To estimate the mean of a population with unknown
distribution shape and unknown standard
deviation, we take a random sample of size 64. The sample
mean is 22.3 and the sample standard deviation is 8.8. If we wish
to compute a 92% confidence interval for the
population mean, what will be the t multiplier? (Hint: Use
either a Probability Distribution Graph or the Calculator from
Minitab.)
Which is false?
A. A statistic is used to estimate an unknown parameter
B. Non sampling errors can be present even when a census is
taken
C. Increase sample size to reduce bias
D. Margin of error will get smaller when you increase sample
size
E. Variability describes how spread out the values of the
sample statistic are when we take many samples.
Why
is
normal
distribution
so
important
in the discipline of Statistics?
Examine its development
and usage to answer the question. Write and essay and explaine this
question. Max 2 pages.
Suppose X1, X2, ..., Xn is a random sample from a Poisson
distribution with unknown parameter µ.
a. What is the mean and variance of this distribution?
b. Is X1 + 2X6 − X8 an estimator of µ? Is it a good estimator?
Why or why not?
c. Find the moment estimator and MLE of µ.
d. Show the estimators in (c) are unbiased.
e. Find the MSE of the estimators in (c).
Given the frequency table below:
X 0...
The data below is suspected to be part of a normal distribution
- unknown mean and variance. perform goodness of fit test to
confirm if the data really comes from a normal distribution.
a) Estimate the normal distribution:
b) Partition the range of the data into 4 mutually exclusive
intervals.
c) Calculate the relative frequency of each interval you
selected using the observed data.
d)
Calculate the theoretical probabilities of the intervals you
selected assuming the data came from a...
A population parameter has a normal distribution and has a mean
of 45 and variance of 15. From
this population a sample is selected with a size of 19 and the
variance of the sample is 17. Does
this sample support the population variance? Evaluate.
Empolyee
age
1
25
2
32
3
26
4
40
5
50
6
54
7
22
8
23
age
Mean
34
Standard Error
4.444097209
Median
29
Mode
#N/A
Standard Deviation
12.56980509
Sample Variance
158
Kurtosis
-1.152221485
Skewness
0.767648041
Range
32
Minimum
22
Maximum
54
Sum
272
Count
8
Confidence Level(95.0%)
10.50862004
Describe the point estimate, normal probability distribution, and standard normal probability distribution in details, in 4 paragraphs.
True of False
the sampling distribution of a parameter is the distribution of
the parameter value if repeated random samples are obtained
The central lmit theorem is important in statistics because for
a large random sample, it says the sampling distribution of the
sample mean is approximately normal