You surveyed 350 students, out of which 182 were unsure.
The calculation gives: 182/350 = 0.52, indicating that 52% of the students were uncertain.
Now, apply this percentage to the national survey total:
50,000 x 0.52 = 26,000
The final result is 26,000 students who wouldn't know.
Answer:
40%
Step-by-step explanation:
According to the provided information:
The likelihood of rain on Saturday stands at 25%.
P(Sunday)=25%=0.25
If it rains on Saturday, the probability of rain on Sunday rises to 50%.
P(Sunday|Saturday)=50%=0.5
If it does not rain on Saturday, the chance of Sunday rain is 25%.
P(Sunday|No Rain on Saturday)=25%=0.25
We aim to find the probability of rain on Saturday given that it rained on Sunday, P(Saturday|Sunday).
P(No rain on Saturday)=1-P(Saturday)=1-0.25=0.75
Using Bayes' theorem for conditional probabilities:
P(Saturday|Sunday)=
=
=0.4
Thus, there is a 40% likelihood that it rained on Saturday given the conditions on Sunday.
Response:
/??
Detailed explanation of the process:
Answer:
A correlation coefficient of +1 or -1 reflects a perfect linear relationship, but a 0.94 indicates a strong positive correlation between the aspen leaf's length and surface area, though not guaranteeing linearity.
Step-by-step explanation:
The correlation coefficient (r) ranges between +1 and −1, where +1 means perfect positive correlation, −1 means perfect negative correlation, and 0 means no correlation.
The closer r is to ±1, the stronger the correlation. Generally, values between 0.7 and 1, or −0.7 and −1, indicate a significant correlation.
While 0.94 shows a strong direct association between the leaf's length and surface area, it does not definitively prove a linear relationship is the best fit.
