Think about a bush in your back yard. Is it alive according to the characteristics of life? Why or why not?
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The change in internal energy of this gas sample is equal to: c. 715 J.
<u>Given the following data:</u>
- Quantity of heat = 874 J.
- Work done = 159 J.
Mathematically, the the First Law of Thermodynamics is given by this formula:
Where;
is the change in internal energy.
- Q is the quantity of heat.
- W is the work done.
Substituting the parameters into the formula, we have;
Change in internal energy (ΔH) = 715 Joules.
Read more on enthalpy change here: brainly.com/question/11628413
Two traits that we are examining are the color (purple/white) and the smoothness.
In our sample, we have 135 individuals ( 75 +28+24+8= 135).
Since we know that expected ratio of a dihybrid cross, is <span>9:3:3:1 we can calculate what is the expected values of each phenotype is.
So, for the white wrinkled phenotype, we expect that there will be one-sixteenth of the whole sample ( there are 16 parts of the whole sample 9+3+3+1=16).
So, we multiply the whole sample- 135 with one-sixteenth (or </span>0.0625) and get 8,4375.
When you calculate the values for all phenotypes you get results shown in the attached excel table.
When you have your expected and experimental values you compare them with a chi-square test. (The test determines if the difference between the expected and experimental results is statistically significant).
In our sample, we have 135 individuals ( 75 +28+24+8= 135).
Since we know that expected ratio of a dihybrid cross, is <span>9:3:3:1 we can calculate what is the expected values of each phenotype is.
So, for the white wrinkled phenotype, we expect that there will be one-sixteenth of the whole sample ( there are 16 parts of the whole sample 9+3+3+1=16).
So, we multiply the whole sample- 135 with one-sixteenth (or </span>0.0625) and get 8,4375.
When you calculate the values for all phenotypes you get results shown in the attached excel table.
When you have your expected and experimental values you compare them with a chi-square test. (The test determines if the difference between the expected and experimental results is statistically significant).