What is the output of the following code that performs a one-way ANOVA test on three groups of data?
from scipy.stats import f_oneway group1 = [5, 7, 8, 6, 9] group2 = [10, 12, 11, 13, 12] group3 = [7, 8, 7, 6, 7] stat, p = f_oneway(group1, group2, group3) print(round(stat, 3), round(p, 3))
Recall that the F-statistic measures variance between groups relative to variance within groups.
The F-statistic is approximately 10.8 and the p-value is very small (close to 0), indicating significant differences between groups.
How many groups are being compared in this ANOVA test?
from scipy.stats import f_oneway # Data groups A = [4, 5, 6] B = [7, 8, 9] C = [10, 11, 12] D = [13, 14, 15] stat, p = f_oneway(A, B, C, D) print(len([A, B, C, D]))
Count the number of lists passed to the function.
There are 4 groups: A, B, C, and D.
What error does the following code produce?
from scipy.stats import f_oneway group1 = [5, 6, 7] group2 = 10, 11, 12 stat, p = f_oneway(group1, group2) print(stat, p)
Check the data types of the groups passed to f_oneway.
group2 is a tuple, which is a sequence, so f_oneway accepts it without error.
You run an ANOVA test and get F-statistic = 2.5 and p-value = 0.12. What does this mean about the groups?
Remember the p-value threshold for significance is usually 0.05.
A p-value of 0.12 is greater than 0.05, so we do not reject the null hypothesis that group means are equal.
Which of the following is NOT an assumption required for a valid one-way ANOVA test?
Think about the type of data ANOVA analyzes.
ANOVA requires the dependent variable to be continuous, not categorical.