True/False portion: 1) The sample mean x is a point estimate for the population mean µ. In tests of significance, it is possible to reject the null hypothesis and yet still have a significant result. 2) If one rejects the null hypothesis at the 5% level, then there is a 5% chance 3) that you made the wrong decision.
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
![True/False portion:
1)
The sample mean x is a point estimate for the population mean µ.
2)
In tests of significance, it is possible to reject the null hypothesis and yet
still have a significant result.
3)
that you made the wrong decision.
If one rejects the null hypothesis at the 5% level, then there is a 5% chance
4)
In the p-value approach, if p-value>a (the level of significance) we reject
the null hypothesis.
If you fail to reject the null hypothesis at the 5% level, then the probability
5)
that you are wrong is always 5%.
A wider confidence interval gives a greater level of confidence than a
6)
narrower one (when working with the same data).
If the sample mean of a data set is 3.2 then the population mean must also
7)
be 3.2
8)
As the sample size (n) increases, the standard deviation of x from that
sample decreases, this assumes the standard deviation is positive..
The level of significance is the probability of rejecting the null hypothesis
9)
when the null hypothesis is true.
10)
even with the same level of significance, hypotheses and data?
Classical hypothesis testing can give different decisions than the P-value approach](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F3bf7da54-5138-4b57-a0f9-aec30fa8e8cf%2F5ff9caa2-f671-4f60-b95b-62b0d88cfe68%2Fuuilqkf_processed.jpeg&w=3840&q=75)
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