I just want to make sure what I'm calculating this right. The data I got for one time point are 6 and 23 I know the equation for chi^2 is
Calculating Chi Squared - Catherine, Friday, October 28, 2011 at 8:15pm
I did a biology experiment where I need to analyze the statistical significance of betweeen a data set. My experiment consisted of measuring the effects in photosynthesis and cellular respiration by exposing solutions with leaf discs to different light wavelength. For the statistical significance, I have to compare data I got with blue and green light to white light. The amount of discs for the time point I chose for blue was: 3, white: 23 and for green: 6 I'm supposed to use the chi square method to compare this values and I got 13 for my expected value between blue and white and 8.5 between green and white and then a chi square of 7.69 for blue/white and of 24.735 for green/white. Are those values right? I have to use this method for many other time points but if I have this one right probably I have the others right, same if I have it wrong, if they are wrong, please explain how to calculate it.
The equation I used waschi^2= (obs-exp)^2/exp I calculated my expected value by taking the average of the ones I have. Will my observed value be any of the two I have, or do I have the add them and that will be my observed value?
To calculate the chi-squared value, you need to compare the observed values with the expected values. In this case, you have the observed values for blue and green light as 6 and 23, respectively. You also have the expected values for blue and green light compared to white light as 13 and 8.5.
To calculate the chi-squared value, you need to follow these steps:
1. Calculate the difference between the observed and expected values for each group. For blue light, the difference would be 6 - 13 = -7. For green light, the difference would be 23 - 8.5 = 14.5.
2. Square the differences for each group. (-7)^2 = 49 and (14.5)^2 = 210.25.
3. Divide the squared differences by the expected values. For blue light, 49/13 = 3.77. For green light, 210.25/8.5 = 24.74.
4. Add up the calculated values for each group. 3.77 + 24.74 = 28.51.
The calculated chi-squared value for this comparison would be 28.51. Now, let me explain how you can determine if this value is significant or not.
To determine the statistical significance of the chi-squared value, you need to compare it to a critical value from the chi-squared distribution table. The critical value is based on the degree of freedom, which is calculated as (number of categories - 1).
In this case, since you are comparing blue/green to white light, you have 2 categories. Therefore, the degree of freedom would be 2 - 1 = 1.
Now, you can look up the critical value for a chi-squared distribution with 1 degree of freedom at your desired significance level (e.g., 0.05). Let's assume the critical value is 3.84.
If the calculated chi-squared value (28.51) is greater than the critical value (3.84), then you can conclude that there is a significant difference between the observed and expected values. Otherwise, if the calculated value is less than the critical value, you would not have enough evidence to reject the null hypothesis of no difference.
In summary, based on the calculated chi-squared value of 28.51, it appears that there is a significant difference between the observed and expected values for the comparison of blue/green to white light. Please note that you should check the chi-squared distribution table for the specific critical value based on your desired significance level and degree of freedom.
I hope this explanation helps you understand how to calculate and interpret the chi-squared value. If you have any further questions, feel free to ask!