From generation to generation, the mean age when smokers first start to smoke varies. However, the standard deviation of that age remains constant of around 2.1 years. A survey of 40 smokers of this generation was done to see if the mean starting age is at least 19. The sample mean was 18.1 with a sample standard deviation of 1.3. Do the data support the claim at the 5% level? H0: μ ≥ 19 H1: μ < 19 You will need to specify the appropriate hypothesis, identify the statistical test, estimate p-value (using R command pnorm for Z test or pt for T test), and state your conclusion in the context of the problem. The decision tree to identify which test to use is attached. For the conclusion, please use the following template. If you reject the null write Since p-value is [write the value of your p-value] and is less than [write the value of alpha in percent] we reject the null hypothesis at [write the value of alpha]% significance level. That is, there is sufficient evidence in the data to reject [write down the null hypothesis in the context of the problem] If you fail to reject the null write Since p-value is [write the value of your p-value] and is greater than [write the value of alpha in percent], we fail to reject the null hypothesis at [write the value of alpha]% significance level. That is, there is not sufficient evidence in the data to reject [write down null in the context of the problem]

College Algebra

7th Edition

ISBN:9781305115545

Author:James Stewart, Lothar Redlin, Saleem Watson

Publisher:James Stewart, Lothar Redlin, Saleem Watson

Chapter9: Counting And Probability

Section: Chapter Questions

Problem 2P: Family Planning A intend to have two children. What is tie probability that they will have child of...

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From generation to generation, the mean age when smokers first start to smoke varies. However, the standard deviation of that age remains constant of around 2.1 years. A survey of 40 smokers of this generation was done to see if the mean starting age is at least 19. The sample mean was 18.1 with a sample standard deviation of 1.3. Do the data support the claim at the 5% level?

H₀: μ ≥ 19

H₁:μ < 19

You will need to specify the appropriate hypothesis, identify the statistical test, estimate p-value (using R command pnorm for Z test or pt for T test), and state your conclusion in the context of the problem.

The decision tree to identify which test to use is attached.

For the conclusion, please use the following template.

If you reject the null write
Since p-value is [write the value of your p-value] and is less than [write the value of alpha in
percent] we reject the null hypothesis at [write the value of alpha]% significance level.
That is, there is sufficient evidence in the data to reject [write down the null hypothesis in the
context of the problem]

If you fail to reject the null write
Since p-value is [write the value of your p-value] and is greater than [write the value of alpha in
percent], we fail to reject the null hypothesis at [write the value of alpha]% significance level.
That is, there is not sufficient evidence in the data to reject [write down null in the context of the
problem]

Decision tree for Hypothesis Testing for the mean (u) of a Single Population
if n < 30
✓
Sample Size (n)
Use Z-Test
if
the population is (approx)
Normal
if σ is known
if n ≥ 30
Use T-Test
if
if o is unknown
Sample Size (n)
if n < 30
the population is (approx)
Normal
Use Z-Test
This DOES NOT require the assumption of
population being (approx) Normal
[because x_bar is approx. Normal by CLT]
if n ≥ 30
Use Z-Test
(use the value of 's' as a substitute for 'o'
This DOES NOT require the assumption
of population being (approx) Normal
[because x_bar is approx. Normal by CLT]

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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