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3) Let's examine the levels of levels of sodium in the blood. 20 people yield the following results (in mEq/L): y = 135.95 s=2.544 (a) Test Ho: 133 using a = 0.001 (that's not a typo). (b) Figure out the p-value. To do this, take the t* value that you calculated in (a) and use R: pt (absolute-value-of-your-t*, df, lower.tail = FALSE) *2 Since it's a two sided test, you need to multiply by 2 at the end. We'll talk more about this in lecture when we do one sided tests; for now just realize that without the "*2" at the end R gives you a one sided p-value. For example, if your t* = 4.65 and you have 67 degrees of freedom you would do: pt(4.65,67,lower.tail = FALSE) *2 and you would get back 1.609352e-05 (c) Is the p-value smaller than a? (d) Why is this (c) important (see also part (a))? It is essential that you understand question (c)! (e) What is the smallest value of a for which you would reject the Ho? Hint: this will not be a "standard" value of a. The correct answer here is a value that is not only small, but totally absurd). Another hint: think about the relationship of p-values to a. As mentioned in (d) it is very important that you understand the connection between a and p-values. (f) For which of the following values of a would you reject? Why (see (c))? i).10 ii) .05 iii) .01 iv) .001 v) .00000001 (note that no one in their right mind would actually use a = .00000001)

3) Let's examine the levels of levels of sodium in the blood. 20 people yield the following results (in mEq/L): y = 135.95 s=2.544 (a) Test Ho: 133 using a = 0.001 (that's not a typo). (b) Figure out the p-value. To do this, take the t* value that you calculated in (a) and use R: pt (absolute-value-of-your-t*, df, lower.tail = FALSE) *2 Since it's a two sided test, you need to multiply by 2 at the end. We'll talk more about this in lecture when we do one sided tests; for now just realize that without the "*2" at the end R gives you a one sided p-value. For example, if your t* = 4.65 and you have 67 degrees of freedom you would do: pt(4.65,67,lower.tail = FALSE) *2 and you would get back 1.609352e-05 (c) Is the p-value smaller than a? (d) Why is this (c) important (see also part (a))? It is essential that you understand question (c)! (e) What is the smallest value of a for which you would reject the Ho? Hint: this will not be a "standard" value of a. The correct answer here is a value that is not only small, but totally absurd). Another hint: think about the relationship of p-values to a. As mentioned in (d) it is very important that you understand the connection between a and p-values. (f) For which of the following values of a would you reject? Why (see (c))? i).10 ii) .05 iii) .01 iv) .001 v) .00000001 (note that no one in their right mind would actually use a = .00000001)

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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If your not going to answer all 6 questions, don't answer this than, or else I'm gna mark the answer as incorrect even if you got it right, so only answer all 6 if your going to answer. also for B u can just figure out the P value, DONT worry about what it says about using "R"

3) Let's examine the levels of levels of sodium in the blood. 20 people yield the following results (in mEq/L): y = 135.95 s=2.544 (a) Test Ho: 133 using a = 0.001 (that's not a typo). (b) Figure out the p-value. To do this, take the t* value that you calculated in (a) and use R: pt (absolute-value-of-your-t*, df, lower.tail = FALSE) *2 Since it's a two sided test, you need to multiply by 2 at the end. We'll talk more about this in lecture when we do one sided tests; for now just realize that without the "*2" at the end R gives you a one sided p-value. For example, if your t* = 4.65 and you have 67 degrees of freedom you would do: pt(4.65,67,lower.tail = FALSE) *2 and you would get back 1.609352e-05 (c) Is the p-value smaller than a? (d) Why is this (c) important (see also part (a))? It is essential that you understand question (c)! (e) What is the smallest value of a for which you would reject the Ho? Hint: this will not be a "standard" value of a. The correct answer here is a value that is not only small, but totally absurd). Another hint: think about the relationship of p-values to a. As mentioned in (d) it is very important that you understand the connection between a and p-values. (f) For which of the following values of a would you reject? Why (see (c))? i).10 ii) .05 iii) .01 iv) .001 v) .00000001 (note that no one in their right mind would actually use a = .00000001)
Transcribed Image Text:3) Let's examine the levels of levels of sodium in the blood. 20 people yield the following results (in mEq/L): y = 135.95 s=2.544 (a) Test Ho: 133 using a = 0.001 (that's not a typo). (b) Figure out the p-value. To do this, take the t* value that you calculated in (a) and use R: pt (absolute-value-of-your-t*, df, lower.tail = FALSE) *2 Since it's a two sided test, you need to multiply by 2 at the end. We'll talk more about this in lecture when we do one sided tests; for now just realize that without the "*2" at the end R gives you a one sided p-value. For example, if your t* = 4.65 and you have 67 degrees of freedom you would do: pt(4.65,67,lower.tail = FALSE) *2 and you would get back 1.609352e-05 (c) Is the p-value smaller than a? (d) Why is this (c) important (see also part (a))? It is essential that you understand question (c)! (e) What is the smallest value of a for which you would reject the Ho? Hint: this will not be a "standard" value of a. The correct answer here is a value that is not only small, but totally absurd). Another hint: think about the relationship of p-values to a. As mentioned in (d) it is very important that you understand the connection between a and p-values. (f) For which of the following values of a would you reject? Why (see (c))? i).10 ii) .05 iii) .01 iv) .001 v) .00000001 (note that no one in their right mind would actually use a = .00000001)
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