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1. |
Generate 5 samples of sizes 5, 7, 6, 7 and 8 from normal
populations with means 45, 40, 47, 43 and 38 respectively. While the
standard deviations of these distributions are 4, 6, 8, 7 and 9
respectively. Test the equality of means. |
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2. |
Test that correlation coefficient between scores on verbal
and math sections of SAT test is zero for data in the dataset grades.mtw.
Also estimate the expected GPA for a student whose verbal score is 690 and
math score is 750. |
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3. |
Use the data set bears.mtw to find the minimum and maximum
length, mean weight and median age by gender of the bears, also test the
equality of mean length for male and female bears. Check whether the
variances are equal or not before testing the equality of means and act
accordingly. |
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4. |
Construct x-bar and R charts for the dataset brakes.sav. |
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5. |
Test the equality of means for the following experiment of
maize yield for different varieties. Use LSD or DMR test if necessary. |
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Treatments |
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Blocks |
A |
B |
C |
D |
E |
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I |
12.5 |
5 |
20.5 |
59.5 |
38 |
|
II |
12 |
6 |
18 |
62 |
31 |
|
III |
11 |
5.5 |
16 |
53 |
26 |
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IV |
12 |
5.5 |
17 |
56 |
30.5 |
|
V |
16.5 |
9 |
28 |
67.5 |
45 |
|
VI |
16.5 |
9 |
27 |
78 |
49 |
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6. |
Use MINITAB to test that the mean of the Metals is equal to
50 in Employ.MTW work sheet. |
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7. |
Test the equality of mean yeild for field 2 and 4 in
Alfalfa.MTW worksheet. |
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8. |
Find the mean, median, quartiles and standard deviation for
sample data set icu.mtw. Calculate z-scores for the variable. Find the
mean, standard deviation and variance of the resultant z-scores. |
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9. |
Generate two datasets of 1000 values each from two
different normal distributions N(10,5) and N(12, 3). Draw two random
samples of sizes 8 and 10 from these datasets respectively and test the
significance of the equality of means. |
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10. |
Use MINITAB to perform one sample z test to test that
population mean is 70, using the following sample information, taken from
a population with variance = 25, mean=60. |
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11. |
Perform regression analysis to predict trade on the basis
of other two variables on sample dataset Employ.MTW. Also use matrix
approach. |
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12. |
Test equality of means for the following experiment of
wheat yield for different varieties.
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Blocks |
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I |
A (8) |
B (5.3) |
C (4.1) |
D (5) |
E (16) |
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II |
D (6.8) |
A (4.9) |
B (4.1) |
C (3.2) |
E (18) |
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III |
B (6.3) |
E (16) |
C (4.7) |
D (4.0) |
A (5.0) |
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IV |
C (5.7) |
D (3.3) |
E (25) |
A (4.0) |
B (4.2) |
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V |
E (18) |
C (4.7) |
A (4.2) |
D (6.6) |
B (6.2) |
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13. |
Using weight measurements in dataset bears2.MTW, create a
new variable by grouping these values into five subintervals [0, 100),
[100, 200), [200, 300), [300, 400) , [400, 500). Calculate the frequency
distribution, the relative frequency distribution, and the cumulative
distribution of this ordered categorical variable. |
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14. |
Simulate tossing of a fair coin 1000 times. Prepare its
frequency distribution. Also test that proportion of heads is equal to
that of tails. |
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15. |
Simulate tossing of a biased coin, such that chance of
getting a head is twice that of a tail, 1000 times. Prepare its frequency
distribution. Also test that proportion of heads is twice that of tails. |
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