The dataset Silverweight.csv contains data collected "The Absolute Isotopic Abundance and Atomic Weight of a Reference Sample of Silver" from NBS Journal of Research, 87, pp. 9-19. It compared the Atomic weight of silver (in Aus) as measured by 2 different instruements. (a) Perform a hypothesis test to determine if their is evidence for the existence of bias or improper calibration in one of the instruments, use a = 0.01. (b) Construct a 99% confidence interval for the difference in the estimated atomic weights. (c) Evaluate the assumptions of your hypothesis test in a). (d) Compute an appropriate effect size for the difference in estimates between the two techniques. (e) Estimate the difference in calibrations (effect size as measured as difference of the means) that you have a 90% chance of detecting for this dataset. Use sp = 1.7 x 10-5 Au of the sample as approximately equal to o and a sample size of 24 in each group. - (f) What sample size would you need in order to have an 80% chance of detecting a calibration difference of 0.8 x 10-5 Au between the two machines. (g) Construct a plot to show the mean silver weight measured on both instruments.
The dataset Silverweight.csv contains data collected "The Absolute Isotopic Abundance and Atomic Weight of a Reference Sample of Silver" from NBS Journal of Research, 87, pp. 9-19. It compared the Atomic weight of silver (in Aus) as measured by 2 different instruements. (a) Perform a hypothesis test to determine if their is evidence for the existence of bias or improper calibration in one of the instruments, use a = 0.01. (b) Construct a 99% confidence interval for the difference in the estimated atomic weights. (c) Evaluate the assumptions of your hypothesis test in a). (d) Compute an appropriate effect size for the difference in estimates between the two techniques. (e) Estimate the difference in calibrations (effect size as measured as difference of the means) that you have a 90% chance of detecting for this dataset. Use sp = 1.7 x 10-5 Au of the sample as approximately equal to o and a sample size of 24 in each group. - (f) What sample size would you need in order to have an 80% chance of detecting a calibration difference of 0.8 x 10-5 Au between the two machines. (g) Construct a plot to show the mean silver weight measured on both instruments.
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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By using r studio please solve parts a-g
Transcribed Image Text:The dataset *Silverweight.csv* contains data collected on "The Absolute Isotopic Abundance and Atomic Weight of a Reference Sample of Silver" from NBS Journal of Research, 87, pp. 9-19. It compared the atomic weight of silver (in Aus) as measured by 2 different instruments.
**(a)** Perform a hypothesis test to determine if there is evidence for the existence of bias or improper calibration in one of the instruments; use α = 0.01.
**(b)** Construct a 99% confidence interval for the difference in the estimated atomic weights.
**(c)** Evaluate the assumptions of your hypothesis test in (a).
**(d)** Compute an appropriate effect size for the difference in estimates between the two techniques.
**(e)** Estimate the difference in calibrations (effect size as measured as difference of the means) that you have a 90% chance of detecting for this dataset. Use \( s_p = 1.7 \times 10^{-5} \text{Au} \) of the sample as approximately equal to σ and a sample size of 24 in each group.
**(f)** What sample size would you need in order to have an 80% chance of detecting a calibration difference of \( 0.8 \times 10^{-5} \text{Au} \) between the two machines?
**(g)** Construct a plot to show the mean silver weight measured on both instruments.
Transcribed Image Text:The data consists of two columns labeled "Instrument" and "AgWt." Each row represents a measurement with a corresponding instrument number and weight. The data is divided into two sections categorizing measurements under two distinct instrument numbers: 1 and 2.
**Instrument Number: 1**
- 107.8681568
- 107.8681465
- 107.8681572
- 107.8681785
- 107.8681446
- 107.8681903
- 107.8681526
- 107.8681494
- 107.8681616
- 107.8681587
- 107.8681519
- 107.8681486
- 107.8681419
- 107.8681569
- 107.8681508
- 107.8681672
- 107.8681385
- 107.8681518
- 107.8681662
- 107.8681424
- 107.8681360
- 107.8681333
- 107.8681610
- 107.8681477
- 107.8681079
**Instrument Number: 2**
- 107.8681976
- 107.8681344
- 107.8681513
- 107.8681197
- 107.8681385
- 107.8681642
- 107.8681365
- 107.8681151
- 107.8681082
- 107.8681517
- 107.8681448
- 107.8681198
- 107.8681482
- 107.8681334
- 107.8681609
- 107.8681101
- 107.8681512
- 107.8681469
- 107.8681360
- 107.8681261
- 107.8681450
- 107.8681368
This set of data seems to represent precise measurements possibly related to weights or sensor readings. Each measurement corresponds to an entry recorded by one of two instruments, indicating a comparison or analysis of precision between different tools.
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VIEWStep 2: Perform hypothesis test to determine if their is evidence for existence of improper calibration.
VIEWStep 3: Construct a 99% confidence interval for the difference in the estimated atomic weights.
VIEWStep 4: Check the assumptions of the hypothesis test in a).
VIEWStep 5: Compute an appropriate effect size for the difference in estimates between the two techniques.
VIEWStep 6: Estimate the difference in calibrations having 90% chance of detection for this dataset.
VIEWStep 7: Determine sample size needed to get 80% chance of detecting a calibration difference.
VIEWStep 8: Construct a plot to show the mean silver weight measured on both instruments.
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