Do these data indicate that miRNA diversity and animal complexity are negatively correlated, positively correlated, or uncorrelated? Explain

Short Answer

Expert verified

The data suggest that miRNA diversity and animal complexity are positively correlated because the correlation coefficient between the two is greater than zero.

Step by step solution

01

Outline of the study

In the study, scientists used two variables: the number of miRNAs and an average number of cell types to determine the relationship between miRNA diversity and animal complexity.

To establish the relationship between the two variables, researchers calculated the correlation coefficient.

02

Correlation coefficient (r)

The correlation coefficient reflects the magnitude and direction of a linear relationship between two variables. The correlation coefficient is calculated using the following formula:

r=1n-1(xi-x)¯(yi-y¯)sxsy

where x and y are the two variables, and n is the number of observations.

r ranges from -1 to 1. The value of rmore than 1 indicates a positive relationship, whereas r less than 1 indicates a negative relationship between the two variables.

03

Correlation between miRNA diversity and animal complexity

The r calculated using the data from the study is 0.957. Since the value of r is greater than zero, the value indicates that miRNA diversity and animal complexity are positively correlated.

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Most popular questions from this chapter

Next, we’ll calculate the mean and standard deviation for each variable. (a) The mean( x¯ ) is the sum of the data values divided by n, the number of observations:. Calculate the mean number of miRNAs (x¯ ) and the mean number of cell types ( x-) and enter them in the data table (for y¯, replace each x in the formula with a y). (b) Next, calculate ( xi-x¯) and ( yi-y¯) for each observation, recording your results in the appropriate column. Square each of those results in the appropriate column. Square each of those results to complete the (xi-x)¯2and (yi-y)¯2 columns; sum the results for those columns. (c) The standard deviation, s, which describes the variation found in the data, is calculated using the following formula:

sx=1n-1(xi-x¯)2

Calculate sx and sy by substituting the results in (b) into the formula for the standard deviation.

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