Calculating Probability with Normal Distribution Sample from N(μ=50, σ2=100)

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Homework Statement



Let X1, X2,...,X16 be a random sample of size 16 from N(μ=50, σ2=100) distribution.

Find P(Xbar > 50 + .6505(s))

Homework Equations



Z= (xbar - μ)/(σ/√n)

The Attempt at a Solution



So I know the solution of this problem is given by P( T(15 d.f.) > 2.602 ) but I'm not sure why.

I notice that you get the value 2.602 by plugging (50 + .6505(s)) in for xbar in the Z equation.

I guess I'm not really sure why we use the T distribution here and how you're supposed to come up with the value 2.602. 15 degrees of freedom makes sense.
 
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Phox said:

Homework Statement



Let X1, X2,...,X16 be a random sample of size 16 from N(μ=50, σ2=100) distribution.

Find P(Xbar > 50 + .6505(s))

Homework Equations



Z= (xbar - μ)/(σ/√n)

The Attempt at a Solution



So I know the solution of this problem is given by P( T(15 d.f.) > 2.602 ) but I'm not sure why.

I notice that you get the value 2.602 by plugging (50 + .6505(s)) in for xbar in the Z equation.

I guess I'm not really sure why we use the T distribution here and how you're supposed to come up with the value 2.602. 15 degrees of freedom makes sense.

You have to use the Student's t distribution because your sample size is so small. As I recall the cutoff is about n = 28. For your problem, n = 16.
 
Mark44 said:
You have to use the Student's t distribution because your sample size is so small. As I recall the cutoff is about n = 28. For your problem, n = 16.

Ok. That makes sense.

I suppose I'm confused because in the previous problem we were asked to find P(xbar >52) and we used z scores/normal cdf
 
Phox said:

Homework Statement



Let X1, X2,...,X16 be a random sample of size 16 from N(μ=50, σ2=100) distribution.

Find P(Xbar > 50 + .6505(s))

Homework Equations



Z= (xbar - μ)/(σ/√n)

The Attempt at a Solution



So I know the solution of this problem is given by P( T(15 d.f.) > 2.602 ) but I'm not sure why.

I notice that you get the value 2.602 by plugging (50 + .6505(s)) in for xbar in the Z equation.

I guess I'm not really sure why we use the T distribution here and how you're supposed to come up with the value 2.602. 15 degrees of freedom makes sense.

What, exactly, do you mean by 's' in the expression Xbar > 50 + 0.6505 s ? If 's' is the sample standard deviation, you need to use the t-distribution because you are essentially asking for the distribution of T = (Xbar - μ)/s (or maybe (Xbar - μ)/(s/√n), depending on what s actually represents). You would use the normal distribution if you wanted Xbar > 50 + 0.6505 σ with known σ = 10. In other words, use N for (Xbar - μ)/σ and use T for (Xbar - μ)/s.
 
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Ray Vickson said:
What, exactly, do you mean by 's' in the expression Xbar > 50 + 0.6505 s ? If 's' is the sample standard deviation, you need to use the t-distribution because you are essentially asking for the distribution of T = (Xbar - μ)/s (or maybe (Xbar - μ)/(s/√n), depending on what s actually represents). You would use the normal distribution if you wanted Xbar > 50 + 0.6505 σ with known σ = 10. In other words, use N for (Xbar - μ)/σ and use T for (Xbar - μ)/s.

's' represents the sample standard deviation.

I'm still a bit unclear as to how we come up with the value 2.602
 
Phox said:
's' represents the sample standard deviation.

I'm still a bit unclear as to how we come up with the value 2.602

2.602 = 4 \times 0.6505 = \sqrt{16} \times 0.6505
 
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