Construct a 95% confidence interval estimate for the mean GPA .Change the interval above to a 99% confidence interval estimate for the mean GPA.If you want this 99% confidence interval estimate to be no wider than ± 0.1, by how much must you increase the sample size?IDFemaleMajorGPA1142.5372023.6483132.9814022.6835123.2346132.4677113.3848133.5559023.26310113.71111151.97012143.40613012.52314031.75015163.19116122.79517012.60618052.39719163.79120043.49021032.42122053.93723052.89024162.24625123.37126153.11427013.08428052.70329133.04530011.94831112.71732161.99633132.87034052.98635013.39336122.74037162.49938143.69539142.66440152.30641133.02242162.77643152.17544023.82845063.41046042.33047053.97848133.50349143.25350122.215

The aim is to compute 95% CI for mean ,99% CI for mean and find sample size.

Answered: Construct a 95% confidence interval…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Construct a 95% confidence interval estimate for the mean GPA .
Change the interval above to a 99% confidence interval estimate for the mean GPA.
If you want this 99% confidence interval estimate to be no wider than ± 0.1, by how much must you increase the sample size?

ID	Female	Major	GPA
1	1	4	2.537
2	0	2	3.648
3	1	3	2.981
4	0	2	2.683
5	1	2	3.234
6	1	3	2.467
7	1	1	3.384
8	1	3	3.555
9	0	2	3.263
10	1	1	3.711
11	1	5	1.970
12	1	4	3.406
13	0	1	2.523
14	0	3	1.750
15	1	6	3.191
16	1	2	2.795
17	0	1	2.606
18	0	5	2.397
19	1	6	3.791
20	0	4	3.490
21	0	3	2.421
22	0	5	3.937
23	0	5	2.890
24	1	6	2.246
25	1	2	3.371
26	1	5	3.114
27	0	1	3.084
28	0	5	2.703
29	1	3	3.045
30	0	1	1.948
31	1	1	2.717
32	1	6	1.996
33	1	3	2.870
34	0	5	2.986
35	0	1	3.393
36	1	2	2.740
37	1	6	2.499
38	1	4	3.695
39	1	4	2.664
40	1	5	2.306
41	1	3	3.022
42	1	6	2.776
43	1	5	2.175
44	0	2	3.828
45	0	6	3.410
46	0	4	2.330
47	0	5	3.978
48	1	3	3.503
49	1	4	3.253
50	1	2	2.215

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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