Natalie conducted a study on the effects of triclosan on three algae populations. she collected an algae sample from three different ponds, counted the number of algae cells present in the sample, and then exposed them to a 5 ppm aqueous solution of triclosan and re-counted the number of algae cells in each sample. using a paired t-test, she obtained a p-value of 0.083 when comparing the original algae population sizes to the population sizes after exposure to triclosan. natalie concluded that triclosan is toxic to algae because her data for the three samples showed a trend toward a reduction in population size. what could natalie do to show a statistically significant effect of triclosan on algae population size

She could collect larger samples from the 3 ponds she used or include more ponds in her sample.

Step-by-step explanation:

First we need to define what statistical significance is: Statistical significance means that the relationship between two or more variables is caused by something other than chance. When the researcher conducts a hypothesis testing and gets a p-value of 5% or lower, usually it means that the test has statistical significance.

In the problem, Natalie got a p-value of 0.083 which is 8%. therefore, her test doesn't show a statistically significant effect of triclosan on algae population size.

To show a statistically significant effect, Natalie would need to get a p-value of 5% or lower. To achieve this, she could collect larger samples from the 3 ponds she used or include more ponds in her sample. This way, with a larger sample she could get a p-value that is statistically significant on the effect of triclosan on algae population size.

For the same numerator, bigger denominators mean smaller fractions (if everything's positive).  2/3 is bigger than all the other ones , which are 1/2 or less.

2/3, 1/2, 1/4, 1/5, 1/6