Explanation:
The sample mean is not always equal to the population mean but if we take more and more number of samples from the population then the mean of the sample would become equal to the population mean.
The Central Limit Theorem states that we can have a normal distribution of sample means even if the original population doesn't follow normal distribution, But we have to take a lot of samples.
Suppose a population doesn't follow normal distribution and is very skewed then we can still have sampling distribution that is completely normal if we take a lot of samples.
Answer: -6 -2
Step-by-step explanation:
Answer:
3rd quadrant
Step-by-step explanation:
- First we just convert the angle from radians to degrees
- Now that's too big, all this means is if we start rotating from the positive y-axis in a circle we will cross the starting point 2 times, 2 full circles;
- Now in which quadrant it 210 degrees?
- 0 degrees to 90 degrees is 1st quadrant
- 90 degrees to 180 degrees is 2nd quadrant
- 180 degrees to 270 degrees is 3rd quadrant
- 270 degrees to 360 degrees is 4th quadrant
- So our answer is the 3rd quadrant.
Answer:
True
Step-by-step explanation:
First two points are inverse of last two points, all points reflects each other over y = -x
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