Assume you toss a die 20 times and get the following values:
1,1,3,5,6,3,2,1,3,6,5,2,3,6,5,4,2,3,4,1
Use a Chi...
Assume you toss a die 20 times and get the following values:
1,1,3,5,6,3,2,1,3,6,5,2,3,6,5,4,2,3,4,1
Use a Chi square test to check if it is a fair die or
no.
P-value is 0.05, use excel and consider the following
cases.
1- number of bins is 6
2-number of bins is 3
A six-sided die is thrown 50 times. The numbers of occurrences
of each face are shown...
A six-sided die is thrown 50 times. The numbers of occurrences
of each face are shown below.
Face
1
2
3
4
5
6
Count
12
9
8
9
7
5
Can you conclude that the die is not fair? Determine
the type of test should be used in this situation and the test
statistic.
a.
Goodness of Fit,
b.
Goodness of Fit,
c.
Two sample z-test for proportions, z = 1.138
d.
One sample z-test for proportions, z = 1.391...
A six-sided die is rolled 120 times. Fill in the expected
frequency column. Then, conduct a...
A six-sided die is rolled 120 times. Fill in the expected
frequency column. Then, conduct a hypothesis test at the 5% level
to determine if the die is fair. The data below are the result of
the 120 rolls. (Enter exact numbers as integers, fractions, or
decimals.)
Face Value
Frequency
Expected
Frequency
1
14
?
2
33
?
3
15
?
4
14
?
5
30
?
6
14
?
Part (a)
State the null hypothesis. Choose 1 or 2...
A six-sided die is rolled 120 times. Fill in the expected
frequency column. Then, conduct a...
A six-sided die is rolled 120 times. Fill in the expected
frequency column. Then, conduct a hypothesis test at the 5% level
to determine if the die is fair. The data below are the result of
the 120 rolls. (Enter exact numbers as integers, fractions, or
decimals.)
Face Value
Frequency
Expected Frequency
1
14
?
2
32
?
3
15
?
4
15
?
5
30
?
6
14
?
Part (a)
State the null hypothesis. Choose 1 or 2...
For the data in the table below, assume a uniform distribution.
Estimate the parameters for this...
For the data in the table below, assume a uniform distribution.
Estimate the parameters for this distribution, and perform a Chi
Squared goodness of fit test on what is assumed to be a uniform
distribution.
6.40
4.39
6.86
5.24
4.01
5.54
4.50
5.69
5.85
5.42
5.94
6.78
6.52
5.82
6.46
4.65
4.20
5.25
6.58
4.73
6.53
4.99
5.90
5.51
6.50