one variable increases, so does the value of the other variable; or (2) as the value of one variable increases, the other variable value decreases.

Conclusion Since ρ = -0.9, reject the Ho. Therefore, there is a very strong negative correlation between the ppm of pesticide and the number of guppies. References Smith, T. M., & Smith, R. L. (2015). Elements of ecology​. Harlow (Essex: Pearson.)