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Theoretical Quantiles Theoretical Quantiles 7) Let's use the the data above for male kestrel length, but this time with the addition of 2 more birds (n = 12). Here are the data, sorted to help you. Most of the normal scores are also given: Length(cm): 26.1 26.4 27.0 27.0 27.2 27.3 27.3 27.7 27.9 28.4 28.5 29.1 -0.812 -0.549 -0.319 -0.105 0.105 0.319 0.549 0.812 Z-scores: (a) Calculate the missing normal scores (the first two and the last two). (b) Now construct a q-q plot (normal probability plot). Do this by hand.

Theoretical Quantiles Theoretical Quantiles 7) Let's use the the data above for male kestrel length, but this time with the addition of 2 more birds (n = 12). Here are the data, sorted to help you. Most of the normal scores are also given: Length(cm): 26.1 26.4 27.0 27.0 27.2 27.3 27.3 27.7 27.9 28.4 28.5 29.1 -0.812 -0.549 -0.319 -0.105 0.105 0.319 0.549 0.812 Z-scores: (a) Calculate the missing normal scores (the first two and the last two). (b) Now construct a q-q plot (normal probability plot). Do this by hand.

MATLAB: An Introduction with Applications
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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Answer only question 7 all the way at the bottom. Make sure you show all your work

11:07 Not Secure - mason.gmu.edu (a) Which test (problem (3) or problem (4)) lets you reject the null hypothesis? (b) Which test do you *think* has more power? 30 Wh Usually, but not always(!!), the test with the most power has a lower p-value. (c) If you don't know that the population variances are equal, which test should you use? (d) Which test should you use here? (Refer to (c)). Big hint and comment: This is an example of when the classic (= equal variance) t-test can make a serious mistake. Rejecting a null hypothesis when it is not appropriate is a pretty serious mistake. Note also that the sample sizes are very different. (If you're theoretically inclined, here's what happens: even though we set α = 0.05, the classic t-test makes a type I error at a much higher rate than 5%. In other words, despite setting α = 0.05, the actual value of a 0.05, which is obviously not good!) 6) Match the q-q plots on the next page with the appropriate letter: (A) skewed left (D) long tailed but symmetrical (B) skewed right (E) short tailed PLOT 1 (C) approximately normal PLOT 2 Sample Quantiles 15 c Sample Quantiles 10 10 3 2 2 -2 -1 1 2 Theoretical Quantiles PLOT 3 -2 -1 1 2 Theoretical Quantiles Sample Quantiles ф 2 Sample Quantiles 0.4 0.6 ZO 10 -1 0 Theoretical Quantiles PLOT 4 -1 0 Theoretical Quantiles 7) Let's use the the data above for male kestrel length, but this time with the addition of 2 more birds (n = 12). Here are the data, sorted to help you. Most of the normal scores are also given: Length(cm): 26.1 26.4 27.0 27.0 27.2 27.3 27.3 27.7 27.9 28.4 28.5 29.1 Z-scores: -0.812 -0.549 -0.319 -0.105 0.105 0.319 0.549 0.812 (a) Calculate the missing normal scores (the first two and the last two). (b) Now construct a q-q plot (normal probability plot). Do this by hand. Be prepared to discuss these problems in recitation the week of March 25th.
Transcribed Image Text:11:07 Not Secure - mason.gmu.edu (a) Which test (problem (3) or problem (4)) lets you reject the null hypothesis? (b) Which test do you *think* has more power? 30 Wh Usually, but not always(!!), the test with the most power has a lower p-value. (c) If you don't know that the population variances are equal, which test should you use? (d) Which test should you use here? (Refer to (c)). Big hint and comment: This is an example of when the classic (= equal variance) t-test can make a serious mistake. Rejecting a null hypothesis when it is not appropriate is a pretty serious mistake. Note also that the sample sizes are very different. (If you're theoretically inclined, here's what happens: even though we set α = 0.05, the classic t-test makes a type I error at a much higher rate than 5%. In other words, despite setting α = 0.05, the actual value of a 0.05, which is obviously not good!) 6) Match the q-q plots on the next page with the appropriate letter: (A) skewed left (D) long tailed but symmetrical (B) skewed right (E) short tailed PLOT 1 (C) approximately normal PLOT 2 Sample Quantiles 15 c Sample Quantiles 10 10 3 2 2 -2 -1 1 2 Theoretical Quantiles PLOT 3 -2 -1 1 2 Theoretical Quantiles Sample Quantiles ф 2 Sample Quantiles 0.4 0.6 ZO 10 -1 0 Theoretical Quantiles PLOT 4 -1 0 Theoretical Quantiles 7) Let's use the the data above for male kestrel length, but this time with the addition of 2 more birds (n = 12). Here are the data, sorted to help you. Most of the normal scores are also given: Length(cm): 26.1 26.4 27.0 27.0 27.2 27.3 27.3 27.7 27.9 28.4 28.5 29.1 Z-scores: -0.812 -0.549 -0.319 -0.105 0.105 0.319 0.549 0.812 (a) Calculate the missing normal scores (the first two and the last two). (b) Now construct a q-q plot (normal probability plot). Do this by hand. Be prepared to discuss these problems in recitation the week of March 25th.
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